The Performance of ChatGPT on the American Society for Surgery of the Hand Self-Assessment Examination.

BACKGROUND: This study aims to compare the performance of ChatGPT-3.5 (GPT-3.5) and ChatGPT-4 (GPT-4) on the American Society for Surgery of the Hand (ASSH) Self-Assessment Examination (SAE) to determine their potential as educational tools. METHODS: This study assessed the proportion of correct answers to text-based questions on the 2021 and 2022 ASSH SAE between untrained ChatGPT versions. Secondary analyses assessed the performance of ChatGPT based on question difficulty and question category. The outcomes of ChatGPT were compared with the performance of actual examinees on the ASSH SAE. RESULTS: A total of 238 questions were included in the analysis. Compared with GPT-3.5, GPT-4 provided significantly more correct answers overall (58.0% versus 68.9%, respectively; P = 0.013), on the 2022 SAE (55.9% versus 72.9%; P = 0.007), and more difficult questions (48.8% versus 63.6%; P = 0.02). In a multivariable logistic regression analysis, correct answers were predicted by GPT-4 (odds ratio [OR], 1.66; P = 0.011), increased question difficulty (OR, 0.59; P = 0.009), Bone and Joint questions (OR, 0.18; P < 0.001), and Soft Tissue questions (OR, 0.30; P = 0.013). Actual examinees scored a mean of 21.6% above GPT-3.5 and 10.7% above GPT-4. The mean percentage of correct answers by actual examinees was significantly higher for correct (versus incorrect) ChatGPT answers. CONCLUSIONS: GPT-4 demonstrated improved performance over GPT-3.5 on the ASSH SAE, especially on more difficult questions. Actual examinees scored higher than both versions of ChatGPT, but the margin was cut in half by GPT-4.

Extensor tendon transfer for fracture-related extensor pollicis longus rupture: Long-term outcome case series.

BACKGROUND: Spontaneous rupture of the extensor pollicis longus (EPL) tendon following both nonoperative and operative treatment of distal radius fractures has been well described. PURPOSE: The purpose of this study was to assess long-term outcomes of extensor indicis proprius to EPL tendon transfers for patients following distal radius fracture and EPL tendon repair. STUDY DESIGN: Retrospective case series focusing on long-term clinical outcomes. METHODS: A retrospective review was conducted for patients who sustained a distal radius fracture and subsequently underwent extensor tendon transfer from 2005-2015 at a private practice center. Outcome measures including index finger (IF) metacarpophalangeal (MCP) and thumb interphalangeal (IP) active range of motion (ROM), digital extension against resistance, subjective complaints, and QuickDASH scores were recorded at final follow-up. RESULTS: Seven patients were included in the study. There were six females and one male subject, mean age of 54 ± 13 years at injury of EPL, and 5/7 involved the left upper extremity. For isolated function, 7/7 (100%) patients had isolated, active IF MCP extension, 6/7 (86%) could extend IF MCP and thumb IP against resistance. Mean IF MCP extension was 1° ± 2°, mean IF MCP flexion was 89° ± 2°, mean thumb IP extension was -5° ± 4°, and mean thumb IP flexion was 67° ± 15°. Mean QuickDASH score was 16 ± 14. CONCLUSIONS: This series shows good long-term functional and patient reported outcomes in patients following extensor indicis proprius to EPL tendon transfers at a single center.

Validation of Temperature Sensors to Monitor Thermoplastic Splint Wear in Hand Surgery Patients.

BACKGROUND: The aim of this study was to validate the use of temperature sensors to accurately measure thermoplastic volar forearm splint wear in a healthy cohort of volunteers using 5- and 15-minute temperature measurement intervals. METHODS: A prospective diagnostic study was performed to evaluate the diagnostic accuracy of temperature sensors in monitoring splint wear in 8 healthy volunteers between December 2022 and June 2023. Temperature sensors were molded into thermoplastic volar forearm splints. Volunteers who were familiar with the study aims were asked to keep an exact log of the time spent wearing the splint ("actual wear time"). Sensors recorded temperatures every 5 or 15 minutes, and separate algorithms were developed to determine the sensor-detected wear time compared with the actual wear time as the gold standard. The algorithms were then externally validated with the total population. RESULTS: The 5-minute and 15-minute algorithms demonstrated excellent sensitivity (99.1% vs 96.6%), specificity (99.9% vs 99.9%), positive (99.4% vs 99.5%) and negative (99.9% vs 99.3%) predictive value, and diagnostic accuracy (99.8% vs 99.3%), respectively. The 5-minute algorithm recorded 99.5% of the total splint hours, whereas the 15-minute algorithm recorded 96.1%. There was no significant difference between the actual time per wear session (5.4 ± 2.7 hours) and the time estimated by the 5-minute algorithm (5.4 ± 2.6 hours; P = .40), but there was a significant difference for the 15-minute algorithm (5.2 ± 2.6 hours; P < .001). CONCLUSION: Temperature sensors can be used to accurately monitor thermoplastic volar forearm splint wear. LEVEL OF EVIDENCE: Diagnostic II.

Role of Preoperative Nerve Conduction Studies for Penetrating Hand Injuries Involving the Median Palmar Cutaneous Nerve.

Penetrating lacerations to the hand are a common cause of nerve injury and can lead to debilitating pain and numbness in the distribution of the nerve affected. Owing to an overlap in the cutaneous innervation from different sensory nerves, clinically identifying the injured nerve can be difficult. We present a novel case of isolated injury to the palmar cutaneous nerve from a penetrating knife injury which was detected using 'comparison waveform' nerve conduction studies. Using this technique, we can isolate injuries to the palmar cutaneous branch of the median nerve (PCBmdn) from the median nerve, dorsal radial sensory nerve, and lateral antebrachial cutaneous nerve. In addition, sensory nerve testing identified conduction block as the mechanism of injury, which resolved after surgery at 8 weeks postoperatively. Preoperative nerve conduction study can discern the level of nerve injury to PCBmdn only, thus eliminating the need for median and radial nerve exploration at the forearm, unnecessary incisions, pain, and scarring. The objective of this case report is to illustrate the value of preoperative comparison waveform nerve conduction study, particularly the PCBmdn, in patients presenting with neurologic deficits who have sustained penetrating lacerations to the hand.

Sex-Dependent Transcriptional Changes in Response to Stress in Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Pilot Project.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, multi-symptom illness characterized by debilitating fatigue and post-exertional malaise (PEM). Numerous studies have reported sex differences at the epidemiological, cellular, and molecular levels between male and female ME/CFS patients. To gain further insight into these sex-dependent changes, we evaluated differential gene expression by RNA-sequencing (RNA-Seq) in 33 ME/CFS patients (20 female, 13 male) and 34 matched healthy controls (20 female and 14 male) before, during, and after an exercise challenge intended to provoke PEM. Our findings revealed that pathways related to immune-cell signaling (including IL-12) and natural killer cell cytotoxicity were activated as a result of exertion in the male ME/CFS cohort, while female ME/CFS patients did not show significant enough changes in gene expression to meet the criteria for the differential expression. Functional analysis during recovery from an exercise challenge showed that male ME/CFS patients had distinct changes in the regulation of specific cytokine signals (including IL-1ß). Meanwhile, female ME/CFS patients had significant alterations in gene networks related to cell stress, response to herpes viruses, and NF-κß signaling. The functional pathways and differentially expressed genes highlighted in this pilot project provide insight into the sex-specific pathophysiology of ME/CFS.

Medical decision support system using weakly-labeled lung CT scans.

Purpose: Determination and development of an effective set of models leveraging Artificial Intelligence techniques to generate a system able to support clinical practitioners working with COVID-19 patients. It involves a pipeline including classification, lung and lesion segmentation, as well as lesion quantification of axial lung CT studies. Approach: A deep neural network architecture based on DenseNet is introduced for the classification of weakly-labeled, variable-sized (and possibly sparse) axial lung CT scans. The models are trained and tested on aggregated, publicly available data sets with over 10 categories. To further assess the models, a data set was collected from multiple medical institutions in Colombia, which includes healthy, COVID-19 and patients with other diseases. It is composed of 1,322 CT studies from a diverse set of CT machines and institutions that make over 550,000 slices. Each CT study was labeled based on a clinical test, and no per-slice annotation took place. This enabled a classification into Normal vs. Abnormal patients, and for those that were considered abnormal, an extra classification step into Abnormal (other diseases) vs. COVID-19. Additionally, the pipeline features a methodology to segment and quantify lesions of COVID-19 patients on the complete CT study, enabling easier localization and progress tracking. Moreover, multiple ablation studies were performed to appropriately assess the elements composing the classification pipeline. Results: The best performing lung CT study classification models achieved 0.83 accuracy, 0.79 sensitivity, 0.87 specificity, 0.82 F1 score and 0.85 precision for the Normal vs. Abnormal task. For the Abnormal vs COVID-19 task, the model obtained 0.86 accuracy, 0.81 sensitivity, 0.91 specificity, 0.84 F1 score and 0.88 precision. The ablation studies showed that using the complete CT study in the pipeline resulted in greater classification performance, restating that relevant COVID-19 patterns cannot be ignored towards the top and bottom of the lung volume. Discussion: The lung CT classification architecture introduced has shown that it can handle weakly-labeled, variable-sized and possibly sparse axial lung studies, reducing the need for expert annotations at a per-slice level. Conclusions: This work presents a working methodology that can guide the development of decision support systems for clinical reasoning in future interventionist or prospective studies.

Development of a BCL-xL and BCL-2 dual degrader with improved anti-leukemic activity.

PROteolysis-TArgeting Chimeras (PROTACs) have emerged as an innovative drug development platform. However, most PROTACs have been generated empirically because many determinants of PROTAC specificity and activity remain elusive. Through computational modelling of the entire NEDD8-VHL Cullin RING E3 ubiquitin ligase (CRLVHL)/PROTAC/BCL-xL/UbcH5B(E2)-Ub/RBX1 complex, we find that this complex can only ubiquitinate the lysines in a defined band region on BCL-xL. Using this approach to guide our development of a series of ABT263-derived and VHL-recruiting PROTACs, we generate a potent BCL-xL and BCL-2 (BCL-xL/2) dual degrader with significantly improved antitumor activity against BCL-xL/2-dependent leukemia cells. Our results provide experimental evidence that the accessibility of lysines on a target protein plays an important role in determining the selectivity and potency of a PROTAC in inducing protein degradation, which may serve as a conceptual framework to guide the future development of PROTACs.