Association Between Patellar Tendon Abnormality and Land-Jump Biomechanics in Male Collegiate Basketball Players During the Preseason.

Background: Patellar tendinopathy is a degenerative condition that predominantly affects jumping athletes. Symptoms may be subtle or nonexistent at preseason, but structural abnormalities may be present. Assessing patellar tendon abnormality (PTA) through magnetic resonance imaging (MRI) and ultrasound (US) and classifying symptoms using the Victorian Institute for Sport Assessment-Patellar tendon (VISA-P) may provide useful insights if combined with biomechanics measurements. Purpose: To (1) assess whether land-jump biomechanical patterns are associated with clinically pertinent PTA as seen on imaging and through VISA-P scores and (2) model the contributing risk and accuracy of biomechanics to classify PTA and symptomatic observations. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A total of 26 National Collegiate Athletic Association Division I and II male basketball players (n = 52 limbs) were recruited during the preseason. We collected VISA-P scores, bilateral PTA through US and MRI morphology measurements, and bilateral 3-dimensional lower extremity kinematics and kinetics measurements from a land-jump test from an 18-inch-high (45.7-cm-high) box. Statistically, each limb was treated independently. The association of biomechanics with PTA and symptoms (VISA-P score <80) was tested with multivariate models and post hoc tests. Logistic regression modeled relative risk and accuracy of biomechanical variables to classify PTA and symptomatic limbs. Results: There were 19 to 24 limbs with PTA depending on US and MRI measurements. Differences in hip and knee kinematic strategies and ground-reaction loads were associated with PTA and symptomatic limbs. Peak landing vertical ground-reaction force was significantly decreased (169 ± 26 vs 195 ± 29 %body weight; P = .001), and maximum hip flexion velocity was significantly increased (416 ± 74 vs 343 ± 94 deg/s; P = .005) in limbs with versus without PTA on imaging. Knee flexion at the initial contact was decreased in symptomatic versus healthy limbs (17°± 5° vs 21°± 5°, respectively; P = .045). Regression models classified PTA limbs and symptomatic limbs with 71.2% to 86.5% accuracy. Hip and knee maximum flexion velocity and vertical ground-reaction force variables were most common across models observing clinically pertinent PTA. Conclusion: Our findings suggested that functional kinematic and kinetic biomechanical strategies at the hip and knee were associated with PTA, identified on imaging, and symptomatic limbs.

Development and Validation of an Electronic Medical Record Algorithm to Identify Phenotypes of Rotator Cuff Tear.

BACKGROUND: A lack of studies with large sample sizes of patients with rotator cuff tears is a barrier to performing clinical and genomic research. OBJECTIVE: To develop and validate an electronic medical record (EMR)-based algorithm to identify individuals with and without rotator cuff tear. DESIGN: We used a deidentified version of the EMR of more than 2 million subjects. A screening algorithm was applied to classify subjects into likely rotator cuff tear and likely normal rotator cuff groups. From these subjects, 500 likely rotator cuff tear and 500 likely normal rotator cuff were randomly chosen for algorithm development. Chart review of all 1000 subjects confirmed the true phenotype of rotator cuff tear or normal rotator cuff based on magnetic resonance imaging and operative report. An algorithm was then developed based on logistic regression and validation of the algorithm was performed. RESULTS: The variables significantly predicting rotator cuff tear included the number of times a Current Procedural Terminology code related to rotator cuff procedures was used (odds ratio [OR] = 3.3; 95% confidence interval [CI]: 1.6-6.8 for ≥3 vs 0), the number of times a term related to rotator cuff lesions occurred in radiology reports (OR = 2.2; 95% CI: 1.2-4.1 for ≥1 vs 0), and the number of times a term related to rotator cuff lesions occurred in physician notes (OR = 4.5; 95% CI: 2.2-9.1 for 1 or 2 times vs 0). This phenotyping algorithm had a specificity of 0.89 (95% CI: 0.79-0.95) for rotator cuff tear, area under the curve (AUC) of 0.842, and diagnostic likelihood ratios (DLRs), DLR+ and DLR- of 5.94 (95% CI: 3.07-11.48) and 0.363 (95% CI: 0.291-0.453). CONCLUSION: Our informatics algorithm enables identification of cohorts of individuals with and without rotator cuff tear from an EMR-based data set with moderate accuracy.

Association of Primary Anesthesia Type with Postoperative Adverse Events After Transcarotid Artery Revascularization.

OBJECTIVES: The literature remains sparse regarding the influence of primary anesthesia type (monitored anesthesia care [MAC] v general anesthesia) on 30-day adverse events after transcarotid artery revascularization (TCAR). The objective of this study was to report the association of primary anesthesia type with 30-day adverse events after TCAR. DESIGN: Retrospective cohort analysis of the American College of Surgeons National Surgical Quality Improvement Program Registry from 2012-2016. SETTING: Multi-institutional. PARTICIPANTS: The final analysis included 625 patients who underwent TCAR. INTERVENTIONS: The primary exposure was anesthesia type, categorized as MAC (defined as regional anesthesia, local anesthesia, or MAC) or general anesthesia. The primary endpoint was 30-day mortality. Secondary 30-day endpoints included pulmonary, renal, and cardiac complications; sepsis; deep venous thrombosis; stroke; blood transfusion; embolism/thrombosis of ipsilateral carotid vessel; and redo surgery. MEASUREMENTS AND MAIN RESULTS: The prevalence of MAC was 73.4%. A 93% decrease was observed in the odds of 30-day mortality (p = 0.003) in patients who received MAC. Mean (standard deviation) hospital stay (2.99 [5.92] d v 4.30 [9.15] d; p = 0.037) and case duration (88.45 [39.48] min v 105.85 [63.77] min; p < 0.001) were shorter among patients who received MAC. The odds of pulmonary complications (odds ratio 0.19, 95% confidence interval 0.05-0.65; p = 0.009) were significantly lower in the MAC group. No other differences in secondary endpoints were found between the anesthesia type cohorts. CONCLUSIONS: The majority of studies on this topic pertain to carotid endarterectomy patients, and this retrospective analysis sheds light on outcomes after TCAR. Overall, the authors urge additional risk stratification and preprocedural optimization to carefully select patients who may undergo MAC.

Metabolic effects of smoking cessation.

Smoking continues to be the leading cause of preventable death in the USA, despite the vast and widely publicized knowledge about the negative health effects of tobacco smoking. Data show that smoking cessation is often accompanied by weight gain and an improvement in insulin sensitivity over time. However, paradoxically, post-cessation-related obesity might contribute to insulin resistance. Furthermore, post-cessation weight gain is reportedly the number one reason why smokers, especially women, fail to initiate smoking cessation or relapse after initiating smoking cessation. In this Review, we discuss the metabolic effects of stopping smoking and highlight future considerations for smoking cessation programs and therapies to be designed with an emphasis on reducing post-cessation weight gain.