Can We Geographically Validate a Natural Language Processing Algorithm for Automated Detection of Incidental Durotomy Across Three Independent Cohorts From Two Continents?

Background Incidental durotomy is an intraoperative complication in spine surgery that can lead to postoperative complications, increased length of stay, and higher healthcare costs. Natural language processing (NLP) is an artificial intelligence method that assists in understanding free-text notes that may be useful in the automated surveillance of adverse events in orthopaedic surgery. A previously developed NLP algorithm is highly accurate in the detection of incidental durotomy on internal validation and external validation in an independent cohort from the same country. External validation in a cohort with linguistic differences is required to assess the transportability of the developed algorithm, referred to geographical validation. Ideally, the performance of a prediction model, the NLP algorithm, is constant across geographic regions to ensure reproducibility and model validity. Question/purpose Can we geographically validate an NLP algorithm for the automated detection of incidental durotomy across three independent cohorts from two continents? Methods Patients 18 years or older undergoing a primary procedure of (thoraco)lumbar spine surgery were included. In Massachusetts, between January 2000 and June 2018, 1000 patients were included from two academic and three community medical centers. In Maryland, between July 2016 and November 2018, 1279 patients were included from one academic center, and in Australia, between January 2010 and December 2019, 944 patients were included from one academic center. The authors retrospectively studied the free-text operative notes of included patients for the primary outcome that was defined as intraoperative durotomy. Incidental durotomy occurred in 9% (93 of 1000), 8% (108 of 1279), and 6% (58 of 944) of the patients, respectively, in the Massachusetts, Maryland, and Australia cohorts. No missing reports were observed. Three datasets (Massachusetts, Australian, and combined Massachusetts and Australian) were divided into training and holdout test sets in an 80:20 ratio. An extreme gradient boosting (an efficient and flexible tree-based algorithm) NLP algorithm was individually trained on each training set, and the performance of the three NLP algorithms (respectively American, Australian, and combined) was assessed by discrimination via area under the receiver operating characteristic curves (AUC-ROC; this measures the model's ability to distinguish patients who obtained the outcomes from those who did not), calibration metrics (which plot the predicted and the observed probabilities) and Brier score (a composite of discrimination and calibration). In addition, the sensitivity (true positives, recall), specificity (true negatives), positive predictive value (also known as precision), negative predictive value, Fl-score (composite of precision and recall), positive likelihood ratio, and negative likelihood ratio were calculated. Results The combined NLP algorithm (the combined Massachusetts and Australian data) achieved excellent performance on independent testing data from Australia (AUC-ROC 0.97 [95% confidence interval 0.87 to 0.99]), Massachusetts (AUC-ROC 0.99 [95% CI 0.80 to 0.99]) and Maryland (AUC-ROC 0.95 [95% CI 0.93 to 0.97]). The NLP developed based on the Massachusetts cohort had excellent performance in the Maryland cohort (AUC-ROC 0.97 [95% CI 0.95 to 0.99]) but worse performance in the Australian cohort (AUC-ROC 0.74 [95% CI 0.70 to 0.77]). Conclusion We demonstrated the clinical utility and reproducibility of an NLP algorithm with combined datasets retaining excellent performance in individual countries relative to algorithms developed in the same country alone for detection of incidental durotomy. Further multi-institutional, international collaborations can facilitate the creation of universal NLP algorithms that improve the quality and safety of orthopaedic surgery globally. The combined NLP algorithm has been incorporated into a freely accessible web application that can be found at https://sorg-apps.shinyapps.io/nlp_incidental_durotomy/. Clinicians and researchers can use the tool to help incorporate the model in evaluating spine registries or quality and safety departments to automate detection of incidental durotomy and optimize prevention efforts

Research productivity during orthopedic surgery residency correlates with pre‑planned and protected research time: a survey of German‑speaking countries

Purpose The purpose of this study was to identify modifiable factors associated with research activity among residents working in orthopedic surgery and traumatology. Methods Residents at 796 university-affiliated hospitals in Austria, Germany, and Switzerland were invited to participate. The online survey consisted of questions that ascertained 13 modifiable and 17 non-modifiable factors associated with the residents’ current research activities. Responses of 129 residents were analyzed. Univariate linear regression was used to determine the association of individual factors with the current research activity (hours per week). The impact of significant non-modifiable factors (with unadjusted p values < 0.05) was controlled for using multivariate linear regression. Results The univariate analysis demonstrated six non-modifiable factors that were significantly associated with the current research activity: a University hospital setting (p < 0.001), an A-level hospital setting (p = 0.024), Swiss residents (p = 0.0012), the completion of a dedicated research year (p = 0.007), female gender (p = 0.016), and the department’s size (p = 0.048). Multivariate regression demonstrated that the number of protected research days per year (p < 0.029) and the percentage of protected days, that were known 1 week before (p < 0.001) or the day before (p < 0.001), were significantly associated with a higher research activity. Conclusions As hypothesized, more frequent and predictable protected research days were associated with higher research activity among residents in orthopedic surgery and traumatology. Level of evidence III

Inpatient Opioid Use Varies by Construct Length Among Laminoplasty Versus Laminectomy and Fusion Patients

BACKGROUND: Laminoplasty (LP) and laminectomy and fusion (LF) are utilized to achieve decompression in patients with symptomatic degenerative cervical myelopathy (DCM). Comparative analyses aimed at determining outcomes and clarifying indications between these procedures represent an area of active research. Accordingly, we sought to compare inpatient opioid use between LP and LF patients and to determine if opioid use correlated with length of stay. METHODS: Sociodemographic information, surgical and hospitalization data, and medication administration records were abstracted for patients \u3e18 years of age who underwent LP or LF for DCM in the Mass General Brigham (MGB) health system between 2017 and 2019. Specifically, morphine milligram equivalents (MME) of oral and parenteral pain medication given after arrival in the recovery area until discharge from the hospital were collected. Categorical variables were analyzed using chi-squared analysis or Fisher exact test when appropriate. Continuous variables were compared using Independent samples RESULTS: One hundred eight patients underwent LF, while 138 patients underwent LP. Total inpatient opioid use was significantly higher in the LF group (312 vs. 260 MME, p=.03); this difference was primarily driven by higher postoperative day 0 pain medication requirements. Furthermore, more LF patients required high dose (\u3e80 MME/day) regimens. While length of stay was significantly different between groups, with LF patients staying approximately 1 additional day, postoperative day 0 MME was not a significant predictor of this difference. When operative levels including C2, T1, and T2 were excluded, the differences in total opioid use and average length of stay lost significance. CONCLUSIONS: Inpatient opioid use and length of stay were significantly greater in LF patients compared to LP patients; however, when constructs including C2, T1, T2 were excluded from analysis, these differences lost significance. Such findings highlight the impact of operative extent between these procedures. Future studies incorporating patient reported outcomes and evaluating long-term pain needs will provide a more complete understanding of postoperative outcomes between these 2 procedures

Supplemental Material - Neurological Outcomes and the Need for Retreatments Among Multiple Myeloma Patients With High-Grade Spinal Cord Compression: Radiotherapy vs Surgery

Supplemental Material for Neurological Outcomes and the Need for Retreatments Among Multiple Myeloma Patients With High-Grade Spinal Cord Compression: Radiotherapy vs Surgery by Hester Zijlstra, MD, Alexander M. Crawford, MD, Brendan M. Striano, MD, Robert-Jan Pierik, BSc, Daniel G. Tobert, MD, Nienke Wolterbeek, PhD, Diyar Delawi, MD, PhD, Wim E. Terpstra, MD, PhD, Diederik H. R. Kempen, MD, PhD, Jorrit-Jan Verlaan, MD, PhD, and Joseph H. Schwab, MD, MS in Global Spine Journal</p