Increased Risk of Humeral Fracture With Open Versus Arthroscopic Tenodesis of the Long Head of the Biceps Brachii.

PURPOSE: To determine the risk of postoperative humeral fracture following tenotomy, open tenodesis and arthroscopic tenodesis of the long head of the biceps brachii. METHODS: A retrospective review of deidentified patient data from the Medicare Standard Analytic File using the PearlDiver software was conducted to identify procedures performed between 2005 and 2014. Groups were matched by age, gender, region, and medical comorbidities. RESULTS: We evaluated 157,163 patients who had undergone arthroscopic or open tenodesis or tenotomy of the long head of the biceps brachii over a 10-year period (2005-2014), and we identified 2,196 postoperative humeral fractures (1.4%). Matched subgroup analysis consisting of 44,292 patients demonstrated a statistically significant increase in humeral fracture risk in open (280; 1.26%) compared to arthroscopic tenodesis (232; 1.04%) with a P value of 0.03 and an odds ratio of 1.21. The majority of fractures were sustained by patients 65-74 years of age. CONCLUSION: In this study, an increased risk of postoperative humeral fracture was associated with open tenodesis of the LHB. LEVEL OF EVIDENCE: III, Retrospective Comparative Trial.

Clinical experience across the fetal-fraction spectrum of a non-invasive prenatal screening approach with low test-failure rate.

OBJECTIVE: To describe our clinical experience across the entire range of fetal-fraction (FF) measurements of a non-invasive prenatal screen (NIPS) that uses whole- genome sequencing (WGS). METHODS: We analyzed retrospectively results from 58 105 singleton pregnancies that underwent NIPS on a customized WGS platform during an 8-month period and assessed clinical test performance for trisomy 21, trisomy 18 and trisomy 13. Pregnancy outcomes were sought for all screen-positive patients and for 18% of screen-negative patients. As differences in outcome-collection response rates could artificially impact test-performance calculations, we computed inferred sensitivity, specificity, positive predictive values (PPV) and negative predictive values adjusted for ascertainment bias. RESULTS: The screening test yielded a result for 99.9% (n = 58 048) of patients, meaning that approximately 1 in 1000 patients received a test failure (i.e. test failure rate = 0.1%). Of pregnancies with a test result, 572 (1%) screened positive for one of the common aneuploidies (362 for trisomy 21, 142 for trisomy 18 and 68 for trisomy 13). Informative outcomes were received for 237 (41.4%) patients with a screen-positive result and 3258 (5.7%) of those with a screen-negative result. In the full cohort, inferred sensitivities for trisomy 21, trisomy 18 and trisomy 13 were 99.7%, 96.8% and 94.3%, respectively, and PPVs were 93.1%, 85.2% and 48.4%, respectively. If a FF threshold of 4% had been employed to guard against false negatives, calculated sensitivities for the three aneuploidies would not have changed significantly, yet, importantly, the overall test-failure rate would have increased to 6.6% (n = 3829), impacting 1 in 15 women. CONCLUSIONS: Our clinical experience demonstrates that a customized WGS-based NIPS without a FF threshold achieves high accuracy while maintaining a low test-failure rate of 0.1%. As such, alternative strategies to ensure high accuracy of detection of common aneuploidies in samples with low FF (such as redraw after test failure, redrawing at a later gestational age, risk scoring based on FF) are not necessary for this screening approach. © 2019 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Integration of disease-specific single nucleotide polymorphisms, expression quantitative trait loci and coexpression networks reveal novel candidate genes for type 2 diabetes.

AIMS/HYPOTHESIS: While genome-wide association studies (GWASs) have been successful in identifying novel variants associated with various diseases, it has been much more difficult to determine the biological mechanisms underlying these associations. Expression quantitative trait loci (eQTL) provide another dimension to these data by associating single nucleotide polymorphisms (SNPs) with gene expression. We hypothesised that integrating SNPs known to be associated with type 2 diabetes with eQTLs and coexpression networks would enable the discovery of novel candidate genes for type 2 diabetes. METHODS: We selected 32 SNPs associated with type 2 diabetes in two or more independent GWASs. We used previously described eQTLs mapped from genotype and gene expression data collected from 1,008 morbidly obese patients to find genes with expression associated with these SNPs. We linked these genes to coexpression modules, and ranked the other genes in these modules using an inverse sum score. RESULTS: We found 62 genes with expression associated with type 2 diabetes SNPs. We validated our method by linking highly ranked genes in the coexpression modules back to SNPs through a combined eQTL dataset. We showed that the eQTLs highlighted by this method are significantly enriched for association with type 2 diabetes in data from the Wellcome Trust Case Control Consortium (WTCCC, p = 0.026) and the Gene Environment Association Studies (GENEVA, p = 0.042), validating our approach. Many of the highly ranked genes are also involved in the regulation or metabolism of insulin, glucose or lipids. CONCLUSIONS/INTERPRETATION: We have devised a novel method, involving the integration of datasets of different modalities, to discover novel candidate genes for type 2 diabetes.