Extended postoperative venous thromboembolism prophylaxis after bariatric surgery: a comparison of existing risk-stratification tools and 5-year MBSAQIP analysis.

Background: Venous thromboembolism (VTE) is a leading cause of 30-day mortality after metabolic and bariatric surgery (MBS). Multiple predictive tools exist for VTE risk assessment and extended VTE chemoprophylaxis determination.

Objective: To review existing risk-stratification tools and compare their predictive abilities.

Ambiguous and Incomplete: Natural Language Processing Reveals Problematic Reporting Styles in Thyroid Ultrasound Reports.

Objective: Natural language processing (NLP) systems convert unstructured text into analyzable data. Here, we describe the performance measures of NLP to capture granular details on nodules from thyroid ultrasound (US) reports and reveal critical issues with reporting language.

Methods: We iteratively developed NLP tools using clinical Text Analysis and Knowledge Extraction System (cTAKES) and thyroid US reports from 2007 to 2013.

Thyroid Ultrasound Reports: Will the Thyroid Imaging, Reporting, and Data System Improve Natural Language Processing Capture of Critical Thyroid Nodule Features?

Background: Critical thyroid nodule features are contained in unstructured ultrasound (US) reports. The Thyroid Imaging, Reporting, and Data System (TI-RADS) uses five key features to risk stratify nodules and recommend appropriate intervention. This study aims to analyze the quality of US reporting and the potential benefit of Natural Language Processing (NLP) systems in efficiently capturing TI-RADS features from text reports.

Patterns of opioid use in dialysis access procedures.

Background: Overprescription of opioids after surgical procedures is recognized as an important contributor to opioid misuse. Dialysis access procedures are commonly performed outpatient operations with few data or guidelines to inform prescription pain management practices. We sought to characterize opioid pain medication use after dialysis access surgery to promote a conservative approach to postoperative opioid prescriptions.

Identifying Predictors of Prolonged Levothyroxine Dose Adjustment After Thyroidectomy.

Background: Levothyroxine (LT4) is one of the most prescribed drugs in the United States; however, many patients started on LT4 after thyroidectomy suffer from symptoms of hyper- or hypo-thyroidism before achieving euthyroidism. This study aims to describe the time required for dose adjustment before achieving euthyroidism and identify predictors of prolonged dose adjustment (PDA+) after thyroidectomy.

Methods: This is a single institution retrospective cohort study of patients who achieved euthyroidism with LT4 therapy between 2008 and 2017 after total or completion thyroidectomy for benign disease.

The optimal dosing scheme for levothyroxine after thyroidectomy: A comprehensive comparison and evaluation.

Background: Patients often struggle to attain euthyroidism after thyroidectomy, and multiple dosing schemes have been proposed to supplant the standard weight-based approach for initial levothyroxine dosing after thyroidectomy. The objectives of this study were to review the literature for existing levothyroxine dosing schemes and compare estimation accuracies with novel schemes developed with machine learning.

Methods: This study retrospectively analyzed 598 patients who attained euthyroidism after total or completion thyroidectomy for benign disease.

Bariatric surgery barriers: a review using Andersen's Model of Health Services Use.

Severe obesity affects nearly 20 million adults in the United States and is associated with significant morbidity and mortality. Bariatric surgery is the most effective treatment for weight loss and resolution of obesity-related co-morbidities. Of adults with severe obesity,<1% undergo bariatric surgery annually.

Machine learning to identify multigland disease in primary hyperparathyroidism.

Background: 20%-25% of patients with primary hyperparathyroidism will have multigland disease (MGD). Preoperatative imaging can be inaccurate or unnecessary in MGD. Identification of MGD could direct the need for imaging and inform operative approach.