Applying natural language processing to patient messages to identify depression concerns in cancer patients.

OBJECTIVE: This study aims to explore and develop tools for early identification of depression concerns among cancer patients by leveraging the novel data source of messages sent through a secure patient portal. MATERIALS AND METHODS: We developed classifiers based on logistic regression (LR), support vector machines (SVMs), and 2 Bidirectional Encoder Representations from Transformers (BERT) models (original and Reddit-pretrained) on 6600 patient messages from a cancer center (2009-2022), annotated by a panel of healthcare professionals. Performance was compared using AUROC scores, and model fairness and explainability were examined. We also examined correlations between model predictions and depression diagnosis and treatment. RESULTS: BERT and RedditBERT attained AUROC scores of 0.88 and 0.86, respectively, compared to 0.79 for LR and 0.83 for SVM. BERT showed bigger differences in performance across sex, race, and ethnicity than RedditBERT. Patients who sent messages classified as concerning had a higher chance of receiving a depression diagnosis, a prescription for antidepressants, or a referral to the psycho-oncologist. Explanations from BERT and RedditBERT differed, with no clear preference from annotators. DISCUSSION: We show the potential of BERT and RedditBERT in identifying depression concerns in messages from cancer patients. Performance disparities across demographic groups highlight the need for careful consideration of potential biases. Further research is needed to address biases, evaluate real-world impacts, and ensure responsible integration into clinical settings. CONCLUSION: This work represents a significant methodological advancement in the early identification of depression concerns among cancer patients. Our work contributes to a route to reduce clinical burden while enhancing overall patient care, leveraging BERT-based models.

Statistical Methods to Examine Racial and Ethnic Disparities in the Surgical Literature: A Review and Recommendations for Improvement.

OBJECTIVE: We characterized the quality of statistical methods for studies of racial and ethnic disparities in the surgical-relevant literature during 2021-2022. BACKGROUND: Hundreds of scientific papers are published each year describing racial and ethnic disparities in surgical access, quality, and outcomes. The content and design quality of this literature has never been systematically reviewed. METHODS: We searched for 2021-2022 studies focused on describing racial and/or ethnic disparities in surgical or perioperative access, process quality, or outcomes. Identified studies were characterized in terms of three methodological criteria: 1) adjustment for variables related to both race/ethnicity and outcomes, including social determinants of health (SDOH); 2) accounting for clustering of patients within hospitals or other subunits ("providers") and; 3) distinguishing within- and between-provider effects. RESULTS: We identified 224 papers describing racial and/or ethnic differences. Of the 38 single institution studies, 24 (63.2%) adjusted for at least one SDOH variable. Of the 186 multisite studies, 113 (60.8%) adjusted for at least one SDOH variable, and 43 (23.1%) accounted for clustering of patients within providers using appropriate statistical methods. Only 10 (5.4%) of multi-institution studies made efforts to examine how much of overall disparities were driven by within versus between provider effects. CONCLUSIONS: Most recently published papers on racial and ethnic disparities in the surgical literature do not meet these important statistical design criteria and therefore may risk inaccuracy in the estimation of group differences in surgical access, quality, and outcomes. The most potent leverage points for these improvements are changes to journal publication guidelines and policies.

Experience with the utilization of new-generation shared-control robotic system for spinal instrumentation.

BACKGROUND: Robotic assistance in spine surgery is emerging as an accurate, effective and enabling technology utilized in the treatment of patients with surgical spinal pathology. The safety and reproducibility of robotic assistance in the placement of pedicle screw instrumentation is still being investigated. The objective of this study was to present our experience of instrumented spinal fusion utilizing an intraoperative robotic guidance system. METHODS: We retrospectively reviewed all cases of spinal instrumentation of the thoracic and lumbo-sacral spine using the Mazor X robotic system (Medtronic Inc, Minneapolis, MN, USA), performed at our institution by one surgeon between July 2017 and June 2020. Wilcoxon Rank test was used to compare time taken to place each screw during the first 20 cases and the cases thereafter. RESULTS: A total of 28 patients were included. A total of 159 screws were placed using the Mazor X robotic system. The overall mean time for screw placement was 7.8±2.3 minutes and there was a significant reduction in the mean time for screw placement after the 20th case or 120 screws (8.70 vs. 5.42 min, P=0.008). No postoperative neurologic deficit or new radiculopathy was noted to occur secondary to hardware placement. No revision surgery was required for replacement or removal of a mispositioned screw. CONCLUSIONS: From this single-center, single-surgeon series we conclude that robot-assisted spine surgery can be safely and efficiently integrated into the operating room workflow, which improves after a learning curve of approximately 20 operative interventions. We found robot-assisted spinal instrumentation to be reliable, safe, effective and highly precise.

Machine Learning in Neurosurgery: Toward Complex Inputs, Actionable Predictions, and Generalizable Translations.

Machine learning can predict neurosurgical diagnosis and outcomes, power imaging analysis, and perform robotic navigation and tumor labeling. State-of-the-art models can reconstruct and generate images, predict surgical events from video, and assist in intraoperative decision-making. In this review, we will detail the neurosurgical applications of machine learning, ranging from simple to advanced models, and their potential to transform patient care. As machine learning techniques, outputs, and methods become increasingly complex, their performance is often more impactful yet increasingly difficult to evaluate. We aim to introduce these advancements to the neurosurgical audience while suggesting major potential roadblocks to their safe and effective translation. Unlike the previous generation of machine learning in neurosurgery, the safe translation of recent advancements will be contingent on neurosurgeons' involvement in model development and validation.

Type II odontoid fractures in the elderly presenting to the emergency department: an assessment of factors affecting in-hospital mortality and discharge to skilled nursing facilities.

BACKGROUND CONTEXT: Type II odontoid fractures (OF) are among the most common cervical spine injuries in the geriatric population. However, there is a paucity of literature regarding their epidemiology. Additionally, the optimal management of these injuries remains controversial, and no study has evaluated the short-term outcomes of geriatric patients presenting to emergency departments (ED). PURPOSE: This study aims to document the epidemiology of geriatric patients presenting to EDs with type II OFs and determine whether surgical management was associated with early adverse outcomes such as in-hospital mortality and discharge to skilled nursing facilities (SNF). STUDY DESIGN: This is a retrospective cohort study. PATIENT SAMPLE: Data was used from the 2016-2020 Nationwide Emergency Department Sample. Patient encounters corresponding to type II OFs were identified. Patients younger than 65 at the time of presentation to the ED and those with concomitant spinal pathology were excluded. OUTCOME MEASURES: The association between the surgical management of geriatric type II OFs and outcomes such as in-hospital mortality and discharge to SNFs. METHODS: Patient, fracture, and surgical management characteristics were recorded. A propensity score matched cohort was constructed to reduce differences in age, comorbidities, and injury severity between patients undergoing operative and nonoperative management. Additionally, to develop a positive control for the analysis of geriatric patients with type II OFs and no other concomitant spinal pathology, a cohort of patients that had been excluded due to the presence of a concomitant spinal cord injury (SCI) was also constructed. Multivariate regressions were then performed on both the matched and unmatched cohorts to ascertain the associations between surgical treatment and in-hospital mortality, inpatient length of stay, encounter charges, and discharge to SNFs. RESULTS: A total of 11,325 encounters were included. The mean total charge per encounter was $60,221. 634 (5.6%) patients passed away during their encounters. In total, 1,005 (8.9%) patients were managed surgically. Surgical management of type II OFs was associated with a 316% increase in visit charge (95% CI: 291%-341%, p<.001), increased inpatient length of stay (IRR: 2.87, 95% CI: 2.62-3.12, p<.001), and increased likelihood of discharge to SNFs (OR=2.62, 95% CI: 2.26-3.05, p<.001), but decreased in-hospital mortality (OR=0.32, CI: 0.21-0.45, p<.001). The propensity score matched cohort consisted of 2,010 patients, matching each of the 1,005 that underwent surgery to 1,005 that did not. These cohorts were well balanced across age (78.24 vs 77.91 years), Elixhauser Comorbidity Index (3.68 vs 3.71), and Injury Severity Score (30.15 vs 28.93). This matching did not meaningfully alter the associations determined between surgical management and in-hospital mortality (OR=0.34, CI=0.21-0.55, p<.001) or SNF discharge (OR=2.59, CI=2.13-3.16, p<.001). Lastly, the positive control cohort of patients with concurrent SCI had higher rates of SNF discharge (50.0% vs 42.6%, p<.001), surgical management (32.3% vs 9.7%, p<.001), and in-hospital mortality (28.9% vs 5.6%, p<.001). CONCLUSIONS: This study lends insight into the epidemiology of geriatric type II OFs and quantifies risk factors influencing adverse outcomes. Patient informed consent should include a discussion of the protective association between definitive surgical management and in-hospital mortality against potential operative morbidity, increased lengths of hospital stay, and increased likelihood of discharge to SNFs. This information may impact patient treatment selection and decision making.

Accuracy of predicted postoperative segmental lumbar lordosis in spinal fusion using an intraoperative robotic planning and guidance system.

BACKGROUND: Restoring lumbar lordosis is one of the main goals in lumbar spinal fusion surgery. The Mazor X-AlignTM software allows for the prediction of postoperative segmental lumbar lordosis based on preoperative imaging. There is limited data on the accuracy of this preoperative prediction, especially in patients undergoing short segment lumbar fusion. The objective of our study was to determine the accuracy of predicted postoperative segmental lumbar lordosis using the Mazor X-AlignTM software in patients requiring short segmental fusion. METHODS: Retrospective analysis of adult patients undergoing pedicle screw spinal instrumentation of not more than four levels using the Mazor XTM Robot (Medtronic Inc., Minneapolis, MN, USA) between July 2017 to June 2020. The robotic guidance software, Mazor X-AlignTM (Medtronic Inc., Minneapolis, MN, USA) was used to calculate the predicted segmental lumbar lordosis based on preoperative CT-imaging and the plan was executed under intraoperative robotic guidance. Predicted segmental lumbar lordosis was compared to achieved segmental lumbar lordosis on 1-month postoperative x-rays using the Cobb angle methodology. RESULTS: A total of 15 patients (46.6% female) with a mean age of 61.5±10.9 years were included. All patients underwent posterior lumbo-sacral spinal fusion with the Mazor XTM robotic system with 11 patients (73.3%) undergoing anterior column reconstruction prior to posterior fixation. Instrumentation was performed across a mean of 2.6 levels per case. Preoperative, the mean segmental lumbar lordosis was 30.2±13.6 degrees. The mean planned segmental lumbar lordosis was 35.5±17.0 degrees while the mean achieved segmental lumbar lordosis was 35.8±16.7 degrees. There was no significant mean difference between the planned and achieved segmental lumbar lordosis (P=0.334). CONCLUSIONS: The Mazor XTM intraoperative robotic planning and guidance is accurate in predicting postoperative segmental lumbar lordosis after short segmental fusion. Our findings may assure surgical decision making and planning.

Calmodulin kinase II inhibition shortens action potential duration by upregulation of K+ currents.

The multifunctional Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) is activated by elevated intracellular Ca(2+) (Ca(2+)(i)), and mice with chronic myocardial CaMKII inhibition (Inh) resulting from transgenic expression of a CaMKII inhibitory peptide (AC3-I) unexpectedly showed action potential duration (APD) shortening. Inh mice exhibit increased L-type Ca(2+) current (I(Ca)), because of upregulation of protein kinase A (PKA) activity, and decreased CaMKII-dependent phosphorylation of phospholamban (PLN). We hypothesized that CaMKII is a molecular signal linking Ca(2+)(i) to repolarization. Whole cell voltage-clamp recordings revealed that the fast transient outward current (I(to,f)) and the inward rectifier current (I(K1)) were selectively upregulated in Inh, compared with wild-type (WT) and transgenic control, mice. Breeding Inh mice with mice lacking PLN returned I(to,f) and I(K1) to control levels and equalized the APD and QT intervals in Inh mice to control and WT levels. Dialysis of AC3-I into WT cells did not result in increased I(to,f) or I(K1), suggesting that enhanced cardiac repolarization in Inh mice is an adaptive response to chronic CaMKII inhibition rather than an acute effect of reduced CaMKII activity. Increasing PKA activity, by cell dialysis with cAMP, or inhibition of PKA did not affect I(K1) in WT cells. Dialysis of WT cells with cAMP also reduced I(to,f), suggesting that PKA upregulation does not increase repolarizing K(+) currents in Inh mice. These findings provide novel in vivo and cellular evidence that CaMKII links Ca(2+)(i) to cardiac repolarization and suggest that PLN may be a critical CaMKII target for feedback regulation of APD in ventricular myocytes.