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Student Athlete Drug Testing

U.S. Sports Academy2016-04-01T09:57:44-05:00February 13th, 2008|Contemporary Sports Issues, Sports Management|

Submitted by: Joseph C. Franz, M.D.

Since the June 1995 U. S. Supreme Court ruling in support of random interscholastic student athlete drug testing, more schools then ever before have begun either mandatory, reasonable suspicion or voluntary types of drug testing as they battle drug abuse by their students. By far most student drug testing programs consist of mandatory testing of only student athletes since the U.S. Supreme Court upheld this type of testing. Some schools have begun drug testing all co-curricular students or students wishing to drive to school. This latter action was challenged in Rush County, Indiana, and upheld by the District Court. When appealed to the U. S. Supreme Court they allowed the District Court ruling to stand.

Schools contemplating a drug testing program must first document their student athletes are using drugs to comply with the U.S. Supreme Court ruling. Likewise it is imperative that they rally community support for such a program in order for it to be a helpful tool used both my school officials and parents. Urine drug testing is the industry standard and recommended over hair or saliva testing which may not be defendable in court.

Student Drug Testing Options

Drug testing programs can be mandatory, as with interscholastic student athletes, voluntary as part of a student assistance program, or based on reasonable suspicion only. Random urine drug testing by far is the most deterrent to drug use by students since the students may be selected at any time for testing. This type program gives the students another reason to say “No!” However such a program requires more testing be done which elevates the total cost of the program. Voluntary programs do help those students caught breaking the rules by using drugs or alcohol, but has little impact on students using and not getting caught. Reasonable Suspicion programs are very effective at keeping drugs out of schools but have little deterrence to use by students in general.

Drugs to Screen for

A student drug testing program must screen for the appropriate illicit drugs and banned substances. Most schools have student codes of conduct and/or athletic codes of conduct that state illicit drugs are not to be used and most include tobacco as a banned substance. The substance abuse coordinator from your school should be able to tell you what drugs or substances your students are using and abusing. This list will probably include Pre-Game Drugs like tobacco (smoked and chewed), marijuana, pain medications (often used with parent knowledge) and anabolic steroids. After games, the Post-Game Drugs will include tobacco, marijuana, alcohol, LSD, and inhalants. There are several “club drugs” that students are starting to use including ecstacy, a methamphetamine known as MDMA, and ketamine, a veterinary anesthetic. Ecstacy has stimulation and hallucinogenic effects and often used at parties called Raves where students dance wildly and often dehydrate from elevated body temperatures. Unfortunately one dose of ecstacy causes permanent brain damage. During a Rave a student may take as many as 15 hits of Ecstacy. Current urine drug testing can discover Ecstacy but only when ordered as a special test and at considerable expense. There is not a screening test yet available for Ecstacy or Ketamine.

Currently most certified laboratories offer a standard Substance Abuse Panel -10 (SAP-10) which screen for the following ten drugs:

Amphetamines
Barbiturates
Benzodiazepines (Valium®)
Cocaine
Marijuana
Methadone
Methaqualone
Opiates (Codeine)
Phencyclidine
Propoxyphene (Darvon®)

Many other chemical substances can be detected in the urine, and considering the drug use patterns of today’s youth, the following additional drug screens can be ordered:

Alcohol
Anabolic Steroids
LSD
Nicotine (Tobacco)
MDMA (Ecstacy)

In the laboratory, the SAP-10 is automated and therefore less expensive to do. The other drugs must be tested for by different methods or at special locations, resulting in higher prices. The typical school will pay from $25 to $50 for each SAP-10 ordered, with urine alcohol costing $6 – $10 each, LSD $22-25 each, urine nicotine costs $10-12 each, and anabolic steroids costing $80-95 each. For this price, you should get MRO services as well (see Medical Review Officer section).

Since the drugs abused mostly by teenagers today consist of tobacco, marijuana, alcohol and LSD, a drug abuse intervention program must screen for these chemicals. Simply doing the industry standard of a SAP-10 is not enough. However, detection of alcohol in the urine is not very reliable since it is eliminated from the body very quickly. A drug screen for alcohol done on Tuesday is not likely to find alcohol that was consumed on Saturday night. LSD also leaves the body very quickly and is hard to catch. Therefore, schools often do weekend collection to deter the use of alcohol by their athletes.

A Certified Laboratory is a Must

There are many laboratories, both local and national, who advertise the ability to do urine drug testing. However, not every lab uses the same methods nor are they all certified by the Government. Therefore, it is imperative that only Government certified laboratories are used for any student drug testing program. This is the only way you can be assured that your results are accurate. If your policy will deny the privilege to participate in sports or other co-curricular activities when a positive test is found, your school will be in really hot water if your results are wrong. Any lab your medical vendor uses must be certified by the Substance Abuse and Mental Health Services Administration(SAMHSA) and should have a minimum of ten years of experience in toxicology testing and chair-of-custody procedures. Sport Safe Testing Service uses Quest Diagnostics, Inc. exclusive for testing due to their many years experience with athlete drug testing.

Analysis of Specimens

There are two levels of analysis that occur routinely with urine drug abuse screens. The sample is first subjected to an automated screening test that quickly looks for the presence of specified drugs or their metabolites. This initial testing uses a highly accurate immunoassay technique commonly called an EMIT®. All presumptive positive results should be confirmed by a Gas Chromatography/Mass Spectroscopy (GC/MS) confirmatory tests. This confirmation method provides a “molecular fingerprint” of the drug and/or metabolite, providing a high level of accuracy and specificity. The quantitative results, in nanograms per milliliter, are usually reported as well. Currently the GC/MS confirmatory test is the only acceptable industry standard for drug abuse screen confirmations. Thin layer chromatography, as sometimes offered by non-certified labs, is not acceptable.

Second-Hand Exposure

The first words out of a teen’s mouth when told their urine showed marijuana is that they were in a car with someone who was smoking and therefore that is why their test came up positive. It is very true that detectable levels of both THC (active ingredient of marijuana) and nicotine can be found in those individuals having close exposure to the smoke of the burning tobacco or marijuana. The urine of young children whose parents smoke will have detectable nicotine. For this reason, a series of cutoff levels has been determined and proven scientifically so when a urine drug screen is positive, we know it is from use and not second-hand exposure. For THC the standard is 20-50 nanograms (ng) per milliliter in the screening test and 15 ng/ml by GC/MS. Nicotine has to be above 300 ng/ml to be called positive. When a drug screen is reported as positive, the actual quantitative levels are reported to the Medical Review Officer. This data is becoming more important in determining recent use verses natural decay of levels in the body. The levels for nicotine are less standardized and often take careful interpretation by the MRO.

Medical Review Officer

A Medical Review Officer (MRO) is a licensed physician who has additional training and certification in the area of drug testing. Specifically they have learned how drug testing is done, what affects the results, specifically medications and foods, and how individuals will try and adulterate the specimens to give false negative results. A physician can be certified by the Medical Review Officer Certification Council (MROCC) or the American Association of Medical Review Officers.

Any program of drug testing involving students should have a certified MRO to review all results and make a final certification as to being positive or negative. The MRO must be willing to phone parents when a positive result is found to verify if any medication has been prescribed. This is very important since medications like Tylenol® with codeine could be legally prescribed for a student following a tooth extraction and that student having a drug test would be positive for opiates. The MRO’s job is to verify if any medication has been prescribed for the student which could have resulted in the positive result. If the MRO receives from the prescribing physician or dentist documentation that a codeine containing medication was prescribed, the MRO will rule the test negative. However, if the parent happened to give the student one of his or her pills, and the student has no legal prescription for the medication, then the MRO must rule this test positive since a controlled drug was given and taken without the order of a licensed physician. (Believe it or not, athletes, with full knowledge of their parents, have taken pain medications prior to athletic competition to make their overused joints hurt less during that day’s events). Having an MRO adds significant credibility to any program and shares the burden of liability the school is placed under. For more information and contact Sport SafeTesting Service, Inc., 18 Grace Drive, Powell OH 43065 or call (614) 847-0847. Sample policies are available on our web site at www.sportsafe.com.

Correspondence concerning this article should be addressed to Dr. Joseph C. Franz, Medical Director, SPORT SAFE Testing Service, Inc., 18 Grace Drive, Powell, OH 43065. Phone/Fax:(614) 847-0874. Sample policies are available at www.sportsafe.com.

United States Anti-Doping Agency Protocol For Olympic Movement Testing

U.S. Sports Academy2013-11-27T16:27:27-06:00February 13th, 2008|Contemporary Sports Issues, Sports Management|

Submitted by: Richard Bell, Ed.D.

USADA’s Relationship with the United States Olympic committee (“USOC”)USADA is an independent legal entity not subject to the control of the USOC. The USOC has contracted with USADA to conduct drug testing and results management for participants in the Olympic movement within the United States and to provide educational information to those participants. For the purposes of transmittal of information by USADA, the USOC is USADA’s client/ However, the USOC has authorized USADA to transmit information simultaneously to the relevant National governing Body (“NGB”), International Federation (“IF”) the World Anti-Doping Agency (“WADA”) and involved athlete.

Athletes Subject to Testing USADAThe USOC and NGBs have authorized USADA to test the following athletes:
1. Any athlete who is a member of a NGB;
2. Any athlete participating at a competition sanctioned by the USOC or a NGB;
3. Any foreign athlete who would otherwise be subject to testing by USADA, the USOC or NGB; or
4. Any other athlete who has given his/her consent to testing by USADA.
5. Any athlete who has been named by the USOC or an NGB or is competing in a qualifying event to represent the USOC or NGB is in international competition.

USADA will not allow the testing process to be used to harass any athlete. In selecting athletes for testing, USADA will focus primarily on athletes who are participating or have the potential to participate, in international competition.

Choice of Rules In conducting drug testing and results management under this protocol, USADA will look to the following sources of rules:

The selection and collection procedures set forth in paragraphs 4, 5, & 6

herein shall apply to all testing done by USADA unless different procedures are agreed to between USADA and the party requesting the test for a particular event.

All test performed by USADA shall be analyzed by IOC-accredited laboratories. In analyzing samples for USADA, those laboratories shall follow the standards established by the IOC.
Tests performed by USADA shall be analyzed for the categories of prohibited and restricted substances set forth in the rules of the applicable IF unless agreed otherwise between USADA and the party ordering the test.
USADA shall be responsible for results management of all tests performed by it and all other tests for which the applicable IF rules require the initial adjudication forth in paragraph 9 herein, unless otherwise referred by USADA to a foreign sports organization having jurisdiction over the athlete.

Selection of Athletes to be Tested In-Competition
USADA shall have the authority to determine which athlete will be selected for testing in all competitions tested by USADA. In making this determination, USADA will normally follow NGB or IF selection procedures and will include at a minimum the selection formulas or requests for target selection on particular athletes which are proposed by the USOC or a particular NGB. USADA retains the right to test any athlete that it chooses, with or without cause or explanation.

Selection of Athletes to be Tested Out-of-Competition USADA shall have the authority to determine which athlete will be selected for testing out-of-competition testing by USADA. In making this determination, USADA will carefully consider selection formulas or requests for target selection on particular athletes which are proposed by the USOC or a particular NGB. USADA retains the right to test any athlete that it chooses, with or without cause or explanation.
Each NGB will provide USADA with a regularly updated list of athletes to have included in No Advance Notice or other out-of competition testing. With respect to each athlete on such list and such additional athletes as may be designated by USADA, the NGB will provide USADA with the information as set forth on the athlete location form attached as Annex A. Thereafter it shall be the responsibility of each individual athlete to provide USADA with updated information as to his or her whereabouts.

Sample Collection Sample collection by USADA will substantially conform to the standards set forth by the IOC and the World Anti-Doping Agency.

Laboratory Analysis All samples collected by USADA will be sent for analysis only to IOC-accredited laboratories.

Notification USADA will provide the following notification will respect to each laboratory report received by USADA:

Upon receipt of a negative laboratory report, USADA will promptly forward that result to the athlete, the USOC and the applicable NGB.
Upon receipt of a positive laboratory A report or a report indicating an elevated testosterone, epitestosterone ratio or epitestosterone concentration, USADA will promptly notify the applicable NGB and athlete at the address on the Doping Control Notifications/Signature Form and shall advise the athlete of the date on which the laboratory will conduct the B sample analysis. The athlete may attend the B sample analysis accompanied by a representative at his or her own expense. Prior to the B sample opening, USADA shall provide to the athlete the A sample laboratory documentation set forth on Annex B. A sample shall not be considered positive until after the B sample analysis confirms the A sample analysis.
Upon receipt of the laboratory’s B sample report, USADA shall promptly notify the USOC, the applicable NGB and the athlete. USADA shall then provide to the athlete the B sample documentation package set forth on Annex C. The laboratory shall not be required to produce any documentation in addition to Annexes B and C unless ordered to do so by an arbitrator(s) during adjudication, in which case it shall be produced at the athlete’s expense.
In special circumstances where USADA is conducting testing for an IF, regional or continental sports organization or other Olympic movement sporting body, other than the USOC or an NGB, the notification described in this section shall be made exclusively to that sporting body, the athlete, and , if applicable, to the USOC and NGB.

Results Management Whenever USADA receives a laboratory report confirming positive test, elevated testosterone or epitestosterone ration or epitestosterone concentration, or when USADA has other reason to believe that a doping violation has occurred, such as admitted doping, address that case through the following results management procedures:
Upon USADA’s receipt of a laboratory report identifying an analytically positive or elevated B test result, the following steps shall be taken:
1. ADJUDICATION
  1. Following receipt of the Review Board Recommendations, USADA shall notify the athlete in writing whether USADA considers the matter closed or alternatively what specific charges or alleged violations will be adjudicated and what sanction, consistent with IF rules, USADA is adjudicated and what sanction, consistent with IF rules, USADA is seeking the have imposed (an other possible sanctions which could be imposed under the applicable IF rules). The notice shall also include a copy of the USADA Protocol for Olympics Sport Testing and the modifications to AAA Commercial Rules. Within ten (10) days following such notice, the athlete must notify USADA if he or she desires a hearing to contest the sanction sought by USADA. If the sanction is to contested, then it shall be communicated by USADA to the USOC, the applicable NGB and If and WADA and thereafter imposed by the NGB. If the sanction is contested by the athlete, then a hearing shall be conducted pursuant to the procedure set forth below.
  2. The hearing will take place before the American Arbitration Association (“AAA”) using a single arbitrator (or a three arbitrator panel if demanded by either of the parties) selected from a pool of the North American Court of Arbitration for Sports (“CAS”) Arbitrators who shall also be AAA Arbitrators. The hearing will take place in the U.S., be administered by Decentralized Office of CAS in the Americas (the “Administrator”), and the conducted under modified AAA Commercial Rules attached as Annex D. The parties will be USADA and the athlete. USADA shall also invite the applicable IF to participate either as a party or as an observer. For their information only, notice of the hearing date shall also be sent to the USOC, the applicable NGB and WADA.
  3. Either the athlete or the IF(whether a party or not) shall be entitled to appeal the AAA arbitrator(s) decision to CAS. A CAS appeal shall be filed with the Administrator and the CAS hearing will automatically take place in the U.S. Otherwise the regular CAS appellate rules apply. The decision of CAS shall be final and binding on all parties and shall to be subject to further review or appeal.
  4. The athlete, within ten (10) days following the Notice described in section (i) above, shall be entitled, at his or her option, to elect to bypass the hearing described in section (ii) above and proceed directly to a single final hearing before CAS conducted in the United States. The CAS decision shall be final and binding on all parties and shall not be subject to further review or appeal.
  5. In all hearings conducted pursuant to this procedure the applicable IF’s categories of prohibited substance, definition of doping and sanctions shall be applied. In the event an IF’s rules are silent on a issue, the rules set for the in the Olympic Movement Anti-Doping Code shall apply. Notwithstanding the foregoing; (a) The IOC laboratories used by USADA shall be presumed to have conducted testing and custodial procedures in accordance to prevailing and acceptable standards a of scientific practice. This presumption can be rebutted by evidence to the contrary, but the accredited laboratory shall have no onus in the first instance to show that it conducted the procedures other than in accordance with its standard practices conforming to any applicable IOC requirements; (b) minor irregularities in sample collection, sample testing or other procedures set forth herein which cannot reasonablely be considered to have effected the results of an otherwise valid test or collection shall have no effect on such results; and (c) if contested, USADA shall have the burden of establishing the integrity of the sample collection process, the chain of custody of the sample, the accuracy of laboratory test results by clear and convincing evidence unless the rules of the applicable IF set a higher standard.
  6. All administrative costs of the USADA review and adjudication process will be borne by USADA except the CAS appeal fee which will be refunded to eh athlete by USADA should the athlete prevail on appeal.
  7. The results of all hearings shall be communicated by USADA to the athlete, the USOC, the applicable NGB and If and WADA. The NGB shall impose any sanction resulting from the adjudication process. The NGB shall not impose any sanctions until after the athlete has had the opportunity for a hearing pursuant to section 9(b)ii or 9(b)iv.
Ownership and Use of Samples All samples collected by USADA shall be the property of USADA. USADA may authorize the use of negative samples for research; however, in such event all markings on the sample which identify the ample as coming from a particular athlete shall be obliterated.
Confidentially Except for the notifications to the USOC, NGB, IF, WADA (or other sporting body ordering the test) as otherwise provided in this protocol, USADA shall not publicly disclose an athlete’s positive test result or other alleged doping violation until after the athlete has been found to have committed a doping violation in a hearing conducted under either article 9(b)(ii) or 9(b)(iv) above. USADA may release aggregate statistics of testing and adjudication results.
Expedited Procedures USADA may shorten any time period set fourth in these procedures where doing so is reasonable necessary to resolve an athlete’s eligibility before a protected competition.

Generic Alcoholism: Are College Athletes at Risk?

U.S. Sports Academy2016-10-12T11:42:46-05:00February 13th, 2008|Contemporary Sports Issues, Sports Management, Sports Studies and Sports Psychology|

Submitted by: Michael Moulton, Ed.D

Alcohol and other drug use by college athletes have received increased attention in recent years. The purpose of this study was to explore the relationship of collegiate athletes and non-athletes drinking patterns to those of generic alcoholism. The findings revealed a large portion of the college sample, both athlete and non-athlete, reported alcohol dependency as indicated by the scores of the Michigan Alcoholism Screening Test (MAST). Additionally, a significant difference was found to exist between males and females with respect to their scores on the MAST.

In recent years alcohol and other drug use by college athletes has received increased attention by the media. The drug-related deaths and arrests of several professional athletes have fueled the public interest in examining the role which alcohol and other drugs play in the lives of athletes. Despite the general perception that athletes are more health-conscious than their non-athlete counterparts, studies indicate that athletes abuse drugs regularly with alcohol as the most widely abused drug of all (Evans, Weinberg, & Jackson, 1992; Anderson, Albrecht, McKeag, Hough, & McGrew, 1991).

Over the past two decades very few studies have investigated alcohol use among college athletes and compared their use to student non-athletes. However, the findings of the studies which have been conducted (Overman & Terry, 1991; Anderson et al., 1991; Vance, 1982) indicate that minimal differences in alcohol use exist between these two groups. In a large national survey Anderson et al. (1991) found that nearly 89 percent of collegiate athletes reported alcohol use during the previous 12 months compared to 91.5 percent of the general population of college students. Similar findings were observed in a study comparing alcohol use and attitudes among college athletes and non-athletes (Overman & Terry, 1991). In this study, the researchers found no evidence that alcohol and other drug use is higher among college athletes than the rest of the student population. Furthermore, Vance (1982) reported NCAA survey findings indicated that athletes and non-athletes do not differ with respect to alcohol use.

In comparison, numerous studies have been conducted investigating alcohol use among high school athletes and non-athletes. The findings in these studies have been somewhat conflicting. Shields (1995) and Forman, Dekker, Javors, and Davison (1995) found a lower prevalence of alcohol use by student-athletes as compared to non-athletes. In contrast, a comprehensive study conducted by Rainey, McKeown, Sargent, and Valois (1996) found that adolescent athletes reported more drinking and binge drinking than did non-athletes. Similarly, in a study comparing alcohol use and intoxication in high school athletes and non-athletes, researchers found that athletes drank more frequently and reported less abstinence from alcohol consumption than student non-athletes (Carr, Kennedy, & Dimick, 1990).

Reviewing the literature for both the college and high school athlete populations in respect to alcohol use is important. Recent research indicates unhealthy drinking patterns in college may begin in high school (Anderson et al., 1991). Specifically, Anderson et al. (1991) found that 63 percent of the college athlete sample who reported using alcohol and drugs had their first experiences while in high school and 22 percent in junior high school.

Based on the findings reported, research is indicating that when studying substance use at the high school level, athletes are reporting drinking more alcohol more frequently that non-athletes. In addition, it appears that college athletes are not more health conscious, with regard to substance use, that their non-athletic counterparts. These types of findings lead to questions regarding the long-term effects of alcohol use by athletes. Are collegiate athletes at risk for developing generic alcoholism? So far, there have been no studies conducted examining and comparing college athletes and non-athletes and their tendency toward generic alcoholism using an alcoholism screening questionnaire. The purpose of the current study was to explore the relationship of collegiate athletes and non-athletes drinking patterns to those of generic alcoholism. Specifically, the study was designed to determine if significant differences existed between college athletes and non-athletes with regard to scores on the Michigan Alcoholism Screening Test (MAST) (Selzer, 1971). The secondary purpose of this study was to determine if gender differences existed between and within the two groups.

Method

Participants
A sample of 367 undergraduate students attending psychology and health courses at a small Southern university volunteered to participate in this study for extra credit points. Approximately 34 percent were male (n = 123) and 66 percent were female (n = 244) with approximately 74 percent between the ages of 18 and 21. There were 327 non-athletes and 38 athletes; Data from two of the participants were not included in the subject pool due to missing information about athletic status.

For the purpose of this study, only the data from the subjects who scored between 5 and 9 on the Michigan Alcoholism Screening Test (Selzer, 1971) were used. Thirty-four percent of the participants scored in this range: 110 non-athletes and 15 athletes; 44 males and 81 females.

Materials
The Michigan Alcoholism Screening Test (MAST) (Selzer, 1971) and a demographic information sheet were used to collect data. The MAST is used to predict alcohol dependence. For this study’s purposes, only data from the subjects scoring between 5 and 9 on the MAST were used in the analysis. Scores in this range indicate an 80 percent association with generic alcoholism (Selzer, 1971). The demographic information sheet asked questions about age, gender, and athletic status. Athletic status was determined by participation in a college varsity sport.

Procedures
Students from selected courses in the Psychology and Health and Human Performance Departments were asked to participate in the study. Recruitment occurred during the subjects’ regularly scheduled class times using sign-up sheets for testing sessions. During this time the subjects were told the amount of extra credit they would receive for their participation. Testing occurred at various class times within one week. Each testing session lasted approximately 45 minutes. Prior to the distribution of the surveys, the subjects received a description of the study and an informed consent form, and were allowed to withdraw at any time without penalty. They were also advised that their answers would remain anonymous. After returning the informed consent forms, subjects received instructions and the questionnaires, which included the MAST and demographics sheet.

The subject’s responses from the questionnaires were entered on a general scantron sheet without their names to ensure confidentiality.

Results

Thirty-four percent (44 males and 81 females) of the total sample scored in the
5 – 9 category of the MAST. A two-way analysis of variance (ANOVA) for unequal sample sizes was computed to find if the differences in scores on the MAST were significant between and within the sample of athletes and non-athletes. Table II reports the findings of this analysis.

Table 1 Analysis of Variance – Michigan Alcoholism Screening Test
Source of Variation	df	Sums of Squares	Mean Square	F	P
Main Effects	2	10.175	5.088	8.760	.000
Athletic Status

110.15610.15617.488.000

Gender

14.7174.7178.122.005

2-Wat Interactions16.8016.80111.711.001

Athletic Status X

Gender

16.0816.08111.711.001 Within12170.274.581 Total12481.888.660

The Analysis of Variance Summary Table indicated that there was a significant difference between athletes and non-athletes with respect to their scores in the 5 – 9 category of the MAST, F.01 = (1,121) = 17.488, p < .001. The mean score (M = 6.87) for athletes was significantly higher than the mean score (M = 6.26) for non-athletes. (See Table II) There were also significant differences between males and females with respect to their scores in the 5 – 9 category of the MAST, F.01= (1, 121) = 8.122, p < .005. The mean score (M = 6.45) for males was significantly higher than the mean score (M = 6.27) for females. (See Table II) It is notable that while males (N = 44) scored significantly higher on the MAST, the frequencies of females (F = 81) reporting a 5 – 9 generic range was higher.

Table 2 Group Means of the Michigan Alcoholism Screening Test
	M	SD
Athlete	6.8667	1.187
Non-Athlete	6.2636	.725
Males	6.4545	.901
Females	6.2716	.758

Finally, the test for the interaction of athletic status and gender was significant,
F.01(1,121) = 11.71, p < .001. However, due to the relatively low number of female athletes in the sample, further investigation into the interaction was not conducted.

Discussion

The findings revealed that a large proportion of the college sample used in this study reported alcohol dependence as indicated by their scores on the MAST. These findings correspond very closely to the large percentage of college student binge drinkers found in a large-scale study by Weschler, Davenport, Dowdall, Moeykens, and Castillo (1994). The results from this study indicated that 44 percent of the nation’s college students engaged in binge drinking behaviors. While it is acknowledged that binge drinking is a separate construct from generic alcoholism, binge-drinking behaviors are considered as primary indicators of alcoholism (Diagnostic and Statistical Manual of Mental Disorders, 1994).

The findings of the current study are in direct contrast with earlier studies (Overman & Terry, 1991; Anderson et al., 1991; Vance, 1982) indicating minimal differences in alcohol use between athletes and non-athletes. The present study revealed that there were significant differences between athletes and non-athletes with respect to their scores on the MAST. Athletes scored higher on the MAST than did non-athletes, suggesting that alcohol dependency is greater among athletes than for the general student body. Several possibilities have been suggested as to why athletes might abuse alcohol more than non-athletes. Falk (1990) investigated the various sociological and psychological factors associated with the chemically dependent athlete. Obsessive compulsive personality features, difficulty in maintaining interpersonal relationships, preoccupation with body image and physical appearance, and inability to cope with high expectations are a few of the factors identified by Falk. It appears that athletes have specific pressures and concerns directly related to athletic participation. Additionally, there may be a lack of awareness, information and/or support for many athletes in developing positive coping skills to address the pressure surrounding athletics.

The findings also indicated that significant differences exist between males and females with respect to their scores on the MAST. Males scored higher on the MAST than did females indicating that males have a greater dependency for alcohol than females. These results are supported by several other studies that found alcohol frequency and consumption rates to be higher among males than females (Weschler et al., 1994; Overman & Terry, 1991; Flynn & Shoemaker, 1989).

Based upon the results of this study, two factors that are associated with alcohol dependency in college are participation in athletics and being male. However, the number of females scoring in the 5 – 9 category in this study indicate that females (athlete or non-athlete) are at risk for developing alcohol dependency similarly to their male counterparts. This is evident in several studies that found minimal differences between females and males (athlete or non-athlete) in regards to their drinking behaviors (Anderson et al., 1991; Center on Addiction and Substance Abuse, 1994; Anderson & McKeag, 1985).

The 5 – 9 category of the MAST scores was chosen to meet specific purposes in the present study. This 5 – 9 scoring is considered to be a conservative estimate when aiding in the clinical diagnosis of alcohol dependence. It is considered to eliminate false positives in the adult population. This means that a higher incidence of high-risk behavior is needed to categorize an individual as dependent. This category of scoring (5 – 9) was deemed the most appropriate for the present study due to its conservative nature, the progressiveness of the disease of alcoholism, the peer culture, and the developmental stage of the college population.

Findings such as these indicate a strong need for further research in this area beyond the preliminary study. Future research needs to address design issues such as sample and cell size. In addition, focus may be placed on the effects of various sports on alcohol behaviors, specific indicators of athletes at risk, early prevention, and positive coping skills. Continued research and application is needed to aid young individuals, both athletes and non-athletes, in meeting their full potential.

References

American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. (1994) Washington, DC, American Psychiatric Association.

Anderson, W. A., Albrecht, R. R., McKeag, D. B., Hough, D. O., & McGrew, C. A. (1991). A national survey of alcohol and drug use by college athletes. The Physician and Sportsmedicine, 19(2), 91-104.

Anderson, W. A., & McKeag, D. B. (1985). The substance use and abuse habits of college student-athletes (Report No. 2). Mission, KS: The National Collegiate Athletic Association.

Carr, C. N., Kennedy, S. R., & Dimick, K. M. (1990). Alcohol use among high school athletes: A comparison of alcohol use and intoxication in male and female high school athletes and non-athletes. The Journal of School Health, 66(1), 27-32.

Center on Addiction and Substance Abuse (CASA). (1994). Commission reports on substance abuse on american campuses. The Alcoholism Report [On-line], 22(5), 4-5. Available: http://pogo.edc.org/hec/pubs/catalst4.txt

Evans, M., Weinberg, R., & Jackson, A. (1992). Psychological factors related to drug use in college athletes. The Sport Psychologist, 6, 24-41.

Falk, M. A. (1990). Chemical dependency and the athlete: Treatment implications. Alcoholism Treatment Quarterly, 7(3), 1-16.

Flynn, C. A, & Shoemaker, T. A. (1989). Alcohol and college athletes: Frequency of use versus perceptions of others. NASPA Journal, 27(2), 172-176.

Forman, E. S., Dekker, A. H., Javors, J. R., & Davison, D. T. (1995). High-risk behaviors in teenage male athletes. Clinical Journal of Sports Medicine, 5, 36-42.

Overman, S. J., & Terry, T. (1991). Alcohol use and athletes: A comparison of college athletes and nonathletes. Journal of Drug Education, 21(2), 107-117.

Rainey, C. J., McKeown, R. E., Sargent, R. G., & Valois, F. (1996). Patterns of tobacco and alcohol use among sedentary, exercising, non-athletes and athletic youth. Journal of School Health, 66(1), 27-32.

Selzer, M. L. (1971). The michigan alcoholism screening test: The quest for a new diagnostic instrument. American Journal of Psychiatry, 127, 1653-1658.

Shields, E. W. (1995). Sociodemographic analysis of drug use among adolescent athletes: Observations-perceptions of athletic directors-coaches. Adolescence, 30(120), 839-860.

Vance, N. S. (1982, September 1). Colleges urged to teach athletes the dangers of drug abuse and “doping”. Chronicle of Higher Education, pp. 25, 28.

Wechsler, H., Davenport, A., Dowdell, G., Moeykens, B., & Castillo, S. (1994). Health and behavioral consequences of binge drinking in college: A national survey of students at 140 campuses. The Journal of the American Medical Association, 272(21), 1672-1677.

Correspondence concerning this article should be addressed to Michael Moulton, moultonm@nsula.edu, (318) 357-5142.

Factors Associated with Success Among NBA Teams

U.S. Sports Academy2013-11-27T16:29:09-06:00February 13th, 2008|Sports Coaching, Sports History, Sports Management, Sports Studies and Sports Psychology|

Submitted by: Anthony J. Onwuegbuzie

Abstract

Data from the 1997-1998 National Basketball Association (NBA) regular season were analyzed to determine factors that best predicted success, as measured by winning percentage. A total of 20 variables were examined. A multiple regression analysis revealed that field goal conversion percentage was the best predictor of success, explaining 61.4% of the variance in winning percentage. The average three-point conversion percentage of the opposing teams explained a further 18.9% of the variance. These two variables combined explained 80.3% of the variance in winning percentage. The finding pertaining to field goal conversion percentage suggest that the attainments of the offense are more important than are the defensive attainments in predicting the success levels of NBA teams. These and other implications are discussed.

Introduction

The game of basketball was invented in December 1891 by Dr. James A. Naismith while an instructor in the physical training department of the International Young Men’s Christian Association (YMCA) Training School in Springfield, Massachussets (Fox, 1974). Naismith’s goal was to answer the challenge of Dr. Luther H. Gulick, his department head, who wanted an indoor game to be invented that (1) would attract young men during the winter, when baseball and football were out of season, and (2) would replace gymnastics and calisthenics, which provoked little interest (Fox, 1974). Naismith, known as “the father of basketball,” incorporated features of soccer, U.S. football, rugby football, field hockey, and other outdoor sports in developing the game of basketball.

By 1946, professional basketball had acquired a large and faithful following among U.S. sports fans, who wanted to watch their former collegians in action. During this period, there was the American Basketball League (ABL) on the East Coast and the National Basketball League (NBL) in the Midwest. In June, 1946, the Basketball Association of America was formed, which effectively replaced the ABL and competed directly with the NBL (Fox, 1974). The BAA and the NBL merged in 1950 as the National Basketball Association (NBA), comprising 17 teams. The NBA was reduced to 10 teams in 1951, as 7 NBL teams with marginal franchises dropped out (Fox, 1974). However, in the 1970s, the NBA expanded to 22 teams. Presently, the NBA contains 29 teams, with 15 teams in the Eastern Conference (with 7 teams representing the Atlantic division and 8 teams representing the Central division) and 14 teams in the Western Conference (with 7 teams representing the Midwest division and 7 teams representing the Pacific division). Basketball is now one of the most popular sports in the United States. Indeed, in the 1997-1998 season (the last time a full 82-game season was played), a total of 8,877,309 people attended an NBA game (The Sports Network, 1998), with an average attendance of 17,135 people per game (USATODAY, 1999).

Currently, at the end of the regular season, that is, when each team has played 82 matches, the top eight teams in each conference qualify for the playoffs. These eight teams then participate in a knockout tournament with the eventual winners of this stage within each conference advancing to the NBA finals. Because the teams which advance to the playoffs are those that have the highest winning percentages in their respective divisions during the regular season, knowledge of factors which predict success during this period would be of educational value for NBA coaches and analysts. Indeed, the former group could use this information to target coaching interventions.

Basketball is abound with empirical facts. Surprisingly, however, only descriptive statistics (e.g., averages, totals, percentages) tend to be utilized. Conversely, few inferential statistical analyses are undertaken on NBA data. Yet, such analyses provide consumers with information regarding the relationships among variables. As such, inferential statistics can yield very detailed and important information to consumers of professional basketball. Moreover, inferential statistics can be used to determine factors that predict the performance levels of teams.

To date, only a few studies have investigated correlates of basketball-related performance. Of those that have, the majority have involved an examination of psychological antecedents of basketball performance. For example, Whitehead, Butz, Vaughn, and Kozar (1996) found that increased stress (assumed to be present in games as opposed to practices) among members of an NCAA Division I men’s varsity team was associated with longer pre-shot preparations and a greater incidence of overthrown shots.

Newby and Simpson (1994) reported (1) a statistically significant negative relationship between minutes played by a sample of men and women college basketball players and mood, (2) a statistically significant negative relationship between the number of assists and depression, (3) a statistically significant negative relationship between the number of turnovers committed and mood, and (4) a statistically significant positive relationship between the number of turnovers committed and degree of tension. The researchers concluded that success in basketball is negatively related to psychopathology.

Both Pargman, Bender, and Deshaires (1975) and Browne (1995) found no relationship between free-throw and field goal shooting and field independency/field dependency. Additionally, Shick (1971) found no relationship between hand-eye dominance and depth perception and free-throw shooting ability in college women. Hall and Erffmeyer (1983) examined the effect of imagery combined with modeling on free-throw shooting performance among female college basketball students. These researchers noted that players who shot free throws under the conditions of videotaped modeling combined with relaxation and imagery were significantly more accurate than were those who shot in the relaxation and imagery condition only.

All the above studies investigated correlates of specific basketball skills (e.g., free-throw shooting), and, with a few exceptions (e.g., Butz et al., 1996), these skills typically were examined under simulated conditions. Such studies, although interesting, have limited utility for basketball coaches, in particular, because they does not provide any information as to why or how a team wins a basketball game. Indeed, the only inquiry found determining factors associated with success among basketball players was that of Steenland and Deddens (1997). These researchers studied the effects of travel and rest on performance, utilizing the results for 8,495 regular season NBA games over eight seasons (1987-1988 through 1994-1995). Findings revealed a statistically significant positive relationship between the amount of the time that elapsed between games and performance level. Specifically, more than 1 day between games was associated with a mean increase of 1.1 points for the home team and 1.6 points for the visitors. Peak performance occurred with 3 days between games. The researchers theorized that the negative effects of little time between games may be due more to insufficient time for physical recovery than to the effects of circadian rhythm (i.e., jet lag). However, although not statistically significant, they also found that visiting teams performed four points better, on average, when they traveled from the west coast to the east coast than when they traveled form east to west.

Surprisingly, no other study has investigated predictors of success among NBA teams. Even more surprising is the fact that no research appears to have examined what factors directly associated with skill level (e.g., field goal conversion percentage) best predict a team’s winning percentage. This was the purpose of the present inquiry. A secondary goal was to determine whether offensive or defensive factors would have more predictive power. It was expected that knowledge of these factors could help coaches to decide where to focus their attention, as well as assist analysts and fans in predicting a team’s performance.

Method
The data comprised all 21 unique team-level variables (when both team averages and totals were presented, only the averages were utilized, since they rendered totals redundant) that were presented on the official NBA website (i.e., http://www.nba.com) for the 1997-1998 regular professional basketball season. (The 1997-1998 NBA season was chosen because it represented the last time a full 82-game season was played.) These variables comprised winning percentage, which was treated as the dependent measure and 20 other variables which were utilized as independent variables. All variables are presented in Table 1. Scores pertaining to each variable for each team were analyzed using the Statistical Package for the Social Sciences (SPSS; SPSS Inc., 1999).

Table 1 Pearson Product-Moment Correlations of Winning Percentage and Selected Variables for the 1997-1998 Regular NBA Season

Variable	Winning Percentage
three-point conversion percentage	.38
field goal conversion percentage	.78*
free-throw conversion percentage	.03
average number of offensive rebounds per game	-.31
average number of defensive rebounds per game	.47
number of total rebounds	.19
average number of assists per game	.61*
average number of steals per game	.08
average number of blocks per game	-.13
number of points scored per game	.57*
field goal conversion percentage of the opposing teams	-.68*
average three-point conversion percentage of the opposing teams	-.50
average free-throw conversion percentage of the opposing teams	.18
average number of offensive rebounds per game of the opposing teams	-.49
average number of defensive rebounds per game of the opposing teams	-.71*
average number of total rebounds of the opposing teams	-.69*
average number of assists per game of the opposing teams	-.70*
average number of steals per game of the opposing teams	-.45
average number of blocks per game of the opposing teams	-.58*
average number of points scored per game of the opposing teams	-.70*
* statistically significant after the Bonferroni adjustment

Results and Discussion
Table 1 presents the correlations between winning percentage and each of the selected variables. It can be seen that, after adjusting for Type I error (i.e., the Bonferroni adjustment), winning percentages increased with field goal conversion percentage, number of assists per game, and number of points scored per game, and decreased with field goal conversion percentage of the opposing teams, average number of defensive rebounds per game of the opposing teams, average number of total rebounds per game of the opposing teams, average number of assists per game of the opposing teams, average number of blocks per game of the opposing teams, and average number of points per game of the opposing teams.

An all possible subsets (APS) multiple regression (Thompson, 1995) was used to identify which combination of independent variables best predicted NBA teams’ success. Again, success was measured by NBA teams’ regular season winning percentages. For this study, the criterion used to determine adequacy of the model was the maximum proportion of variance explained (i.e., R2), which provides an important measure of effect size (Cohen, 1988). Specifically, all variables were included except for those that represented (1) the total number of points scored or the total number of rebounds (use of the number of defensive rebounds and offensive rebounds rendered use of the total number of rebounds redundant). Consequently, a total of 16 independent variables were analyzed.

The multiple regression analysis revealed that the following two variables made a statistically significant contribution (F [2, 26] = 53.12, p < .0001) to the model: field goal conversion percentage and average three-point conversion percentage of the opposing teams. The regression equation was as follows:

winning percentage =
-159.53 + {(7.90) X field goal conversion percentage} – {(4.24) X average three-point conversion percentage of the opposing teams}

The regression equation indicates that every 1 percentage increase in field goal conversion rate is associated with a 7.90% increase in winning percentage. The confidence interval corresponding to this variable suggests that we are 95% certain that every 1 percentage increase in field goal conversion rate is associated with an average increase in winning percentage of between 6.00% and 9.80%. Additionally, every 1 percentage increase in the three-point conversion rate of the opposing teams is associated with a 4.24% decrease in winning percentage (95% confidence interval is 2.49% to 5.99%).

With respect to predictive power of the model, field goal conversion percentage explained 61.4% of the variance in winning percentages, whereas average three-point conversion percentage of the opposing teams explained 18.9%. These two variables combined to explain 80.3% of the total variance in winning percentage (adjusted R2 = 78.8%). In the study of human behavior, this percentage is extremely large, suggesting that an NBA team’s success can be predicted with an excellent degree of accuracy.

Conclusions
The purpose of this study was to determine which variables best predict whether an NBA team’s success rate. The finding that field goal conversion percentage explains more than three times the variance in success than does the average three-point conversion percentage of the opposing teams suggests that the attainments of the offense are more important than are the defensive attainments in predicting whether an NBA team will be successful. Thus, the present finding is in contrast to Onwuegbuzie (1999a), who identified four multiple regression models which adequately predicted the winning percentages of National Football League (NFL) teams for the 1997-1998 regular football season–the most notable being a two-variable model comprising turnover differential (which explained 43.4% of the variance in success) and total number of rushing yards gained by the offense (which explained a further 9.3% of the variance). Based on these models, Onwuegbuzie concluded that, outside the 20-yard zone, the attainments of the defense are more important than are the offensive attainments in predicting whether an NFL team is successful.

The present result pertaining to NBA teams also is in contrast to Onwuegbuzie’s (1999b) replication study of NFL teams for the 1998-1999 football season in which a model was identified containing the following five variables: (1) turnover differential (which explained 54.4% of the variance); (2) total number of rushing yards conceded by the defense (which explained 21.3% of the variance); (3) total number of passing first downs attained by the offense (which explained 9.4% of the variance), (4) percentage of third-down plays that produce a first down (which explained 4.1% of the variance), and (5) total number of penalties conceded by the opponents’ defense resulting in a first down (which explained 4.1% of the variance). Onwuegbuzie concluded that defensive gains are better predictors of success than are offensive gains because the first two variables, which explained more than 75% of the variance, were characteristics of the defense.

The finding that field goal percentage rate explained a very large proportion of the variance in success (i.e., 61.4%) highlights the importance of offensive efficiency not only of the starting players but also of the “bench” players, since the latter group also contribute to the field goal percentage rate. Nevertheless, the fact that three-point conversion percentage also made a contribution to the regression model, albeit a smaller one, suggests the importance of teams forcing the opposition to hurry their three-point shots and to take these shots from non-optimal parts of the basketball court.

Although a significant proportion of the variance in winning percentage was explained by the selected variables, this study also should be replicated using data from other seasons. Furthermore, regression models should be fitted using college basketball data. Information from such analyses should help coaches and analysts alike to obtain objective data which can be used to monitor the performance of NBA teams.

References

Browne, G.S. (1995). Cognitive style and free throw shooting ability of female college athletes. Unpublished master’s thesis, Valdosta State University, Valdosta, Georgia.

Cohen, J. (1988) Statistical power analysis for the behavioral sciences. New York: Wiley.

Fox, L. (1974). Illustrated history of basketball. New York, NY: Grosset & Dunlap.

Hall, E.G., & Erffmeyer, E.S. (1983). The effect of visuo-motor behavior rehearsal with video taped modeling of free-throw shooting accuracy of intercollegiate female basketball players. Journal of Sport Psychology, 5, 343-346.

Newby, R.W., & Simpson, S. (1994). Basketball performance as a function of scores on profile of mood states. Perceptual and Motor Skills, 78, 1142.

Onwuegbuzie, A.J. (1999a). Defense or Offense? Which is the better predictor of success for professional football teams? Perceptual and Motor Skills, 89, 151-159.

Onwuegbuzie, A.J. (1999b, November). Is defense or offense more important for professional football teams? A replication study using data from the 1998-1999 regular football season. Paper presented at the annual meeting of the Midsouth Educational Research Association, Point Clear, AL.

Pargman, D., Bender, P., & Deshaires, P. (1975). Correlation between visual disembedding and basketball shooting by male and female varsity athletes. Perceptual and Motor Skills, 41, 956.

Shick, J. (1971). Relationships between depth perception and hand-eye dominance and free-throw shooting in college women. Perceptual and Motor Skills, 33, 539-542.

SPSS Inc. (1999) SPSS 9.0 for Windows. [Computer software]. Chicago, IL: SPSS Inc.

Steenland, K., & Deddens, J.A. (1997). Effect of travel and rest on performance of professional basketball players. Sleep, 20(5), 366-369.

The Sports Network. (1998). Statistics: 1997-1998 NBA attendance. The Sports Network, 21(21).

Thompson, B. (1995). Stepwise regression and stepwise discriminant analysis need not apply here: A guidelines editorial. Educational and Psychological Measurement, 55, 525-534.

USATODAY. (December 28, 1999). Inside the numbers. Retrieved January 28, 2000 from the World Wide Web: http://www.usatoday.com/sports/basketba/skn/numbers.htm.

Whitehead, R., Butz, J.W., Vaughn, R.E., & Kozar, B. (1996). Stress and performance: An application of Gray’s three-factor arousal theory to basketball free-throw shooting. Journal of Sport Behavior, 19(4), 354-364.

Footnote
1 Due to space constraints, the intercorrelations among all the variables is not presented. However, this can be obtained by contacting the author.

Address correspondence to Anthony Onwuegbuzie, Department of Educational Leadership, College of Education, Valdosta State University, Valdosta, Georgia, 31698 or e-mail (TONWUEGB@VALDOSTA.EDU).

Surgical Reconstruction of the Anterior Cruciate Ligament: The Central Quadriceps Tendon as an Alternative Graft Source

U.S. Sports Academy2020-06-02T16:16:34-05:00February 13th, 2008|Contemporary Sports Issues, Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology|

Submitted by: Albert W. Pearsall, IV, MD

*Red numbers
indicate references

INTRODUCTION
Significant advances in surgical reconstruction of the anterior
cruciate ligament (ACL) have been made since Jones’ described
open reconstruction with the central one-third patellar tendon
in 1963.29 Advancements in technology, arthroscopic instrumentation,
and surgical skills have decreased surgical morbidity while improving
functional outcome.5,
23 Continued technological
and surgical improvements in the 1990’s eventually enabled surgeons
to perform ACL reconstructions endoscopically. SIZE=”-2″>3, 4, 19, 23, 24, 37

During the evolution of ACL reconstruction surgery, numerous
graft sources have been described. Currently, the most commonly
utilized tissues for ACL reconstruction are autologous semitendinous/gracilis
tendons (ST-G), central one-third patellar tendon (B-PT-B), and
allograft patellar tendon. >13, 14, 21, 22, 31, 32, 46, 49, 50
Each of these grafts has been touted
to reliably restore knee stability, thereby enabling many patients
to return to pre-injury activity levels. Despite these reports,
complications have been noted with all three types of tendons,
the most frequent being anterior knee pain. SIZE=”-2″>1, 6, 7, 9, 10, 12, 17, 18

Based upon its proven efficacy,
the central 1/3 autologous patellar tendon is considered by a
large number of orthopaedic surgeons to be the graft of choice
in the symptomatic ACL-deficient patient. However, the incidence
of anterior knee pain with the use of this graft has been reported
from 13% to 47%, which diminishes the functional outcome in a
large percentage of individuals. SIZE=”-2″>1, 35, 43-45, 51 Moreover, due to technical factors such as tunnel
angle and graft length, many B-PT-B grafts cannot be secured
at the joint level, resulting in non-anatomic graft fixation.
In an effort to eliminate these problems, other graft sources
have been explored. The ideal ACL graft should result in minimal
or no damage to the patient’s tissues after harvest. It should
enable immediate rigid fixation and reproduce the normal anatomy
of the native ACL. It should also restore normal proprioception
and kinematics to the knee. Although numerous graft sources have
been reported, currently, no graft material, autograft or allograft,
can meet all these requirements.

In an effort to minimize post-surgical
anterior knee pain after ACL reconstruction, the use of semitendinosus/gracilis
tendons has been reported. Advocates of ST-G (hamstrings) point
out that post-operative patellar pain is diminished by virtue
of the patellar mechanism not being violated during graft harvest.
Various authors have reported the incidence of anterior pain
to vary from 3% to 21% following hamstrings ACL reconstruction.<FONT
COLOR=”#ff0000″ SIZE=”-2″>2, 11, 15, 26, 30,
33, 42 However, in the
author’s experience, the use of hamstrings for ACL reconstruction
does not eliminate anterior knee pain in many patients. In addition,
some authors have reported increased tibial translation in females
after ST-G ACL reconstruction. >16

Allograft B-PT-B has been advocated
as an alternative graft source due to the lack of harvest morbidity
and decreased operative time required. SIZE=”-2″>25, 32, 36, 41, 46 However, despite the diminished risk of disease
transmission, opponents of allografts cite reports of prolonged
graft-tunnel healing and intraarticular reactions to some allografts.<FONT
COLOR=”#ff0000″ SIZE=”-2″>28, 40

As a result of the continued
controversy regarding the correct ACL graft source, an alternative
graft has emerged, the central quadriceps tendon (CQT). The central
quadriceps tendon was reported as a graft source as early as
1979 by Marshall et al, however, it did not gain popularity among
surgeons until the 1980’s and 1990’s. SIZE=”-2″> 8, 21, 34, 47 Proponents of the CQT cite it’s greater cross-sectional
area, lower strain at failure, and lower modulus of elasticity
when compared to patellar tendon. SIZE=”-2″>48
Advocates have also cited the lower incidence of patellofemoral
symptoms after CQT graft usage. >20, 31
Our experience at the University of South Alabama Medical Center
is similar, with less then 5% of patients demonstrating postoperative
anterior knee pain symptoms after CQT ACL reconstruction.

The CQT consists of a central
portion of the quadriceps tendon approximately 10-11mm wide.
The graft depth extends 7mm with an average length of approximately
80-90mm. When the graft is harvested as the initial portion of
the surgical procedure, the central portion is obtained without
violation of the suprapatellar pouch or transection of the quadriceps
tendon. This eliminates the need to repair the pouch or tendon
before proceeding with the arthroscopic portion of the procedure.

Initial descriptions of the use of the CQT described harvest
of the tendon without a bone block from the patella.31 Prior
to the development of bioabsorable screws for soft tissue fixation,
such a graft would have required the tendon ends had to be secured
by sutures tied over a post, such a staple, button, or screw.
Several biomechanical studies have demonstrated that such fixation
does not reconstitute the normal isometricity of the ACL, with
increased instability noted as the tibial side is fixed further
away from the articular surface. SIZE=”-2″>27, 38
Consequently, many authors now advocate graft fixation near the
articular surface insertions of the native ACL. SIZE=”-2″>39
When the CQT is being contemplated as a graft source, articular
fixation can be accomplished by harvesting a patellar bone block
and fixing both ends of the graft with bioabsorbable screws near
the surface of the tibia and femur.

SURGICAL TECHNIQUE
After previous studies (radiographs, MRI) and clinical examination
confirm that the ACL is disrupted and causing symptomatic instability,
the patient is brought to the operating room for reconstruction.
The CQT is harvested through a short 2-3 inch incision obliquely
along the lines of the quadriceps mechanism. After delineation
of the quadriceps tendon, a 10mm x 7mm x 85mm graft is harvested,
being careful to not violate the suprapatellar pouch. At the
distal end of the quadriceps tendon a 10mm x 25mm x 8mm bone
plug is harvested from the proximal end of the patella. The patellar
defect can be later filled with cancelleous bone from the tibial
reamings or with allograft chips. The CQT is sized on a back
table to fit through the smallest tunnel that the tendon (not
the bone) will glide through easily; the bone plug is trimmed
to fit accordingly. This usually represents 9-10mm. Two #2 Ethibond
sutures are placed in the patellar bone plug, while two #1 Ethibond
sutures are whipped stitched in the tendon end.

After the stitches are in place
and CQT has been sized, appropriate markings are made to aid
the surgeon during arthroscopic reconstruction. In our use of
the CQT, we place the tendon side in the femoral tunnel, with
the patellar bone block in the tibia. First, a pen mark is made
at the bone-tendon junction. Next, a distance of 35mm is measured
from the CQT-bone junction. This marked area represents the approximate
intraarticular distance of the native ACL. This distance is approximately
30mm in most individuals, however, we allocate an additional
5mm in case the graft slides more proximally in the femoral tunnel.
The distance of the remaining tendon represents the portion of
the tendon that will be pulled into the femoral tunnel (~25mm).
The following calculation is what we use in preparing the CQT
graft for implantation:
85mm {total graft} – 60mm {bone plug + intraarticular
tendon} = 25mm {femoral tunnel}
The graft is set in a moist sponge until later implantation.

After harvest of the CQT, a
routine knee arthroscopy is performed. We routinely perform a
5-7mm lateral notchplasty, along with debridement or repair of
any meniscal lesions. Using a standard tibial guide set at an
angle of 55o, we drill a 9mm tibial tunnel centered 5mm anterior
to the PCL within the footprint of the native ACL. After the
posterior portion of the tibial tunnel has been debrided of all
soft tissue and rasped posteriorly, a 7mm offset endoscopic guide
is placed through the tibial tunnel at the “10:30”
or “1:30” positions on the posterior femoral notch.
A 9-10mm femoral tunnel is reamed to the depth of the previous
calculations (~ 25mm).

After reaming, an eyed Beath
pin (Arthrex, Naples, FL) is placed in the femoral tunnel. Sequential
impaction dilatation of the tibial and femoral bone tunnels is
performed to increase the bone density of the tunnels for bioabsorable
screw placement. After the tunnels are dilated to the size of
the graft (9-10mm), the tendon side of the CQT is brought into
the femoral tunnel. Through the anteromedial or an accessory
anterior portal, a bioabsorable screw of the same diameter as
the femoral tunnel is placed anterior to the graft. Fixation
of the graft is assessed by pulling upon the tibial sutures,while
the knee is put through a range of motion. Tensioning the graft
through several motion cycles diminishes creep within the graft
prior to tibial fixation. After the graft is assessed in extension
for signs of impingement, the knee is placed in 10o-20o of flexion
with 5kg of tension place upon the tibial sutures. The graft
is fixed adjacent to the tibial articular surface with a 10mm
bioabsorable interference screw. The knee is assessed for anterior
tibial translation and the wounds closed with absorbable sutures.
Prior to waking the patient, an intraarticular pain pump is placed
within the knee.

CLINICAL EXPERIENCE
At the University of South Alabama Medical Center, our experience
with CQT spans over 2 years, with nearly 20 cases. To date we
are gathering 2 year follow-up data. 1 patient ruptured his graft
during athletics (collegiate athlete) at 9 months postoperatively.
No patient has reported significant patellofemoral pain and there
have been no ruptures of the quadriceps tendon. All patients
have been happy with their results, indicating that they believe
the procedure improved their quality of life.

Other authors have reported
good results with the CQT. Fulkerson reported excellent results
with the use of the CQT with either endobutton or bioabsorbable
screw fixation.20,
31 Leitman et al reported
on 65 CQT graft cases with a KT-1000 side to side differences
of 2.1mm at 1-2 year follow-up. The authors noted that no patient
had patellofemoral pain and all subjects had returned to their
previous level of activity with no instances of quadriceps tendon
rupture.31

CONCLUSIONS
Individuals with a disrupted anterior cruciate ligament and symptomatic
knee instability often require surgical reconstruction of the
ACL. Over the last several decades, tremendous technological
advances have enabled surgeons to reconstruct the ACL with a
more anatomic and durable graft, while minimizing postoperative
morbidity. As the evolution of ACL graft material continues,
numerous graft choices are available. The central quadriceps
tendon (CQT) is an alternative graft source with biomechanical
properties comparable to or better than a bone-patellar tendon-bone
or double-looped hamstrings graft. In early follow-up studies,
patients undergoing CQT ACL reconstruction have demonstrated
minimal patellofemoral symptoms and excellent clinical function.
The CQT provides another weapon in the orthopaedic surgeon’s
repertoire of surgical graft alternatives to reconstruct the
symptomatic ACL-deficient knee.

REFERENCES

1. Aglietti P, Buzzi R, D’Andria
  S, et al. Patellofemoral problems after intraarticular anterior
  cruciate ligament reconstruction. Clin Orthop 1993;228:195.
2. Aglietti P, Buzzi R, Zaccherotti
  G, et al. Patella tendon versus doubled semitendinosus and gracilis
  tendons for anterior cruciate ligament reconstruction. Am J Sports
  Med 1994;22:211.

Bach B. Technical pitfalls
Kurosaka interference screw fixation. Am J Knee Surg 1989;2:76-82.
Bach B, Tradonsky S, Bojchuk
J, et al. Arthroscopically assisted anterior cruciate ligament
reconstruction using patellar tendon autograft. Five to nine-year
follow-up evaluation. Am J Sports Med 1998;26:20-29.
Bach JB. Arthroscopy-assisted
patellar tendon substitution for anterior cruciate ligament insufficiency:
Surgical technique. Am J Knee Surg 1989;2:3-20.
Bear B, Cohen S, Bowen M,
et al. Patellar fracture after anterior cruciate ligament reconstruction
using bone patellar bone autogenous grafts. Orthop Trans 1996;29:9.
Berg E. Management of patellar
fractures associated with central third bone-patellar tendon-bone
autograft ACL reconstruction. Technical note. Arthroscopy 1996;12:756.
Blauth W. Die zweizugelige
Ersatzplastik des vorderen Kreuzband der Quadricepsshene. Unfallheilkunde
1984;87:45-51.
Bonamo J, Krinick R, Sparn
A. Rupture of the patellar ligament after use of its central-third
for anterior cruciate reconstruction. J Bone Joint Surg 1984;66-A:1294.
Bonatus T, Alexander A. Patellar
fracture and avulsion of the patellar ligament complicating arthroscopic
anterior ligament reconstruction. Orthop Rev 1991;20:770.
Brown C, Steiner M, Carson
E. The use of hamstring tendons for anterior cruciate ligament
reconstruction. Clin Sports Med 1993;12:723.
Christen B, Jakob R. Fractures
associated with patellar ligament grafts in cruciate ligament
surgery. J Bone Joint Surg 1992;74-B:617.
Clancy W, Nelson D, Reider
B, et al. Anterior cruciate ligament reconstruction using one
third of the patellar tendon augmented by extraarticular tendon
transfers. J Bone Joint Surg Am 1982;64:352-359.
Cooper D, Deng X, Burstein
A, et al. The strength of the central thord patellar tendon graft.
A biomechanical study. Am J Sports Med 1993;21:818-824.
Corry I, Webb J, Clingeleffer
A. Endoscopic reconstruction of the anterior cruciate ligament,
a comparison of patella tendon with four strand hamstring autograft.
(poster). In: 10th Combined Orthopaedic Associations Meeting;
1998; New Zealand; 1998.
Corry I, Webb J, Clingeleffer
A, et al. Arthroscopic reconstruction of the anterior cruciate
ligament. A comparison of patellar tendon autograft and four-strand
hamstring tendon autograft. Am J Sports Med 1999;27(3):444-454.
Crosby L, Kamins P. Fracture
of the patella during graft harvest for cruciate ligament reconstruction.
Complications in Orthopaedics 1991;6:104.
DeLee J, Craviotto D. Rupture
of the quadriceps tendon after a central-third patellar tendon
anterior cruciate ligament reconstruction. Am J Sports Med 1991:415.
Ferrari J, Bush-Joseph C,
Bach B. Anterior cruciate ligament reconstruction using bone-patellar
tendon-bone grafts: autograft and allograft endoscopic techniques
and two-incision autograft technique. Op Tech in Spts Med 1999;7(4):156-171.
Fulkerson J. Central quadriceps
free tendon for anterior curciate ligament reconstruction. Op
Tech Sports Med 1999;7(4):195-200.
Fulkerson J, Langeland R.
An alternative cruciate reconstruction graft: the central quadriceps
tendon. Arthroscopy 1995;11:252-254.
Hamner D, Brown C, Steiner
M, et al. Hamstring tendon grafts in ACL reconstruction: Biomechanics
of mltiple strands and tensioning techniques. J Bone Joint Surg
Am 1999;81:549-557.
Hardin G, Bach B, Bush-Joseph
C, et al. Endoscopic single incision ACL reconstruction using
patellar tendon autograft: Surgical technique. Am J Knee Surg
1992;5:144-155.
Harner C, Marks P, Fu F, et
al. Anterior cruciate ligament reconstruction: Endoscopic versus
two-incision technique. Arthroscopy 1994;10:502-512.
Harner C, Olson E, Irrgang
J, et al. Allograft versus autograft anterior cruciate ligament
reconstruction: 3- to 5- year outcome. Clin Orthop 1996;324:134-144.
Hormel S, Larson R, Larry
I. Arthroscopic anterior cruciate ligament reconstruction using
double-loop semitendinosus and gracilis tendons: A three-year
follow-up study. (paper 508). In: In final program American Academy
of Orthopaedic Surgeons 62nd Annual Meeting; Florida. p. 316.
Ishibashi Y, Rudy T, Livesay
G, et al. The effect of the anterior cruciate ligament graft
fixation level, on knee stability: Evaluations using a robotic
testing system. Arthroscopy 1997;13:177-182.
Jackson D, Windler G, Simon
T. Intraarticular reaction associated with the use of freeze-dried,
ethylene oxide-sterilized bone-patella tendon-bone allografts
in the reconstruction of the anterior cruciate ligament. Am J
Sports Med 1990;18:1-11.
Jones K. Reconstruction of
the anterior cruciate ligament: A technique using the central
third of the patellar ligament. J Bone Joint Surg Am 1963;45:925-932.
Larson R, Ericksen D. Complications
in the use of the hamstring tendons for anterior cruciate ligament
reconstruction. Sports Medicine and Arthroscopy Review 1997;5:83.
Leitman E, Morgan C, Grawl
D. Quadriceps tendon anterior cruciate ligament reconstruction
using the all-inside technique. Op Tech in Spts Med 1999;7(4):179-188.
Levitt R, Malinin T, Posada
A, et al. Reconstruction of anterior cruciate ligaments with
bone-patellar tendon-bone and achilles tendon allografts. Clin
Orthop 1994;303:67-78.
Maeda A, Shino K, Horibe S,
et al. Anterior cruciate ligament reconstruction with multistranded
autogenous semitendinosus tendon. Am J Sports Med 1996;24:504.
Marshall J, Warren R, Wickiewicz
T, et al. The anterior cruciate ligament. A technique of repair
and reconstruction. Clin Orthop 1979;143:97-106.
Martin R, Galloway M, Diagneault
J, et al. Patello-femoral pain following ACL reconstruction:
Bone grafting the patellar defect. Orthop Trans 1996;20:9.
Miller M, Harner C. The use
of allograft. Techniques and results. Clin in Spts Med 1993;12(4):757-770.
Miller M, Hinkin D. The “N
+ 7 rule” for tibial tunnel placement in endoscopic anterior
cruciate ligament reconstruction. Arthroscopy 1996;12:124-126.
Morgan C, Kalman C, Grawl
D. Isometry testing for ACL reconstruction revisited. Arthroscopy
1995;11:647-659.
Morgan C, Kalman V, Grawl D. Definitive landmarks for reproducible
tibial tunnel placement in anterior cruciate ligament reconstruction.
Arthroscopy 1995;11:275-288.
Nikolaou P, Seaber A, Glisson
R, et al. Anterior cruciate ligament allograft transplantation:
long-term function, histology, revascularization, and operative
technique. Am J Sports Med 1986;14:348-360.
Olson E, Harner C, Fu F, et
al. Clinical use of fresh, frozen soft tissue allografts. Orthopedics
1992;15(10):1225-1232.
O’Neill D. Arthroscopically
assisted reconstruction of the anterior cruciate ligament. A
prospective randomized analysis of three techniques. J Bone Joint
Surg 1996;78-A:803.
Rubinstein R, Shelbourne K.
Prevention of complications and minimizing morbidity after autogenous
bone-patella tendon-bone anterior ligament reconstruction. Oper
Tech Sports Med 1993;1:72.
Sachs R, Daniel D, Stone M,
et al. Patellofemoral problems after anterior cruciate ligament
reconstruction. Am J Sports Med 1989;17:760.
Shelbourne K, Trumper R. Preventing
anterior knee pain after anterior cruciate ligament reconstruction.
Am J Sports Med 1997;25:41.
Shino K, Kimura T, Hirose
H, et al. Reconstruction of the anterior cruciate ligament by
allogeneic tendon graft. J Bone Joint Surg 1986;68-B:739-746.
Staubli H. Arthroscopically
assisted ACL reconstruction using autologous quadriceps tendon.
In: Jakob R, Staubli H, editors. The Knee and the Cruciate Ligaments.
Berlin: Springer Verlag; 1992. p. 443-451.
Staubli H, Birrer S. The popliteus
tendon and tis fascicles at the popliteal hiatus: Gross anatomy
and functional arthroscopic evalution with and without anterior
cruciate ligament deficiency. Arthroscopy 1990;6:209-220.
Steiner M, Hecker A, Brown
A, et al. Anterior cruciate ligament graft fixation: Comparison
of hamstring and patellar tendon grafts. Am J Sports Med 1994;22:240-247.
Steiner M, Kowalk D. Anterior
cruciate ligament reconstruction using hemstrings for a two-incision
technique. Op Tech in Spts Med 1999;7(4):172-178.
Weiss R, Re L, Rintz K. Incidence
of anterior knee pain after treatment for anterior cruciate ligament
rupture. Arthroscopy 1933;9:366.

Address correspondence to:
Albert W. Pearsall, IV, MD
Department of Orthopaedic Surgery
University of South Alabama Medical Center
2451 Fillingim Street
Mobile, Alabama 36617
Email: apearsal@usamail.usouthal.edu

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