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during training. 57% and 49% of respondents reported "never" performing micropauses or stretching between surgeries, respectively. 56.9% of respondents take NSAIDs for work related pain.CONCLUSIONS: Most survey responders report an increase in neck and lower back pain after performing surgery. Many did not have formalized ergonomics training and do not employ preventative strategies to optimize ergonomics. This survey study identifies a gap in urology training and a potential area of focus to promote career wellness and longevity.

Osteogenesis imperfecta (OI) is a rare disorder of bone fragility caused by mutations in the COL1A1/2 genes, which encode type I procollagen. It commonly manifests with bone fractures, joint dislocations, and easy bruising. OI patients presenting for surgery may pose multiple challenges to the anesthesiologist such as management of a potentially difficult airway and heightened positional fracture risks. We present a case detailing the spinal anesthetic management of a 28-year-old woman with type I OI requiring cesarean delivery for a 32-week intrauterine pregnancy with fetal cardiac anomalies.

We present a unique case of a patient coming to our internal medicine clinic with intermittent diffuse lymphadenopathy and non-specific symptoms for the past eight years. Initially, the patient was thought to have carcinoma of unknown primary origin, given the abnormalities seen in her imaging. The diagnosis of sarcoidosis was also dismissed, given that the patient had not responded to steroids with negative laboratory support. The patient was referred to several specialists, and only after a pulmonary biopsy was a non-caseating granuloma revealed after multiple prior failed biopsies. The patient was placed on infusion therapy and responded positively. This case demonstrates a challenging diagnosis and treatment which emphasizes the importance of considering alternative treatments if the initial therapy fails.

Background:The Accreditation Council for Graduate Medical Education (ACGME) case log system for anesthesiology resident training relies on subjective categorization of surgical procedures and lacks clear guidelines for assigning credit roles. Therefore, resident reporting practices likely vary within and between institutions. Our primary aim was to develop a systematic process for generating automated case logs using data elements extracted from the electronic health care record. We hypothesized that automated case log reporting would improve accuracy and reduce reporting variability. Methods:We developed a systematic approach for automating anesthesiology resident case logs from the electronic health care record using a discrete classification system for assigning credit roles and Anesthesia Current Procedure Terminology codes to categorize cases. The median number of cases performed was compared between the automated case log and resident-reported ACGME case log.Results: Case log elements were identified in the electronic health care record and automatically extracted. A total of 42 individual case logs were generated from the extracted data and visualized in an external dashboard. Automated reporting captured a median of 1226.5 (interquartile range: 1097-1366) total anesthetic cases in contrast to 1134.5 (interquartile range: 899-1208) reported to ACGME by residents (P = .0014). Automation also decreased the case count interquartile range and the distribution approached normality, suggesting that automation reduces reporting variability.Conclusions: Automated case log reporting uniformly captures the resident training experience and reduces reporting variability. We hope this work provides a foundation for aggregating graduate medical education data from the electronic health care record and advances adoption of case log automation.