Citations

AbstractBackgroundPrevious wide local excision prior to sentinel lymph node biopsy (SLNB) may have the potential to disrupt lymphatic channels, thus incorrectly identifying the sentinel node. The purpose of this study was to investigate: (1) regional recurrence rates of prior wide local excision compared to other biopsy techniques and (2) survival outcomes in patients with melanoma of the head and neck.MethodsBetween the years 2000 and 2016, 391 cases were reviewed with a median follow‐up time of 30 months in a large tertiary care center. Biopsy practices included shave, punch, wide local excision, and narrow margin excisional/Mohs, and associations with time to local or regional relapse and death from melanoma were evaluated. Main outcomes included identification of sentinel lymph nodes, overall survival, and melanoma‐specific survival.ResultsOf the 391 patients, biopsy patterns were as follows: 77 (19%) unknown biopsy, 30 (8%) prior wide local excision (WLE), 105 (27%) narrow margin excisional biopsy, 69 (18%) punch biopsy, and 110 (28%) shave biopsy. SLNB was successfully identified in all 30 patients whom had a prior WLE. There were 50 regional recurrences in the neck and 27 local recurrences with the median (IQR) at 1.2 years and 1.0 years, respectively. Multivariable associations of type of prior biopsy, depth of invasion, and nodal status with time to regional recurrence, local recurrence, overall survival, and melanoma‐specific survival were not significantly different.ConclusionsSentinel lymph node biopsy for melanoma of the head and neck can be successfully performed in patients after previous wide local excision.

BackgroundOlfactory nerve fibers are at risk of injury during transnasal endoscopic skull‐base approaches. Olfactory outcomes for various techniques have not been thoroughly investigated. This study aims to report long‐term olfactory outcomes when a cold knife upper septal limb incision technique is used compared to monopolar cautery.MethodsA prospective cohort study was performed at a tertiary referral center. Adult patients undergoing endoscopic approaches with septal incisions were randomized to cold knife or monopolar cautery groups. Patient demographics, clinical history, surgical data, and outcomes were collected. Preoperative, 3‐month, and 12‐month postoperative scores on the University of Pennsylvania Smell Inventory Test (UPSIT) and 22‐item Sino‐Nasal Outcome Test (SNOT‐22) were measured. Fisher's exact tests were performed for categorical variables and t tests were performed for continuous variables.ResultsTwenty‐two (22) patients (10 cold knife, 12 cautery) were enrolled between March 2016 and August 2017. The average age ± standard deviation was 50.2 ± 14.0 years (p = 0.59), 54% (p = 0.69) were female, and the primary pathology was pituitary adenoma (73%, p = 1.00). Preoperative, 3‐month, and 12‐month postoperative UPSIT scores were similar between the cold knife and cautery groups (32.8 vs 32.4, p = 0.80; 33.1 vs 33.0, p = 0.96; 33.6 vs 33.3, p = 0.84). On the “sense of smell/taste” question of the SNOT‐22, there was also no difference at all time points (p > 0.22).ConclusionThere was no significant change in patient UPSIT scores 1 year after transnasal skull‐base approaches, and no short‐term or long‐term differences between cold knife and cautery upper septal limb incision techniques. Our study supports an individualized approach based on surgeon preference.

Background There is little data regarding postoperative outcomes of patients with obstructive sleep apnea (OSA) undergoing skull base surgery. The purpose of this study is to determine an association between risk factors and proximity of cerebrospinal fluid (CSF) leak to surgery in patients with OSA undergoing endoscopic skull base surgery. Methods A retrospective review of neurosurgical inpatients, with and without OSA, at a tertiary care institution from 2002 to 2015 that experienced a postoperative CSF leak after undergoing endoscopic skull base surgery. Results Forty patients met inclusion criteria, 12 (30%) with OSA. OSA patients had significantly higher body mass index (BMI; median 39.4 vs. 31.7, p < 0.01) and were more likely to have diabetes (41.7 vs. 10.7%, p = 0.04) than non-OSA patients; otherwise there were no significant differences in clinical comorbidities. No patients restarted positive pressure ventilation (PPV) in the inpatient setting. The type of repair was not a significant predictor of the time from surgery to leak. Patients with OSA experienced postoperative CSF leak 49% sooner than non-OSA patients (Hazard Ratio 1.49, median 2 vs. 6 days, log-rank p = 0.20). Conclusion Patients with OSA trended toward leaking earlier than those without OSA, and no OSA patients repaired with a nasoseptal flap (NSF) had a leak after postoperative day 5. Due to a small sample size this trend did not reach significance. Future studies will help to determine the appropriate timing for restarting PPV in this high risk population. This is important given PPV's significant benefit to the patient's overall health and its ability to lower intracranial pressure.

Abstract Electronic health record (EHR) algorithms for defining patient cohorts are commonly shared as free-text descriptions that require human intervention both to interpret and implement. We developed the Phenotype Execution and Modeling Architecture (PhEMA, http://projectphema.org) to author and execute standardized computable phenotype algorithms. With PhEMA, we converted an algorithm for benign prostatic hyperplasia, developed for the electronic Medical Records and Genomics network (eMERGE), into a standards-based computable format. Eight sites (7 within eMERGE) received the computable algorithm, and 6 successfully executed it against local data warehouses and/or i2b2 instances. Blinded random chart review of cases selected by the computable algorithm shows PPV ≥90%, and 3 out of 5 sites had &gt;90% overlap of selected cases when comparing the computable algorithm to their original eMERGE implementation. This case study demonstrates potential use of PhEMA computable representations to automate phenotyping across different EHR systems, but also highlights some ongoing challenges.