COVID-19 Computed tomography patterns in renal replacement therapy patients / Padrões de tomografia computadorizada da COVID-19 em pacientes em terapia renal substitutiva

ABSTRACT Introduction: Lung diseases are common in patients with end stage kidney disease (ESKD), making differential diagnosis with COVID-19 a challenge. This study describes pulmonary chest tomography (CT) findings in hospitalized ESKD patients on renal replacement therapy (RRT) with clinical suspicion of COVID-19. Methods: ESKD individuals referred to emergency department older than 18 years with clinical suspicion of COVID-19 were recruited. Epidemiological baseline clinical information was extracted from electronic health records. Pulmonary CT was classified as typical, indeterminate, atypical or negative. We then compared the CT findings of positive and negative COVID-19 patients. Results: We recruited 109 patients (62.3% COVID-19-positive) between March and December 2020, mean age 60 ± 12.5 years, 43% female. The most common etiology of ESKD was diabetes. Median time on dialysis was 36 months, interquartile range = 12-84. The most common pulmonary lesion on CT was ground glass opacities. Typical CT pattern was more common in COVID-19 patients (40 (61%) vs 0 (0%) in non-COVID-19 patients, p < 0.001). Sensitivity was 60.61% (40/66) and specificity was 100% (40/40). Positive predictive value and negative predictive value were 100% and 62.3%, respectively. Atypical CT pattern was more frequent in COVID-19-negative patients (9 (14%) vs 24 (56%) in COVID-19-positive, p < 0.001), while the indeterminate pattern was similar in both groups (13 (20%) vs 6 (14%), p = 0.606), and negative pattern was more common in COVID-19-negative patients (4 (6%) vs 12 (28%), p = 0.002). Conclusions: In hospitalized ESKD patients on RRT, atypical chest CT pattern cannot adequately rule out the diagnosis of COVID-19.

RESUMO Introdução: Doenças pulmonares são comuns em pacientes com doença renal em estágio terminal (DRET), dificultando o diagnóstico diferencial com COVID-19. Este estudo descreve achados de tomografia computadorizada de tórax (TC) em pacientes com DRET em terapia renal substitutiva (TRS) hospitalizados com suspeita de COVID-19. Métodos: Indivíduos maiores de 18 anos com DRET, encaminhados ao pronto-socorro com suspeita de COVID-19 foram incluídos. Dados clínicos e epidemiológicos foram extraídos de registros eletrônicos de saúde. A TC foi classificada como típica, indeterminada, atípica, negativa. Comparamos achados tomográficos de pacientes com COVID-19 positivos e negativos. Resultados: Recrutamos 109 pacientes (62,3% COVID-19-positivos) entre março e dezembro de 2020, idade média de 60 ± 12,5 anos, 43% mulheres. A etiologia mais comum da DRET foi diabetes. Tempo médio em diálise foi 36 meses, intervalo interquartil = 12-84. A lesão pulmonar mais comum foi opacidades em vidro fosco. O padrão típico de TC foi mais comum em pacientes com COVID-19 (40 (61%) vs. 0 (0%) em pacientes sem COVID-19, p < 0,001). Sensibilidade 60,61% (40/66), especificidade 100% (40/40). Valores preditivos positivos e negativos foram 100% e 62,3%, respectivamente. Padrão atípico de TC foi mais frequente em pacientes COVID-19-negativos (9 (14%) vs. 24 (56%) em COVID-19-positivos, p < 0,001), enquanto padrão indeterminado foi semelhante em ambos os grupos (13 (20%) vs. 6 (14%), p = 0,606), e padrão negativo foi mais comum em pacientes COVID-19-negativos (4 (6%) vs. 12 (28%), p = 0,002). Conclusões: Em pacientes com DRET em TRS hospitalizados, um padrão atípico de TC de tórax não pode excluir adequadamente o diagnóstico de COVID-19.

Risk factors for acute kidney injury in patients hospitalized with COVID-19 / Fatores de risco para lesão renal aguda em pacientes hospitalizados com COVID-19

Abstract Introduction: Acute kidney injury (AKI) occurs frequently in COVID-19 patients and is associated with greater morbidity and mortality. Knowing the risks of AKI allows for identification, prevention, and timely treatment. This study aimed to identify the risk factors associated with AKI in hospitalized patients. Methods: A descriptive, retrospective, cross-sectional, and analytical component study of adult patients hospitalized with COVID-19 from March 1 to December 31, 2020 was carried out. AKI was defined by the creatinine criteria of the KDIGO-AKI guidelines. Information, regarding risk factors, was obtained from electronic medical records. Results: Out of the 934 patients, 42.93% developed AKI, 60.59% KDIGO-1, and 9.9% required renal replacement therapy. Patients with AKI had longer hospital stay, higher mortality, and required more intensive care unit (ICU) admission, mechanical ventilation, and vasopressor support. Multivariate analysis showed that age (OR 1.03; 95% CI 1.02-1.04), male sex (OR 2.13; 95% CI 1.49-3.04), diabetes mellitus (DM) (OR 1.55; 95% CI 1.04-2.32), chronic kidney disease (CKD) (OR 2.07; 95% CI 1.06-4.04), C-reactive protein (CRP) (OR 1.02; 95% CI 1.00-1.03), ICU admission (OR 1.81; 95% CI 1.04-3.16), and vasopressor support (OR 7.46; 95% CI 3.34-16.64) were risk factors for AKI, and that bicarbonate (OR 0.89; 95% CI 0.84-0.94) and partial pressure arterial oxygen/inspired oxygen fraction index (OR 0.99; 95% CI 0.98-0.99) could be protective factors. Conclusions: A high frequency of AKI was documented in COVID-19 patients, with several predictors: age, male sex, DM, CKD, CRP, ICU admission, and vasopressor support. AKI occurred more frequently in patients with higher disease severity and was associated with higher mortality and worse outcomes.

RESUMO Introdução: Lesão renal aguda (LRA) ocorre frequentemente em pacientes com COVID-19 e associa-se a maior morbidade e mortalidade. Conhecer riscos da LRA permite a identificação, prevenção e tratamento oportuno. Este estudo teve como objetivo identificar fatores de risco associados à LRA em pacientes hospitalizados. Métodos: Realizou-se estudo descritivo, retrospectivo, transversal e de componente analítico de pacientes adultos hospitalizados com COVID-19 de 1º de março a 31 de dezembro, 2020. Definiu-se a LRA pelos critérios de creatinina das diretrizes KDIGO-LRA. Informações sobre fatores de risco foram obtidas de prontuários eletrônicos. Resultados: Dos 934 pacientes, 42,93% desenvolveram LRA, 60,59% KDIGO-1 e 9,9% necessitaram de terapia renal substitutiva. Pacientes com LRA apresentaram maior tempo de internação, maior mortalidade e necessitaram de mais internações em UTIs, ventilação mecânica e suporte vasopressor. A análise multivariada mostrou que idade (OR 1,03; IC 95% 1,02-1,04), sexo masculino (OR 2,13; IC 95% 1,49-3,04), diabetes mellitus (DM) (OR 1,55; IC 95% 1,04-2,32), doença renal crônica (DRC) (OR 2,07; IC 95% 1,06-4,04), proteína C reativa (PCR) (OR 1,02; IC 95% 1,00-1,03), admissão em UTI (OR 1,81; IC 95% 1,04-3,16) e suporte vasopressor (OR 7,46; IC 95% 3,34-16,64) foram fatores de risco para LRA, e que bicarbonato (OR 0,89; IC 95% 0,84-0,94) e índice de pressão parcial de oxigênio arterial/fração inspirada de oxigênio (OR 0,99; IC 95% 0,98-0,99) poderiam ser fatores de proteção. Conclusões: Documentou-se alta frequência de LRA em pacientes com COVID-19, com diversos preditores: idade, sexo masculino, DM, DRC, PCR, admissão em UTI e suporte vasopressor. LRA ocorreu mais frequentemente em pacientes com maior gravidade da doença e associou-se a maior mortalidade e piores desfechos.

Identifying antinuclear antibody positive individuals at risk for developing systemic autoimmune disease: development and validation of a real-time risk model.

Objective: Positive antinuclear antibodies (ANAs) cause diagnostic dilemmas for clinicians. Currently, no tools exist to help clinicians interpret the significance of a positive ANA in individuals without diagnosed autoimmune diseases. We developed and validated a risk model to predict risk of developing autoimmune disease in positive ANA individuals. Methods: Using a de-identified electronic health record (EHR), we randomly chart reviewed 2,000 positive ANA individuals to determine if a systemic autoimmune disease was diagnosed by a rheumatologist. A priori, we considered demographics, billing codes for autoimmune disease-related symptoms, and laboratory values as variables for the risk model. We performed logistic regression and machine learning models using training and validation samples. Results: We assembled training (n = 1030) and validation (n = 449) sets. Positive ANA individuals who were younger, female, had a higher titer ANA, higher platelet count, disease-specific autoantibodies, and more billing codes related to symptoms of autoimmune diseases were all more likely to develop autoimmune diseases. The most important variables included having a disease-specific autoantibody, number of billing codes for autoimmune disease-related symptoms, and platelet count. In the logistic regression model, AUC was 0.83 (95% CI 0.79-0.86) in the training set and 0.75 (95% CI 0.68-0.81) in the validation set. Conclusion: We developed and validated a risk model that predicts risk for developing systemic autoimmune diseases and can be deployed easily within the EHR. The model can risk stratify positive ANA individuals to ensure high-risk individuals receive urgent rheumatology referrals while reassuring low-risk individuals and reducing unnecessary referrals.

Breast cancer (BC) and severe COVID-19 (C-19) outcomes: a matched analysis.

PURPOSE: Patients with cancer receiving anticancer treatment have a higher risk of severe COVID-19 (C-19) outcomes. We examine the association between breast cancer (BC), recent treatment (systemic therapy, surgery, radiation), and C-19 outcomes. METHODS: Retrospective matched cohort study using the Optum® de-identified C-19 Electronic Health Record dataset (2007-2022). Patients with C-19 were categorized into: no cancer, BC with recent treatment, and BC without recent treatment and matched based on age, C-19 diagnosis date, and comorbidity score. We evaluated 30-day mortality, mechanical ventilation, intensive care unit (ICU) stay, and hospitalization. A composite outcome including all outcomes was analyzed. Multivariable logistic regression models were used. RESULTS: 2200 matched triplets (1:1:10) of patients with BC recently treated, BC not recently treated, and no cancer were included. Rates of adverse outcomes improved in 2021 compared to 2020. Compared to patients without cancer, those with BC recently treated had a similar risk of adverse outcomes, while patients with BC not recently treated had a lower risk of ICU stay and hospitalization. Using the composite variable, BC recently treated had similar outcomes (OR = 1.02; 95%CI 0.93-1.11) to patients without cancer, while BC patients not recently treated had better outcomes (OR = 0.66; 95%CI 0.59-0.74). Among patients with BC, chemotherapy within 3 months was associated with a higher risk of hospitalization (OR = 2.30; 95%CI 1.76-2.99) and composite outcome (OR = 2.11; 95%CI 1.64-2.72). CONCLUSION: Patients with BC have a similar risk of adverse C-19 outcomes compared to patients without cancer. Among patients with BC, recent chemotherapy was associated with a higher risk of hospitalization.

Multi-institutional Assessment of Otitis Media Epidemiology Using Real-world Data.

OBJECTIVES: To determine rates and risk factors of pediatric otitis media (OM) using real-world electronic health record (PEDSnet) data from January 2009 through May 2021. STUDY DESIGN: Retrospective cohort study. SETTING: Seven pediatric academic health systems that participate in PEDSnet. METHODS: Children <6 months-old at time of first outpatient, Emergency Department, or inpatient visit were included and followed longitudinally. A time-to-event analysis was performed using a Cox proportional hazards model to estimate hazard ratios for OM incidence based on sociodemographic factors and specific health conditions. RESULTS: The PEDSnet cohort included 910,265 children, 54.3% male, mean age (months) 1.3 [standard deviation (SD) 1.6] and mean follow up (years) 4.3 (SD 3.2). By age 3 years, 39.6% of children had evidence of one OM episode. OM rates decreased following pneumococcal-13 vaccination (PCV-13) and the COVID-19 pandemic. Along with young age, non-Hispanic Black/African American or Hispanic race/ethnicity, public insurance, higher family income, and male sex had higher incidence rates. Health conditions that increased OM risk included cleft palate [adjusted hazard ratio (aHR) 4.0 [95% confidence interval (CI) 3.9-4.2], primary ciliary dyskinesia [aHR 2.5 (95% CI 1.8-3.5)], trisomy 21 [aHR 2.0 (95% CI 1.9-2.1)], atopic dermatitis [aHR 1.4 (95% CI 1.4-1.4)], and gastroesophageal reflux [aHR1.5 (95% CI 1.5-1.5)]. CONCLUSIONS: Approximately 20% of children by age 1 and 40% of children by age 3 years will have experienced an OM episode. OM rates decreased after PCV-13 and COVID-19. Children with abnormal ciliary function or craniofacial conditions, specifically cleft palate, carry the highest risk of OM.

Interoperability of phenome-wide multimorbidity patterns: a comparative study of two large-scale EHR systems.

Background: Electronic health records (EHR) are increasingly used for studying multimorbidities. However, concerns about accuracy, completeness, and EHRs being primarily designed for billing and administration raise questions about the consistency and reproducibility of EHR-based multimorbidity research. Methods: Utilizing phecodes to represent the disease phenome, we analyzed pairwise comorbidity strengths using a dual logistic regression approach and constructed multimorbidity as an undirected weighted graph. We assessed the consistency of the multimorbidity networks within and between two major EHR systems at local (nodes and edges), meso (neighboring patterns), and global (network statistics) scales. We present case studies to identify disease clusters and uncover clinically interpretable disease relationships. We provide an interactive web tool and a knowledge base combing data from multiple sources for online multimorbidity analysis. Findings: Analyzing data from 500,000 patients across Vanderbilt University Medical Center and Mass General Brigham health systems, we observed a strong correlation in disease frequencies ( Kendall's τ = 0.643) and comorbidity strengths (Pearson ρ = 0.79). Consistent network statistics across EHRs suggest a similar structure of multimorbidity networks at various scales. Comorbidity strengths and similarities of multimorbidity connection patterns align with the disease genetic correlations. Graph-theoretic analyses revealed a consistent core-periphery structure, implying efficient network clustering through threshold graph construction. Using hydronephrosis as a case study, we demonstrated the network's ability to uncover clinically relevant disease relationships and provide novel insights. Interpretation: Our findings demonstrate the robustness of large-scale EHR data for studying complex disease interactions. The alignment of multimorbidity patterns with genetic data suggests the potential utility for uncovering shared etiology of diseases. The consistent core-periphery network structure offers a strategic approach to analyze disease clusters. This work also sets the stage for advanced disease modeling, with implications for precision medicine. Funding: VUMC Biostatistics Development Award, UL1 TR002243, R21DK127075, R01HL140074, P50GM115305, R01CA227481.

Evaluation of Primary Healthcare Centers' Service Availability and Readiness for Implementing Diabetes Care in Abuja, Nigeria: A Cross-Sectional, Formative Assessment.

Introduction: Noncommunicable diseases (NCDs) are associated with a high and rising burden of morbidity and mortality in sub-Saharan Africa, including Nigeria. Diabetes mellitus (DM) is among the leading causes of NCD-related deaths worldwide and is a foremost public health problem in Nigeria. As part of the National Multi-Sectoral Action Plan for the Prevention and Control of NCDs, Nigeria has committed to implementing the World Health Organization (WHO) Package of Essential NCD control interventions. Implementing the intervention requires the availability of essential elements, including guidelines, trained staff, health management information systems, equipment, and medications, in primary healthcare centers (PHCs). This study assessed the availability of the WHO package components and the readiness of PHCs to implement a DM screening, evaluation, and management program. Methods: This cross-sectional formative assessment adapted the WHO Service Availability and Readiness Assessment (SARA) tool to survey 30 PHCs selected by multistage sampling for readiness to deliver DM diagnosis and care in Abuja, Nigeria, between August 2021 and October 2021. The service availability and readiness indicator scores were calculated based on the proportion of PHCs with available DM care services, minimum staff requirement, diagnostic tests, equipment, medications, and national guidelines/protocols for DM care within the defined SARA domain. Results: All 30 PHCs reported the availability of at least two full-time staff (median [interquartile range] staff = 5 [4-9]), which were mostly community health extension workers (median [interquartile range]) = 3 [1-4]. At least one staff member was recently trained in DM care in only 11 (36%) of the PHCs. The study also reported high availability (100%) of paper-based health management information systems (HMIS) and DM screening services using a glucometer (87%), but low availability of DM treatment (23%), printed job aids (27%), and national guidelines/protocols (0%). Conclusion: This systematic assessment of PHCs' readiness to implement a DM screening, evaluation, and management program in Abuja demonstrated readiness to integrate DM care into PHCs in terms of equipment, paper-based HMIS, and nonphysician health workers' availability. However, strategies are needed to promote DM health workforce training, provide DM management guidelines, and ensure a reliable supply of essential DM medications.

Development and validation of an individualised nomogram to predict mother-to-child transmission in pregnant women with syphilis in China: a retrospective cohort study.

OBJECTIVES: The elimination of mother-to-child transmission (MTCT) of syphilis has been set as a public health priority. However, an instrument to predict the MTCT of syphilis is not available. We aimed to develop and validate an intuitive nomogram to predict the individualised risk of MTCT in pregnant women with syphilis in China. DESIGN: Retrospective cohort study. SETTING: Data was acquired from the National Information System of Prevention of MTCT of Syphilis in Guangdong province between 2011 and 2020. PARTICIPANTS: A total of 13 860 pregnant women with syphilis and their infants were included and randomised 7:3 into the derivation cohort (n=9702) and validation cohort (n=4158). PRIMARY OUTCOME MEASURES: Congenital syphilis. RESULTS: Among 13 860 pregnant women with syphilis and their infants included, 1370 infants were diagnosed with congenital syphilis. Least absolute shrinkage and selection operator regression and multivariable logistic regression showed that age, ethnicity, registered residence, marital status, number of pregnancies, transmission route, the timing of syphilis diagnosis, stage of syphilis, time from first antenatal care to syphilis diagnosis and toluidine red unheated serum test titre were predictors of MTCT of syphilis. A nomogram was developed based on the predictors, which demonstrated good calibration and discrimination with an area under the curve of the receiver operating characteristic of 0.741 (95% CI: 0.728 to 0.755) and 0.731 (95% CI: 0.710 to 0.752) for the derivation and validation cohorts, respectively. The net benefit of the predictive models was positive, demonstrating a significant potential for clinical decision-making. We have also developed a web calculator based on this prediction model. CONCLUSIONS: Our nomogram exhibited good performance in predicting individualised risk for MTCT of syphilis, which may help guide early and personalised prevention for MTCT of syphilis.

Validity of ICD-10-based algorithms to identify patients with influenza in inpatient and outpatient settings.

PURPOSE: To evaluate the validity of ICD-10-CM code-based algorithms as proxies for influenza in inpatient and outpatient settings in the USA. METHODS: Administrative claims data (2015-2018) from the largest commercial insurer in New Jersey (NJ), USA, were probabilistically linked to outpatient and inpatient electronic health record (EHR) data containing influenza test results from a large NJ health system. The primary claims-based algorithms defined influenza as presence of an ICD-10-CM code for influenza, stratified by setting (inpatient/outpatient) and code position for inpatient encounters. Test characteristics and 95% confidence intervals (CIs) were calculated using test-positive influenza as a reference standard. Test characteristics of alternative outpatient algorithms incorporating CPT/HCPCS testing codes and anti-influenza medication pharmacy claims were also calculated. RESULTS: There were 430 documented influenza test results within the study period (295 inpatient, 135 outpatient). The claims-based influenza definition had a sensitivity of 84.9% (95% CI 72.9%-92.1%), specificity of 96.3% (95% CI 93.1%-98.0%), and PPV of 83.3% (95% CI 71.3%-91.0%) in the inpatient setting, and a sensitivity of 76.7% (95% CI 59.1%-88.2%), specificity of 96.2% (95% CI 90.6%-98.5%), PPV of 85.2% (95% CI 67.5%-94.1%) in the outpatient setting. Primary inpatient discharge diagnoses had a sensitivity of 54.7% (95% CI 41.5%-67.3%), specificity of 99.6% (95% CI 97.7%-99.9%), and PPV of 96.7% (95% CI 83.3%-99.4%). CPT/HCPCS codes and anti-influenza medication claims were present for few outpatient encounters (sensitivity 3%-10%). CONCLUSIONS: In a large US healthcare system, inpatient ICD-10-CM codes for influenza, particularly primary inpatient diagnoses, had high predictive value for test-positive influenza. Outpatient ICD-10-CM codes were moderately predictive of test-positive influenza.

A Novel Electronic Record System for Documentation and Efficient Workflow for Community Health Workers: Development and Usability Study.

BACKGROUND: The COVID-19 pandemic added to the decades of evidence that public health institutions are routinely stretched beyond their capacity. Community health workers (CHWs) can be a crucial extension of public health resources to address health inequities, but systems to document CHW efforts are often fragmented and prone to unneeded redundancy, errors, and inefficiency. OBJECTIVE: We sought to develop a more efficient data collection system for recording the wide range of community-based efforts performed by CHWs. METHODS: The Communities Organizing to Promote Equity (COPE) project is an initiative to address health disparities across Kansas, in part, through the deployment of CHWs. Our team iteratively designed and refined the features of a novel data collection system for CHWs. Pilot tests with CHWs occurred over several months to ensure that the functionality supported their daily use. Following implementation of the database, procedures were set to sustain the collection of feedback from CHWs, community partners, and organizations with similar systems to continually modify the database to meet the needs of users. A continuous quality improvement process was conducted monthly to evaluate CHW performance; feedback was exchanged at team and individual levels regarding the continuous quality improvement results and opportunities for improvement. Further, a 15-item feedback survey was distributed to all 33 COPE CHWs and supervisors for assessing the feasibility of database features, accessibility, and overall satisfaction. RESULTS: At launch, the database had 60 active users in 20 counties. Documented client interactions begin with needs assessments (modified versions of the Arizona Self-sufficiency Matrix and PRAPARE [Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences]) and continue with the longitudinal tracking of progress toward goals. A user-specific automated alerts-based dashboard displays clients needing follow-up and upcoming events. The database contains over 55,000 documented encounters across more than 5079 clients. Available resources from over 2500 community organizations have been documented. Survey data indicated that 84% (27/32) of the respondents considered the overall navigation of the database as very easy. The majority of the respondents indicated they were overall very satisfied (14/32, 44%) or satisfied (15/32, 48%) with the database. Open-ended responses indicated the database features, documentation of community organizations and visual confirmation of consent form and data storage on a Health Insurance Portability and Accountability Act-compliant record system, improved client engagement, enrollment processes, and identification of resources. CONCLUSIONS: Our database extends beyond conventional electronic medical records and provides flexibility for ever-changing needs. The COPE database provides real-world data on CHW accomplishments, thereby improving the uniformity of data collection to enhance monitoring and evaluation. This database can serve as a model for community-based documentation systems and be adapted for use in other community settings.

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study.

BACKGROUND: Triage is the process of accurately assessing patients' symptoms and providing them with proper clinical treatment in the emergency department (ED). While many countries have developed their triage process to stratify patients' clinical severity and thus distribute medical resources, there are still some limitations of the current triage process. Since the triage level is mainly identified by experienced nurses based on a mix of subjective and objective criteria, mis-triage often occurs in the ED. It can not only cause adverse effects on patients, but also impose an undue burden on the health care delivery system. OBJECTIVE: Our study aimed to design a prediction system based on triage information, including demographics, vital signs, and chief complaints. The proposed system can not only handle heterogeneous data, including tabular data and free-text data, but also provide interpretability for better acceptance by the ED staff in the hospital. METHODS: In this study, we proposed a system comprising 3 subsystems, with each of them handling a single task, including triage level prediction, hospitalization prediction, and length of stay prediction. We used a large amount of retrospective data to pretrain the model, and then, we fine-tuned the model on a prospective data set with a golden label. The proposed deep learning framework was built with TabNet and MacBERT (Chinese version of bidirectional encoder representations from transformers [BERT]). RESULTS: The performance of our proposed model was evaluated on data collected from the National Taiwan University Hospital (901 patients were included). The model achieved promising results on the collected data set, with accuracy values of 63%, 82%, and 71% for triage level prediction, hospitalization prediction, and length of stay prediction, respectively. CONCLUSIONS: Our system improved the prediction of 3 different medical outcomes when compared with other machine learning methods. With the pretrained vital sign encoder and repretrained mask language modeling MacBERT encoder, our multimodality model can provide a deeper insight into the characteristics of electronic health records. Additionally, by providing interpretability, we believe that the proposed system can assist nursing staff and physicians in taking appropriate medical decisions.

Historical Redlining and Heart Failure Outcomes Following Hospitalization in the Southeastern United States.

BACKGROUND: Historical redlining, a discriminatory lending practice, is an understudied component of the patient risk environment following hospital discharge. We investigated associations between redlining, patient race, and outcomes following heart failure hospitalization. METHODS AND RESULTS: We followed a hospital-based cohort of Black and White patients using electronic medical records for acute heart failure hospitalizations between 2010 and 2018 (n=6800). Patient residential census tracts were geocoded according to the 1930s Home Owners' Loan Corporation map grades (A/B: best/still desirable, C: declining, D: redlined). We used Poisson regression to analyze associations between Home Owners' Loan Corporation grade and 30-day outcomes (readmissions, mortality, and their composite). One-third of patients resided in historically redlined tracts (n=2034). In race-stratified analyses, there was a positive association between historically declining neighborhoods and composite readmissions and mortality for Black patients (risk ratio [RR], 1.24 [95% CI, 1.003-1.54]) and an inverse association between redlined neighborhoods and 30-day readmissions among White patients (RR, 0.58 [95% CI, 0.39-0.86]). Examining racial disparities across Home Owners' Loan Corporation grades, Black patients had higher 30-day readmissions (RR, 1.86 [95% CI, 1.31-2.65]) and composite readmissions and mortality (RR, 1.32 [95% CI, 1.04-1.65]) only in historically redlined neighborhoods. CONCLUSIONS: Historical redlining had potentially mixed impacts on outcomes by race, such that residing in less desirable neighborhoods was associated with an elevated risk of an adverse outcome following heart failure hospitalization in Black patients and a reduced risk in White patients. Moreover, racial disparities in patient outcomes were present only in historically redlined neighborhoods. Additional research is needed to explore observed heterogeneity in outcomes.

Social isolation and the risk of Parkinson disease in the UK biobank study.

Parkinson disease (PD) has become one of the most rapidly growing causes of disability among the older population and social isolation is a major concern in the PD community. However, the relationship between social isolation and future risk of PD remains unclear. This study included 192,340 participants aged 60 or older who were free of dementia and PD at baseline from the UK Biobank study. Social isolation was measured using a composite score derived from three questions on number in household, frequency of friend/family visits, and leisure/social activities. Incident PD cases were identified through electronic health records. Multivariable-adjusted Cox regression models were used to compute the hazard ratio (HR) and 95% confidence interval (CI). Among the 192,340 participants (mean [standard deviation] age, 64.2 [2.9] years; 103,253 [53.7%] women), 89,075 (46.3%) participants were in the least isolated group and 26,161 (13.6%) were in the most isolated group. Over a median follow-up of 12.5 years, 2048 incident PD cases were documented. Compared to the least isolated group, the multivariable-adjusted HRs (95% CIs) for PD were 1.00 (0.91-1.10) for the moderately isolated group and 1.19 (1.05-1.36) for the most isolated group (P-trend = 0.04). The observed association was independent of the genetic susceptibility to PD and consistent in subgroup analyses. Social isolation was associated with a higher risk of PD regardless of genetic risk. Our findings highlighted the importance of developing screening and intervention strategies for social isolation among older adults to reduce the risk of PD.

Health status based on EQ-5D-5L for the cancer patient population in Malaysia.

The EQ-5D is a common generic tool used in clinical trials and economic evaluations to evaluate the health-related quality of life as a proxy of health outcomes. To date, studies using EQ-5D-5L to evaluate the health status of cancer patients remain scarce in Malaysia. In this study, EQ-5D-5L dimensions, EQ-5D-5L index, and EQ-VAS scores were applied to assess the health status of Malaysian cancer patients. A cross-sectional study was conducted March-December 2022 to collect data relevant to the EQ-5D-5L valuation of health status via the Research Electronic Data Capture (REDCap) platform. Respondents rated their health states using EQ-5D-5L and EQ-VAS. Among the 235 respondents, the mean EQ-5D-5L index and EQ-VAS score were 0.76 (SD 0.223) and 81.06 (SD 16.36). Most of the patients reported some problems in the pain/discomfort and anxiety/depression dimensions. The level of education, stage of cancer, and comorbidity were significantly associated with better health status on EQ-5D-5L (p < 0.05) but only the stage of cancer was significantly associated with EQ-VAS scores. This study highlighted the disparities in self-reported health status across patients of different sociodemographic and medical profiles with EQ-5D-5L valuation. Thus, future research should use EQ-5D norm scores as a benchmark of comparison among cancer patients.

Trends and geospatial distribution of stillbirths in Uganda, 2014-2020.

INTRODUCTION: Uganda with 17.8 stillbirths per 1,000 deliveries in 2021, is among the countries with a high burden of stillbirths globally. In 2014, Uganda adopted the World Health Organization Every New-born Action Plan (ENAP), which targets < 10 stillbirths per 1,000 deliveries by 2035. Little is known about the trends of stillbirth burden since ENAP was introduced. We assessed the temporal, and spatial distribution of stillbirths, in Uganda, 2014-2020, to inform programming for safe pregnancies and deliveries. METHODS: We obtained and analysed stillbirth surveillance data from the District Health Information System, 2014-2020. A stillbirth was defined as the death of a foetus > 28 weeks of pregnancy or weighing > 1000 g before or during birth and reported to a health facility. We calculated annual incidence rates of stillbirths per 1,000 deliveries at district, regional, and national levels. We used logistic regression to determine the significance of trends. RESULTS: The overall national annual incidence of stillbirths decreased from 24/1,000 deliveries in 2014 to 17/1,000 deliveries in 2020. During the same period, reporting rates declined from 71% in 2014 to 46% in 2020. The central region continuously had the highest incidence rate for the past 5 years despite the largest decline (OR = 0.79; CI = 0.77-0.83, P < 0.001) while the eastern region had the smallest decline (OR = 0.59; CI = 0.57-0.61, P < 0.001). Districts with persistently high annual incidence rates of stillbirths (> 30/1000) included Mubende, Kalangala, Hoima, and Nebbi. There was no difference in the reporting rates of the most- vs. least-affected districts. CONCLUSION: Even with suboptimal reporting, the incidence of stillbirths remained above the national target. Specific areas in the country appear to have particularly high stillbirth rates. We recommend continuous capacity building in managing pregnant women with an emphasis on the most affected districts, and investigation into the reasons for low reporting.

How do opt-in versus opt-out settings nudge patients toward electronic health record adoption? An exploratory study of facilitators and barriers in Austria and France.

BACKGROUND: Electronic health records (EHR) are becoming an integral part of the health system in many developed countries, though implementations and settings vary across countries. Some countries have adopted an opt-out policy, in which patients are enrolled in the EHR system following a default nudge, while others have applied an opt-in policy, where patients have to take action to opt into the system. While opt-in systems may exhibit lower levels of active user requests for access, this contrasts with opt-out systems where a notable percentage of users may passively retain access. Thus, our research endeavor aims to explore facilitators and barriers that contribute to explaining EHR usage (i.e., actively accessing the EHR system) in two countries with either an opt-in or opt-out setting, exemplified by France and Austria. METHODS: A qualitative exploratory approach using a semi-structured interview guideline was undertaken in both countries: 1) In Austria, with four homogenously composed group discussions, and 2) in France, with 19 single patient interviews. The data were collected from October 2020 to January 2021. RESULTS: Influencing factors were categorized into twelve subcategories. Patients have similar experiences in both countries with regard to all facilitating categories, for instance, the role of health providers, awareness of EHR and social norms. However, we highlighted important differences between the two systems regarding hurdles impeding EHR usage, namely, a lack of communication as well as transparency or information security about EHR. CONCLUSION: Implementing additional safeguards to enhance privacy protection and supporting patients to improve their digital ability may help to diminish the perception of EHR-induced barriers and improve patients' health and commitment in the long term. PRACTICAL IMPLICATIONS: Understanding the differences and similarities will help to develop practical implications to tackle the problem of low EHR usage rates in the long run. This problem is prevalent in countries with both types of EHR default settings.

Epidemiology of Irritable Bowel Syndrome in a Large Academic Safety-Net Hospital.

(1) Background: Irritable bowel syndrome (IBS) is a highly prevalent disorder of gut-brain interaction (DGBI) that is known to reduce the quality of life and raise healthcare costs. The aim of this study was to describe the epidemiology of IBS in a large multiracial academic safety-net hospital. (2) Methods: An electronic query was performed using ICD-9 codes to identify 740 IBS outpatients seen at the Boston Medical Center (BMC) between 1 January 2005 and 30 September 2007. Demographic data were collected from electronic medical records. Bivariate analyses using chi-square tests and ANOVA were used to calculate the significance of categorical and continuous dependent variables, respectively. (3) Results: Compared with the general BMC outpatient population, the IBS cohort consisted of significantly higher proportions of White and Asian patients and lower proportions of Black and Hispanic patients (p < 0.0001). White and Asian patients predominantly had private insurance, while Black and Hispanic patients mostly had government/state-funded or no insurance (p < 0.0001). The IBS subgroup frequencies were similar across racial groups; however, Hispanic patients had IBS with constipation (32%, p < 0.02) more often compared to non-Hispanic patients. (4) Conclusions: Significant differences were found across the racial groups studied in this large outpatient IBS cohort. These findings are likely attributed to racial and socioeconomic disparities in healthcare access and utilization.

Can Patients with Electrolyte Disturbances Be Safely and Effectively Treated in a Hospital-at-Home, Telemedicine-Controlled Environment? A Retrospective Analysis of 267 Patients.

BACKGROUND: Morbidities indicated for hospital-at-home (HAH) treatment include infectious diseases and exacerbations of chronic conditions. Electrolyte disturbances are not included per se. However, their rate is high. We aimed to describe our experience via the monitoring and treatment of such patients. METHODS: This was a retrospective analysis of patients in the setting of telemedicine-controlled HAH treatment. We collected data from the electronic medical records of patients who presented electrolyte disturbances. RESULTS: For 14 months, we treated 267 patients in total in HAH settings, with a mean age of 72.2 + 16.4, 44.2% for males. In total, 261 (97.75%) patients were flagged with electrolyte disturbances, of whom 149 had true electrolyte disturbances. Furthermore, 67 cases (44.96%) had hyponatremia, 9 (6.04%) had hypernatremia after correction for hyperglycemia, 20 (13.42%) had hypokalemia and 27 (18.12%) had hyperkalemia after the exclusion of hemolytic samples. Ten (6.09%) patients had hypocalcemia and two (1.34%) had hypercalcemia corrected to albumin levels. Thirteen (8.72%) patients had hypomagnesemia and one (0.67%) had hypermagnesemia. Patients with electrolyte disturbances suffered from more chronic kidney disease (24.2% vs. 12.2%; p = 0.03) and malignancy (6.3% vs. 0.6%; p = 0.006), and were more often treated with diuretics (12.6% vs. 4.1%; p = 0.016). No patient died or suffered from clinically significant cardiac arrhythmias. CONCLUSIONS: The extent of electrolyte disturbances amongst HAH treatment patients is high. The monitoring and treatment of such patients can be conducted safely in this setting.

Comparing Charlson Comorbidity Index Scores between Anesthesiologists, Patients, and Administrative Data: A Prospective Observational Study.

(1) Background: Patients' comorbidities play an immanent role in perioperative risk assessment. It is unknown how Charlson Comorbidity Indices (CCIs) from different sources compare. (2) Methods: In this prospective observational study, we compared the CCIs of patients derived from patients' self-reports and from physicians' assessments with hospital administrative data. (3) Results: The data of 1007 patients was analyzed. Agreement between the CCI from patients' self-report compared to administrative data was fair (kappa 0.24 [95%CI 0.2-0.28]). Agreement between physicians' assessment and the administrative data was also fair (kappa 0.28 [95%CI 0.25-0.31]). Physicians' assessment and patients' self-report had the best agreement (kappa 0.33 [95%CI 0.30-0.37]). The CCI calculated from the administrative data showed the best predictability for in-hospital mortality (AUROC 0.86 [95%CI 0.68-0.91]), followed by equally good prediction from physicians' assessment (AUROC 0.80 [95%CI 0.65-0.94]) and patients' self-report (AUROC 0.80 [95%CI 0.75-0.97]). (4) Conclusions: CCIs derived from patients' self-report, physicians' assessments, and administrative data perform equally well in predicting postoperative in-hospital mortality.

Acute Pancreatitis and Type 2 Diabetes Mellitus: The Chicken-Egg Paradox-A Seven-Year Experience of a Large Tertiary Center.

(1) Background: Preexisting type 2 diabetes mellitus (T2DM) has been shown in some studies as a risk factor and a severity factor for acute pancreatitis (AP). In this study, we aimed to demonstrate the link between T2DM and AP using data from a large retrospective epidemiological registry in a tertiary center. (2) Methods: We conducted a retrospective, large-cohort study of 1855 cases of AP and recurrent AP drawn from the seven-year consecutive hospitalization electronic health records of the largest acute-care tertiary teaching center in Romania. (3) Results: We observed a significant association between T2DM and a more severe course of the disease, and between T2DM and admission to the intensive care unit (ICU) due to AP, in our cohort using a chi-square test. However, we did not see a meaningful difference in comparing LoS-ICU between T2DM-AP and OAP (other known cause of AP). AP patients with T2DM had a greater probability of a severe course of the disease and were more likely to be admitted to the ICU than to the OAP. (4) Conclusions: The association between T2DM and AP remains a topic very representative of the "chicken-egg paradox". We need further research on DM-related AP and their bidirectional association as our study is limited by its retrospective design.