BACKGROUND: There are limited data available regarding the connection between heavy metal exposure and mortality among hypertension patients.
OBJECTIVE: We intend to establish an interpretable machine learning (ML) model with high efficiency and robustness that monitors mortality based on heavy metal exposure among hypertension patients.
METHODS: Our datasets were obtained from the US National Health and Nutrition Examination Survey (NHANES, 2013-2018). We developed 5 ML models for mortality prediction among hypertension patients by heavy metal exposure, and tested them by 10 discrimination characteristics. Further, we chose the optimally performing model after parameter adjustment by genetic algorithm (GA) for prediction. Finally, in order to visualize the model\'s ability to make decisions, we used SHapley Additive exPlanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) algorithm to illustrate the features. The study included 2347 participants in total.
RESULTS: A best-performing eXtreme Gradient Boosting (XGB) with GA for mortality prediction among hypertension patients by 13 heavy metals was selected (AUC 0.959; 95% CI 0.953-0.965; accuracy 96.8%). According to sum of SHAP values, cadmium (0.094), cobalt (2.048), lead (1.12), tungsten (0.129) in urine, and lead (2.026), mercury (1.703) in blood positively influenced the model, while barium (- 0.001), molybdenum (- 2.066), antimony (- 0.398), tin (- 0.498), thallium (- 2.297) in urine, and selenium (- 0.842), manganese (- 1.193) in blood negatively influenced the model.
CONCLUSIONS: Hypertension patients\' mortality associated with heavy metal exposure was predicted by an efficient, robust, and interpretable GA-XGB model with SHAP and LIME. Cadmium, cobalt, lead, tungsten in urine, and mercury in blood are positively correlated with mortality, while barium, molybdenum, antimony, tin, thallium in urine, and lead, selenium, manganese in blood is negatively correlated with mortality.

Endoscopic mucosal resection (EMR) is the recommended technique for colon polypectomy for nonpedunculated lesions that are >20 mm in size not requiring excision. Dual-channel EMR (DC-EMR) uses an endoscope with two working channels to facilitate easier submucosal injection, snare resection, and clip closure of polypectomy defects. There is also promising early literature indicating that this endoscopic modality can reduce the overall learning curve present for single-channel colonoscopy EMR. This chapter will describe the steps and techniques required to perform DC-EMR, potential complications, recommended postprocedure surveillance, and future directions.

UNASSIGNED: Adverse social determinants of health (SDoH) have been associated with cardiometabolic disease; however, disparities in cardiometabolic outcomes are rarely the result of a single risk factor.
UNASSIGNED: This study aimed to identify and characterize SDoH phenotypes based on patient-reported and neighborhood-level data from the institutional electronic medical record and evaluate the prevalence of diabetes, obesity, and other cardiometabolic diseases by phenotype status.
UNASSIGNED: Patient-reported SDoH were collected (January to December 2020) and neighborhood-level social vulnerability, neighborhood socioeconomic status, and rurality were linked via census tract to geocoded patient addresses. Diabetes status was coded in the electronic medical record using International Classification of Diseases codes; obesity was defined using measured BMI ≥30 kg/m2. Latent class analysis was used to identify clusters of SDoH (eg, phenotypes); we then examined differences in the prevalence of cardiometabolic conditions based on phenotype status using prevalence ratios (PRs).
UNASSIGNED: Complete data were available for analysis for 2380 patients (mean age 53, SD 16 years; n=1405, 59% female; n=1198, 50% non-White). Roughly 8% (n=179) reported housing insecurity, 30% (n=710) reported resource needs (food, health care, or utilities), and 49% (n=1158) lived in a high-vulnerability census tract. We identified 3 patient SDoH phenotypes: (1) high social risk, defined largely by self-reported SDoH (n=217, 9%); (2) adverse neighborhood SDoH (n=1353, 56%), defined largely by adverse neighborhood-level measures; and (3) low social risk (n=810, 34%), defined as low individual- and neighborhood-level risks. Patients with an adverse neighborhood SDoH phenotype had higher prevalence of diagnosed type 2 diabetes (PR 1.19, 95% CI 1.06-1.33), hypertension (PR 1.14, 95% CI 1.02-1.27), peripheral vascular disease (PR 1.46, 95% CI 1.09-1.97), and heart failure (PR 1.46, 95% CI 1.20-1.79).
UNASSIGNED: Patients with the adverse neighborhood SDoH phenotype had higher prevalence of poor cardiometabolic conditions compared to phenotypes determined by individual-level characteristics, suggesting that neighborhood environment plays a role, even if individual measures of socioeconomic status are not suboptimal.

BACKGROUND: Endoscopic resection is currently the treatment of choice for laterally spreading tumors (LSTs). Endoscopic sub-mucosal dissection (ESD) can achieve higher enbloc resection and R0 resection, albeit at a slightly higher risk of complications. Given scarce data on ESD from India, we performed a retrospective analysis of our experience with colorectal ESD (CR-ESD) to know its clinical efficacy and complications as well as to assess the learning curve of CR-ESD in non-endemic-areas.
METHODS: Retrospective analysis of prospectively maintained datasheet performed. All patients with large (>2cm), complex or recurrent colorectal LST who underwent ESD at our center between 2012 and 2021 were included in the study. Various baseline lesion-related parameters, procedure-related parameters, enbloc resection (ER) rates, R0 margins and adverse event rates were retrieved. CUSUM analysis was performed to calculate the minimum required procedures to achieve competency in CR-ESD.
RESULTS: Total 149 patients were included in the study; mean patient age was 61.36±18.21 years. Most patients had lesions in rectum (n=102; 68.5%) followed by sigmoid colon (n=25; 16.8%). The mean lesion size was 46.62 ± 25.46 mm and the mean procedure duration for ESD was 219.30 ± 150.05 min. ER was achieved in 94.6% of lesions. R0 resection was achieved in 132 patients (88.6%). Overall, six (4%) adverse events were noted, of which one required surgical intervention. As many as 105 patients (70.5%) had adenomatous lesions on histology. Seventy-four patients underwent follow-up colonoscopy, of which three had a recurrence of adenomatous lesions and five had post-resection stricture requiring endoscopic dilation. CUSUM curve analysis calculated the learning curve for ESD was 47 resections for ER and 55 for the occurrence of AEs, with a composite CUSUM at 47 procedures.
CONCLUSIONS: CR-ESD even in non-endemic area is associated with high en bloc resection rates, R0 resection rates and acceptable complication profile. Approximately 50 cases of CR-ESD are required to achieve competency.

Background and Objectives: Endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) are both well-established and effective treatments for dysplasia and early cancer in Barrett\'s esophagus (BE). This study aims to compare the short- and long-term outcomes associated with these procedures in treating Barrett\'s neoplasia. Materials and Methods: This single-center retrospective cohort study included 95 patients, either EMR (n = 67) or ESD (n = 28), treated for Barrett\'s neoplasia at Sahlgrenska University Hospital between 2004 and 2019. The primary outcome was the complete (en-bloc) R0 resection rate. Secondary outcomes included the curative resection rate, additional endoscopic resections, adverse events, and overall survival. Results: The complete R0 resection rate was 62.5% for ESD compared to 16% for EMR (p < 0.001). The curative resection rate for ESD was 54% versus 16% for EMR (p < 0.001). During the follow-up, 22 out of 50 patients in the EMR group required additional endoscopic resections (AERs) compared to 3 out of 21 patients in the ESD group (p = 0.028). There were few adverse events associated with both EMR and ESD. In both the stratified Kaplan-Meier survival analysis (Log-rank test, Chi-square = 2.190, df = 1, p = 0.139) and the multivariate Cox proportional hazards model (hazard ratio of 0.988; 95% CI: 0.459 to 2.127; p = 0.975), the treatment group (EMR vs. ESD) did not significantly impact the survival outcomes. Conclusions: Both EMR and ESD are effective and safe treatments for BE neoplasia with few adverse events. ESD resulted in higher curative resection rates with fewer AERs, indicating its potential as a primary treatment modality. However, the survival analysis showed no difference between the methods, highlighting their comparable long-term outcomes.

The economic trend and the health care landscape are rapidly evolving across Asia. Effective real-world data (RWD) for regulatory and clinical decision-making is a crucial milestone associated with this evolution. This necessitates a critical evaluation of RWD generation within distinct nations for the use of various RWD warehouses in the generation of real-world evidence (RWE). In this article, we outline the RWD generation trends for 2 contrasting nation archetypes: \"Solo Scholars\"-nations with relatively self-sufficient RWD research systems-and \"Global Collaborators\"-countries largely reliant on international infrastructures for RWD generation. The key trends and patterns in RWD generation, country-specific insights into the predominant databases used in each country to produce RWE, and insights into the broader landscape of RWD database use across these countries are discussed. Conclusively, the data point out the heterogeneous nature of RWD generation practices across 10 different Asian nations and advocate for strategic enhancements in data harmonization. The evidence highlights the imperative for improved database integration and the establishment of standardized protocols and infrastructure for leveraging electronic medical records (EMR) in streamlining RWD acquisition. The clinical data analysis and reporting system of Hong Kong is an excellent example of a successful EMR system that showcases the capacity of integrated robust EMR platforms to consolidate and produce diverse RWE. This, in turn, can potentially reduce the necessity for reliance on numerous condition-specific local and global registries or limited and largely unavailable medical insurance or claims databases in most Asian nations. Linking health technology assessment processes with open data initiatives such as the Observational Medical Outcomes Partnership Common Data Model and the Observational Health Data Sciences and Informatics could enable the leveraging of global data resources to inform local decision-making. Advancing such initiatives is crucial for reinforcing health care frameworks in resource-limited settings and advancing toward cohesive, evidence-driven health care policy and improved patient outcomes in the region.

BACKGROUND: Primary care physicians are at the forefront of the clinical process that can lead to diagnosis, referral, and treatment. With electronic medical records (EMRs) being introduced and, over time, gaining acceptance by primary care users, they have now become a standard part of care. EMRs have the potential to be further optimized with the introduction of artificial intelligence (AI). There has yet to be a widespread exploration of the use of AI in primary health care and how clinicians envision AI use to encourage further uptake.
OBJECTIVE: The primary objective of this research is to understand if the user-centered design approach, rooted in contextual design, can lead to an increased likelihood of adoption of an AI-enabled encounter module embedded in a primary care EMR. In this study, we use human factor models and the technology acceptance model to understand the results.
METHODS: To accomplish this, a partnership has been established with an industry partner, TELUS Health, to use their EMR, the collaborative health record. The overall intention is to understand how to improve the user experience by using user-centered design to inform how AI should be embedded in an EMR encounter. Given this intention, a user-centered approach will be used to accomplish it. The approach of user-centered design requires qualitative interviewing to gain a clear understanding of users\' approaches, intentions, and other key insights to inform the design process. A total of 5 phases have been designed for this study.
RESULTS: As of March 2024, a total of 14 primary care clinician participants have been recruited and interviewed. First-cycle coding of all qualitative data results is being conducted to inform redesign considerations.
CONCLUSIONS: Some limitations need to be acknowledged related to the approach of this study. There is a lack of market maturity of AI-enabled EMR encounters in primary care, requiring research to take place through scenario-based interviews. However, this participant group will still help inform design considerations for this tool. This study is targeted for completion in the late fall of 2024.
UNASSIGNED: DERR1-10.2196/54365.

UNASSIGNED: To describe the demographics and clinical profile of patients with glaucoma presenting during the novel coronavirus (COVID-19) lockdown and unlock phases in India.
UNASSIGNED: This retrospective hospital-based comparative study included patients presenting between March 25, 2017, and March 31, 2021. All patients who presented with glaucoma disorders were included as cases. The demographic and clinical data of these glaucoma patients were collected using an electronic medical record system.
UNASSIGNED: Overall, 34,419 patients (mean 47 per day) diagnosed with glaucoma diseases presented to the network and were included for analysis. The mean age of the patients was 54.16 ± 18.74 years and most were male (n=21,140; 61.42%) from the urban region (n=12,871;37.4%). On categorizing based on the timeline of the COVID-19 pandemic, most of the patients presented pre-COVID-19 (n=29,122; 84.61%), followed by a minority (n=175; 0.51%) during the lockdown and the rest (n=5,122; 14.88%) during unlock phase. An increasing number of patients with secondary glaucoma (n=82; 46.86%) and presenting from the local intra-city (n=82; 46.86%) was seen during the lockdown. There was a 6.6-fold increase in neovascular glaucoma and a 2.7-fold increase in lens induced glaucoma during the lockdown phase ((p<0.001) for both). There was a significant increase in subjects in 4th decade (p<0.03) and a decrease in subjects in 7th decade (p<0.008) during the lockdown period.
UNASSIGNED: The presentation of patients with glaucoma disorders to the hospital is evolving due to the COVID-19 pandemic. The footfalls of patients during the unlock regained to two-thirds of the pre COVID-19 level. During the lockdown, the older patients were less, there was an increase in younger patients and those with secondary glaucoma, and the majority presenting from within the city.

UNASSIGNED: The Pediatric Surviving Sepsis Campaign supports the implementation of automated tools for early sepsis recognition. In 2019 the C.S. Mott Children\'s Hospital Pediatric Intensive Care Unit deployed an electronic medical record (EMR)-based screening for early recognition and treatment of sepsis.
UNASSIGNED: We analyzed all automated primary sepsis alerts, secondary screens, and bedside huddles from November 2019 to January 2020 (Cohort 1) and from November 2020 to January 2021 (Cohort 2) to identify barriers and facilitators for the use of this tool. We distributed surveys to frontline providers to gather feedback on end-user experience.
UNASSIGNED: In Cohort 1, 895 primary alerts were triggered, yielding 503 completed secondary screens and 40 bedside huddles. In Cohort 2, 925 primary alerts were triggered, yielding 532 completed secondary screens and 12 bedside huddles. Surveys assessing end-user experience identified the following facilitators: (1) 73% of nurses endorsed the bedside huddle as value added; (2) 74% of medical providers agreed the bedside huddle increased the likelihood of interventions. The greatest barriers to successful implementation included the (1) overall large number of primary alerts from the automated tool and (2) rate of false alerts, many due to routine respiratory therapy interventions.
UNASSIGNED: Our data suggests that the successful implementation of EMR-based sepsis screening tools requires countermeasures focusing on 3 key drivers for change: education, technology, and patient safety.
UNASSIGNED: While both medical providers and bedside nurses found merit in our EMR-based sepsis early recognition system, continued refinement is necessary to avoid sepsis alert fatigue.

BACKGROUND: Population viral load (VL), the most comprehensive measure of the HIV transmission potential, cannot be directly measured due to lack of complete sampling of all people with HIV.
OBJECTIVE: A given HIV clinic\'s electronic health record (EHR), a biased sample of this population, may be used to attempt to impute this measure.
METHODS: We simulated a population of 10,000 individuals with VL calibrated to surveillance data with a geometric mean of 4449 copies/mL. We sampled 3 hypothetical EHRs from (A) the source population, (B) those diagnosed, and (C) those retained in care. Our analysis imputed population VL from each EHR using sampling weights followed by Bayesian adjustment. These methods were then tested using EHR data from an HIV clinic in Delaware.
RESULTS: Following weighting, the estimates moved in the direction of the population value with correspondingly wider 95% intervals as follows: clinic A: 4364 (95% interval 1963-11,132) copies/mL; clinic B: 4420 (95% interval 1913-10,199) copies/mL; and clinic C: 242 (95% interval 113-563) copies/mL. Bayesian-adjusted weighting further improved the estimate.
CONCLUSIONS: These findings suggest that methodological adjustments are ineffective for estimating population VL from a single clinic\'s EHR without the resource-intensive elucidation of an informative prior.