Artificial intelligence model for automated surgical instrument detection and counting: an experimental proof-of-concept study.

BACKGROUND: Retained surgical items (RSI) are preventable events that pose a significant risk to patient safety. Current strategies for preventing RSIs rely heavily on manual instrument counting methods, which are prone to human error. This study evaluates the feasibility and performance of a deep learning-based computer vision model for automated surgical tool detection and counting. METHODS: A novel dataset of 1,004 images containing 13,213 surgical tools across 11 categories was developed. The dataset was split into training, validation, and test sets at a 60:20:20 ratio. An artificial intelligence (AI) model was trained on the dataset, and the model's performance was evaluated using standard object detection metrics, including precision and recall. To simulate a real-world surgical setting, model performance was also evaluated in a dynamic surgical video of instruments being moved in real-time. RESULTS: The model demonstrated high precision (98.5%) and recall (99.9%) in distinguishing surgical tools from the background. It also exhibited excellent performance in differentiating between various surgical tools, with precision ranging from 94.0 to 100% and recall ranging from 97.1 to 100% across 11 tool categories. The model maintained strong performance on a subset of test images containing overlapping tools (precision range: 89.6-100%, and recall range 97.2-98.2%). In a real-time surgical video analysis, the model maintained a correct surgical tool count in all non-transition frames, with a median inference speed of 40.4 frames per second (interquartile range: 4.9). CONCLUSION: This study demonstrates that using a deep learning-based computer vision model for automated surgical tool detection and counting is feasible. The model's high precision and real-time inference capabilities highlight its potential to serve as an AI safeguard to potentially improve patient safety and reduce manual burden on surgical staff. Further validation in clinical settings is warranted.

Testicular Cancer and Paraneoplastic Encephalitis: A Review of the Current Literature.

INTRODUCTION: Paraneoplastic encephalitis (PE) represents a rare but significant complication in patients with testicular cancer (TC). Given the paucity of comprehensive literature on this topic, our review seeks to consolidate current knowledge and provide evidence-based recommendations for the diagnosis, prognosis, and management of PE in the context of TC. MATERIALS AND METHODS: In adherence to PRISMA guidelines, a systematic literature review was conducted from 1950 to April 2024 using PubMed. The search focused on articles where TC was identified as the primary etiology of PE. The Mixed Methods Appraisal Tool and the Oxford Centre for Evidence-Based Medicine's levels of evidence tool were employed for assessing study quality, and a thematic analysis was conducted to identify trends and patterns. RESULTS: Out of 91 articles identified, 29 met the inclusion criteria, encompassing 5 retrospective chart reviews, 3 case series, and 22 case reports. Findings indicate that PE symptoms can manifest at any stage of TC-before tumor detection, during treatment, or even years posttreatment. A notable observation was the frequent oversight of microscopic testicular tumors in ultrasound imaging, leading to diagnostic delays. The outcomes of PE in the context of TC were diverse, reflecting the heterogeneity of the studies included. CONCLUSION: PE, although rare, is a critical consideration in patients with TC presenting with neuropsychiatric symptoms. Early recognition and appropriate diagnostic workup, including consideration for microscopic neoplasms, are essential for timely intervention and improved patient outcomes.

Automated surgical step recognition in transurethral bladder tumor resection using artificial intelligence: transfer learning across surgical modalities.

Objective: Automated surgical step recognition (SSR) using AI has been a catalyst in the "digitization" of surgery. However, progress has been limited to laparoscopy, with relatively few SSR tools in endoscopic surgery. This study aimed to create a SSR model for transurethral resection of bladder tumors (TURBT), leveraging a novel application of transfer learning to reduce video dataset requirements. Materials and methods: Retrospective surgical videos of TURBT were manually annotated with the following steps of surgery: primary endoscopic evaluation, resection of bladder tumor, and surface coagulation. Manually annotated videos were then utilized to train a novel AI computer vision algorithm to perform automated video annotation of TURBT surgical video, utilizing a transfer-learning technique to pre-train on laparoscopic procedures. Accuracy of AI SSR was determined by comparison to human annotations as the reference standard. Results: A total of 300 full-length TURBT videos (median 23.96 min; IQR 14.13-41.31 min) were manually annotated with sequential steps of surgery. One hundred and seventy-nine videos served as a training dataset for algorithm development, 44 for internal validation, and 77 as a separate test cohort for evaluating algorithm accuracy. Overall accuracy of AI video analysis was 89.6%. Model accuracy was highest for the primary endoscopic evaluation step (98.2%) and lowest for the surface coagulation step (82.7%). Conclusion: We developed a fully automated computer vision algorithm for high-accuracy annotation of TURBT surgical videos. This represents the first application of transfer-learning from laparoscopy-based computer vision models into surgical endoscopy, demonstrating the promise of this approach in adapting to new procedure types.

Frailty and survival among veterans treated with abiraterone or enzalutamide for metastatic castration-resistant prostate cancer.

INTRODUCTION: Abiraterone and enzalutamide are treatments for metastatic castration-resistant prostate cancer (mCRPC). Due to a lack of head-to-head trials, they are prescribed interchangeably. However, the drugs have different pharmacokinetics and thus may have differing efficacy and adverse effects influenced by patient functional status and comorbid diseases. Additionally, mCRPC mainly affects older adults and since the prevalence of frailty increases with age, frailty is an important patient factor to consider in personalizing drug selection. MATERIALS AND METHODS: We conducted a retrospective observational study of US veterans treated with abiraterone or enzalutamide for mCRPC from September 2014 to June 2017. Frailty was assessed using the Veterans Affairs Frailty Index (VA-FI), which utilizes administrative codes to assign a standardized frailty score. Patients were categorized as frail if VA-FI scores were > 0.2. The primary outcome was difference in overall survival (OS) between the two treatment groups. Cox regression modeling and propensity score matching was used to compare between abiraterone and enzalutamide treatments. RESULTS: We identified 5,822 veterans, 57% of whom were initially treated with abiraterone and 43% with enzalutamide. Frail patients (n = 2,314; 39.7%) were older, with a mean age of 76.1 versus 74.9 years in the non-frail group (n = 3,508; 60.3%, p < 0.001) and had shorter OS compared to non-frail patients regardless of treatment group (18.5 vs. 26.6 months, p < 0.001). Among non-frail patients there was no significant difference in OS between abiraterone and enzalutamide treatment (27.7 vs 26.1 months, p = 0.07). However, frail patients treated with enzalutamide versus abiraterone had improved OS (20.7 vs 17.2 months, p < 0.001). In a propensity score matched analysis of frail patients (n = 2,070), enzalutamide was associated with greater median OS (24.1 vs 20.9 months, p < 0.001). In patients with dementia, enzalutamide was associated with longer OS (19.4 vs. 16.6 months, p = 0.003). DISCUSSION: In this study of 5822 US veterans with mCRPC, treatment with enzalutamide was associated with improved OS compared to abiraterone among frail veterans and veterans with dementia, but not among non-frail veterans. Future studies should evaluate interactions between frailty and cancer treatments to optimize selection of therapy among frail adults.

Exploring the link between ACEs and opioid use: A systematic review.

OBJECTIVE: To review the current literature surrounding the relationship between adverse childhood experiences (ACEs) and opioid use disorder (OUD) to guide clinical identification of high-risk individuals and assess treatment implications. DESIGN: A PubMed search was conducted from the year 2000 to 2022 using a series of primary and secondary search terms. A total of 21,524 unique results were screened for relevancy to ACEs and OUDs. After excluding unrelated articles, a total of 48 articles were included in this systematic review. RESULTS: Increased frequency of ACEs was directly related to increased risk of OUD and lower onset age. ACEs were also associated with OUD severity. ACEs linked to OUD included childhood neglect, emotional abuse, physical abuse, and sexual abuse. Additionally, dysfunctional childhood home environment, female gender, and psychiatric/behavioral comorbidities increased the risk of OUD, while resilience was found to be a protective factor. Multiple biochemical markers were associated with both ACEs and OUD. CONCLUSIONS: Children experiencing multiple ACEs should be the target of preventative intervention by medical professionals. Clinicians should include ACEs in their opioid misuse risk assessment. High incidence of co-occurring psychiatric/behavioral disorders provides multiple treatment avenues for patients with OUD. Resilience, along with being therapy target, should be fostered early in the life course. Incorporation of family members may improve opioid abuse treatment outcomes. Future research should focus on interventions interrupting the progression of ACEs to OUD along with proposed biochemical pathways.

Association of Male Hypogonadism With Risk of Hospitalization for COVID-19.

Importance: Male sex is associated with severe COVID-19. It is not known whether the risk of hospitalization differs between men with hypogonadism, men with eugonadism, and those receiving testosterone therapy (TTh). Objective: To compare COVID-19 hospitalization rates for men with hypogonadism who were not receiving TTh, men with eugonadism, and men receiving TTh. Design, Setting, and Participants: This cohort study was conducted in 2 large academic health systems in St Louis, Missouri, among 723 men with a history of COVID-19 who had testosterone concentrations measured between January 1, 2017, and December 31, 2021. Exposures: The primary exposure was gonadal status (hypogonadism, eugonadism, and TTh). Hypogonadism was defined as a total testosterone concentration below the limit of normal provided by the laboratory (which varied from 175 to 300 ng/dL [to convert to nanomoles per liter, multiply by 0.0347]). Main Outcomes and Measures: The primary outcome was rate of hospitalization for COVID-19. Statistical adjustments were made for group differences in age, body mass index, race and ethnicity, immunosuppression, and comorbid conditions. Results: Of the 723 study participants (mean [SD] age, 55 [14] years; mean [SD] body mass index, 33.5 [7.3]), 116 men had hypogonadism, 427 had eugonadism, and 180 were receiving TTh. Men with hypogonadism were more likely than men with eugonadism to be hospitalized with COVID-19 (52 of 116 [45%] vs 53 of 427 [12%]; P < .001). After multivariable adjustment, men with hypogonadism had higher odds than men with eugonadism of being hospitalized (odds ratio, 2.4; 95% CI, 1.4-4.4; P < .003). Men receiving TTh had a similar risk of hospitalization as men with eugonadism (odds ratio, 1.3; 95% CI, 0.7-2.3; P = .35). Men receiving inadequate TTh (defined as subnormal testosterone concentrations while receiving TTh) had higher odds of hospitalization compared with men who had normal testosterone concentrations while receiving TTh (multivariable adjusted odds ratio, 3.5; 95% CI, 1.5-8.6; P = .003). Conclusions and Relevance: This study suggests that men with hypogonadism were more likely to be hospitalized after COVID-19 infection compared with those with eugonadism, independent of other known risk factors. This increased risk was not observed among men receiving adequate TTh. Screening and appropriate therapy for hypogonadism need to be evaluated as a strategy to prevent severe COVID-19 outcomes among men.