International Classification Of Disease Codes Research Articles

Estimated clinical utility of multi-gene pharmacogenetic testing in a retrospective cohort of gynecology patients.

This study aimed to estimate the clinical utility of performing multi-gene pharmacogenetic testing on patients undergoing gynecologic surgery/procedure by evaluating the prescribing rate of Clinical Pharmacogenetics Implementation Consortium (CPIC) level A medications and frequency of drug-gene interactions (DGIs). The electronic health record was queried for 76 current procedural terminology codes to identify gynecologic surgeries/procedures that occurred between 1 January 2015 to 31 December 2020 in patients with at least one of 152 international classification of disease codes. Prescription data for CPIC level A medications was extracted. Those enrolled in the Penn Medicine Biobank were assessed for DGIs. The cohort consisted of 7798 female patients and 682 were in the biobank. Up to 6 years following their surgery or procedure, 80% were ordered ≥1 CPIC level A medication. Over half (54%) of these medications were ordered within 3 days after their surgery or procedure. The most common CPIC level A medications ordered were ibuprofen (57%) and ondansetron (42%). Overall, 7% of the cohort had ≥1 known or predicted DGI with medications they were prescribed. Multi-gene pharmacogenetic testing may be beneficial to gynecologic surgery/procedure patients by assisting clinicians with prescribing postoperative analgesics and future medications.

Occurrence of stroke in children and young adults in Indonesia: a multicenter private hospital study.

Most studies that estimate the occurrence of childhood stroke use heterogeneous methods and rely on International Classification of Diseases codes, a strategy that may be unreliable. This study aimed to estimate the occurrence of childhood stroke in Indonesia using imaging and clinical data from a private hospital network. This cross-sectional study used consecutive retrospective multi-center data samples collected in 2019-2023. The study cohort included children aged >28 days to young adults aged 24 years with confirmed ischemic or hemorrhagic stroke on computed tomography (CT) or magnetic resonance imaging (MRI). The 1-year occurrence was calculated, and the data analysis was performed using SPSS version 26. Over 5 years, the performance of 8,987 CT and 6,133 MRI scans resulted in the identification of 1,074 stroke cases. The average patient age was 14.8 ± 7 years. Stroke occurrence was highest in 2021 (9.08%) and lowest in 2022 (5.91%). Male patients accounted for 67.9% of cases, with hemorrhagic strokes accounting for 83.4% of the total, primarily resulting from accidents (73.2%) and predominantly occurring in the frontal region (37.1%). A significant majority of cases (66.7%) were reported in Java. Males had a relative risk of 1.93 (95% confidence interval, 1.48-2.52; p < 0.0001) for hemorrhagic stroke versus females. The incidence of childhood stroke revealed critical epidemiological trends and disparities, emphasizing the need for targeted public health interventions and enhanced stroke prevention strategies in Indonesia.

Knowledge Aware Automated Health Claims Processing with Medical Ontologies and Large Language Models

One of the major challenges in automating health insurance claims processing lies in the complexity involved in validating an incoming claim's medical diagnoses against its policy Underwriting (UW) exclusions. Termed UW Exclusion Detection, this process ensures claims are only paid out if their diagnoses are not medically associated with conditions excluded under the policy. Medical diagnoses in health insurance claims are typically represented by the International Classification of Disease (ICD) codes, established by the World Health Organization. For example, given a policy that excludes "all respiratory illness". A claim with the ICD code J45 (Asthma) will be subject to rejection as J45 is a respiratory-related diagnosis that falls within the scope of the policy's UW exclusion. The key challenge in automating this process lies in the wide range of available ICD codes. The ICD-10-CM coding scheme consists of over 40,000 codes, which often results in scenarios where codes encountered during inference are absent from the training data. These unseen ICD codes limit the effectiveness of data-driven approaches, which depend on the training data to discern medically relevant associations between UW exclusions and ICD codes. This underscores the need to supplement data-driven approaches with additional domain knowledge. We hypothesize that integrating implicit medical domain knowledge inherent in Large Language Models (LLMs) with explicit domain knowledge from medical ontologies, will enhance data-driven approaches for UW Exclusion Detection. Thoroughly validated on real-world health insurance claims data, our proposed approach proved effective in accurately establishing medically relevant associations between UW exclusions and ICD codes.

REFINING THE DEFINITION OF MILIARY/DISSEMINATED TUBERCULOSIS IN CANADA

While a multi-site definition of disseminated tuberculosis (DTB) exists, there is limited evidence to support its use. Herein we sought to generate that evidence. We evaluated treatment outcomes and reporting requirements against two distinct definitions of DTB in a 15-year population-based cohort of consecutively-diagnosed TB patients in Canada. Definitions were combined in a multi-variable logistic regression to determine risk factors for TB-related death in DTB. We applied two mutually exclusive definitions of DTB to our dataset: 1. 'strict' - TB disease associated with a positive TB culture in blood/bone marrow or TB disease associated with a miliary pattern on chest imaging and a positive TB culture or, 2. 'multisite' - TB disease in two or more non-contiguous sites. Among 2877 notified TB patients, 110 (3.8%) met the 'strict' definition, while 168 (5.8%) met the 'multisite' definition. Of all 278 DTB patients only 135 (48.6%) were notified as DTB using International Classification of Disease codes, and only 66 (23.7%) were classified as DTB by Canada's Public Health Agency. DTB patients, by either definition, were less likely to achieve cure/treatment completion and more likely to die. Risk factors for a fatal outcome included extremes of age, Canadian birth, central nervous system involvement, and HIV co-infection. Our findings support the combination of both a strict and multisite definition of DTB for purposes of reporting consistency and investigational comparability.

Validating International Classification of Diseases Code 10th Revision algorithms for accurate identification of pulmonary embolism

BackgroundMany research investigations for pulmonary embolism (PE) rely on the International Classification of Diseases 10th Revision (ICD-10) codes for analyses of electronic databases. The validity of ICD-10 codes in identifying PE remains uncertain. MethodsUsing a prespecified protocol, patients in the Mass General-Brigham hospitals (2016-2021) with ICD-10 principal discharge codes for PE, those with secondary codes for PE, and those without PE codes were identified (n = 578 from each group). Weighting was applied to represent each group proportionate to their true prevalence. The accuracy of ICD-10 codes for identifying PE was compared with adjudication by independent physicians. The F1 score, which incorporates sensitivity and positive predictive value (PPV), was assessed. Subset validation was performed at Yale-New Haven Health System. ResultsA total of 1712 patients were included (age: 60.6 years; 52.3% female). ICD-10 PE codes in the principal discharge position had sensitivity and PPV of 58.3% and 92.1%, respectively. Adding secondary discharge codes to the principal discharge codes improved the sensitivity to 83.2%, but the PPV was reduced to 79.1%. Using a combination of ICD-10 PE principal discharge codes or secondary codes plus imaging codes for PE led to sensitivity and PPV of 81.6% and 84.7%, respectively, and the highest F1 score (83.1%; P < .001 compared with other methods). Validation yielded largely similar results. ConclusionAlthough the principal discharge codes for PE show excellent PPV, they miss 40% of acute PEs. A combination of principal discharge codes and secondary codes plus PE imaging codes led to improved sensitivity without severe reduction in PPV.

Rates of buprenorphine prescribing and racial disparities among patients with opioid overdose

BackgroundAwareness of the relationship between real-world buprenorphine prescribing and overdose frequency is limited, especially in the Southeastern United States. We described buprenorphine prescribing rates for patients experiencing nonfatal opioid overdoses in the context of overdose frequency. MethodsElectronic medical records review was conducted at an urban, academic hospital in Alabama from January 1 through December 31, 2021. Patients with opioid use disorder (OUD) and nonfatal opioid overdoses, dispositioned from either the emergency department (ED), inpatient, or outpatient affiliated clinics, were identified by International Classification of Diseases-10 codes. ResultsThe study included 358 unique patients. Many patients were white (71.5%), male (59.2%), and uninsured (54.2%), with a mean age of 42.0±12.8 years. The majority (85.5%) experienced one to three overdoses, and 14.5% of patients had more than three overdoses. The buprenorphine prescription rate increased to 55.8% when patients had more than three overdoses, compared to one overdose (34.5%) and two to three overdoses (37.4%) (p=0.025). Compared to females, more males overdosed more than once (p=0.004). Black patients were less likely to receive buprenorphine prescriptions than white patients (27.3% vs. 44.5%, p=0.004). Compared to patients with multiple overdoses, more patients with one overdose had public insurance (p=0.028) and were less likely to present to the ED (p<0.001). ConclusionUnder-prescribing of buprenorphine is high among patients with OUD and opioid overdoses, even in patients with multiple overdoses, and there appear to be racial disparities in prescribing. Our findings indicate clinical opportunities for improving buprenorphine prescribing and reducing the current disparities.

Association Between Congenital Heart Disease-Related Diagnosis Codes and Trauma Surgery Outcomes.

Congenital heart disease (CHD) is one the most common congenital anomalies, with a prevalence of 8-10 cases per 1000 live births in the United States. Congenital heart disease has been recognized as a risk factor for poor perioperative and postoperative outcomes in non-cardiac surgery. We aimed to determine if documentation of CHD-related diagnosis codes was associated with similar risks for trauma surgery. Data were acquired from the 2010-2019 American College of Surgeons' Trauma Quality Programs Participant Use Files. This study included trauma patients of all ages with one or more surgical procedures and at least one documented non-trauma (comorbidity) International Classification of Diseases code. Patients were stratified based on presence of CHD-related comorbidity codes vs any other comorbidity. Outcomes included mortality, hospital length of stay (LOS), discharge disposition, and in-hospital complications. Using 1:1 propensity score matching, we matched 215 cases with CHD-related comorbid diagnoses to non-CHD controls. Compared to patients with other comorbidities, patients with CHD-related comorbidites were less likely to be discharged home to self-care (odds ratio: 0.44, 95% confidence interval [CI]: 0.25, 078 P = .005) and tended to have prolonged hospital LOS (incidence rate ratio [IRR]: 1.06, 95% CI: 1.001, 1.13, P = .046). We present the first quantitative multicenter analysis correlating documentation of comorbid CHD-related diagnoses with higher risk of adverse outcomes after trauma surgery. These results support the need to routinely acknowledge and document CHD as comorbidity in trauma admissions that could lead to surgical intervention and for trauma centers to prepare for patients with a possible CHD comorbidity.

Quantifying Plastic and Reconstructive Surgery Engagement in the Evolution of ICD-10 Codes.

International Classification of Diseases (ICD)-10 code specificity is important for detailed diagnostic documentation. Insufficient coding granularity in plastic surgery may hinder accurate clinical documentation, impacting education, research, and patient care. This study examines ICD-10 code modification efforts by plastic surgeons and plastic surgery organizations within the last decade, subsequently detailing the formal proposal process and highlighting potential areas where coding modifications may be explored. A retrospective review of all modification proposals presented to the ICD Coordination and Maintenance Committee from March 2013 to March 2023 was conducted. Plastic surgery-related proposals were identified and evaluated for successful implementation. These results were compared to those of other specialties using Fisher exact tests and 2-tailed t tests. A total of 472 unique proposals were identified and reviewed. Surgeons and/or surgical organizations contributed to 111 (23.5%) novel proposals, 41 (36.9%) of which were initiated by surgeons. Nine surgical specialties and 14 supporting organizations were represented. The success rate for all surgical-related proposals was 85.6%, with an average time to implementation of 24.7 months. Only 2 (1.8%) of all surgical-related proposals pertained to plastic surgery, both of which were successfully implemented. Though a few plastic surgeons have taken advantage of the ICD code revision process within the last decade, the high overall success rate for surgical-related proposals suggests that this seems to be a feasible method by which plastic surgeons and plastic surgery organizations can bring about useful coding changes that meaningfully impact clinical practice.

Insights into the aetiology and temporal trends in cardiac mortality in the young: a 21-year review of national and registry data in the united kingdom

Abstract Background An accurate representation of the incidence and aetiology of cardiac and sudden cardiac death (SCD) is vital for healthcare policymakers to effectively allocate resources for preventative strategies. Purpose We aimed to report on the incidence and causes of cardiac and SCD among individuals under 35-years-old in England and Wales for 21 years (2001-2021), with a focus on identifying any temporal trends. Methods Annual mortality data from the Office for National Statistics (ONS) pertaining to cardiovascular (CV) and possible CV deaths in individuals under 35-years-old were analyzed using International Classification of Diseases-10 codes. Deaths were categorized into four-classes: A1- definitive cardiac deaths without identifiable structural heart disease (consistent with sudden arrhythmic death syndrome, SADS); A2- definitive cardiac deaths with identified structural heart disease; A3- definitive cardiac deaths with indeterminate cause; and B- potential cardiac deaths. Incidence rates were computed based on annual ONS census data. Additionally, insights were gleaned from the Cardiac Risk in the Young Centre for Cardiac Pathology (CRYCCP) nationwide registry. Results The mean annual number of definitive cardiac deaths (classes A1+A2+A3) was 414 (SD 27.4), resulting in an incidence of young cardiac and SCD of 1.68/100,000 individuals/year. Ischaemic heart disease (28.4%), cardiomyopathies (25.9%), and SADS (21.8%) were the most prevalent cardiac conditions. Cardiomyopathies and SADS related mortality peaked in the 10-to-19 age group, while ischaemic heart disease peaked in the 30-to-35 age group. A mean of 573 (SD 76.6) possible cardiac deaths (class B) occurred, these primarily included ill-defined causes (33.5%), epilepsy (32.4%), sudden infant death syndrome (24.2%), and drowning (7%). Definitive and possible cardiac deaths showed a male preponderance (male to female ratios: 2.3:1 and 1.6:1, respectively). A declining trend in cardiac mortality was observed with a 1.3% (95%CI: 1.0%-1.7%) incidence rate reduction/year (p&amp;lt;0.001). This was associated with a 2.5% annual incidence rate reduction for deaths attributed to structural heart disease (p&amp;lt;0.001), but an 8.5% annual incidence rate increase for deaths attributed to SADS (p&amp;lt;0.001). These trends corelated with increasing numbers of deaths referred to the CRYCCP where an expert cardiac pathologist diagnosed SADS in over 52% of cases. Conclusions Over 21 years in England and Wales, national datasets suggest the incidence of young cardiac and SCD is 1.68/100,000/year, with a small but appreciable declining mortality trend. The rise in SADS rates and contemporaneous decline in deaths attributed to structural heart disease may signify increased awareness and accessibility to expert cardiac pathologists. Ensuring accurate mortality coding is crucial for thoroughly assessing first-degree family members in cases of suspected inherited cardiac conditions.

Health impact of the Serious Accidents Punishment Act in Korean occupational settings

Abstract Background Interrupted time series analysis serves as a valuable study design for assessing the efficacy of public health interventions implemented at a specific moment in time at the population level. We aim to elucidate the effects of the Serious Accidents Punishment Act implemented in February 2021 in Korea by analyzing changes in the incidence rates of occupational diseases. Methods The monthly data from patients with occupational diseases was extracted from the National Health Insurance Service Cohort database from 2011 to 2023. An Interrupted time series analysis with Poisson segmented regression was used to compare the rates before and after the Serious Accidents Punishment Act introduction in both outpatients and inpatients. Adjustments or stratification variables included sex, age, company size, and injury-related international classification of diseases codes (Injury, poisoning, and certain other consequences of external causes, S00-T88). Results Based on injury rates, men’s inpatient injury rates remained stable, but outpatient rates decreased after the act implementation, while women’s injury rates consistently declined in both inpatient and outpatient settings. The Interrupted time series regression analysis indicates that the Serious Accidents Punishment Act led to a significant reduction in both outpatient and inpatient injury rates for men and women, with a marked decline in outpatient rates and hospital admissions among women post-intervention. Conclusions The Interrupted time series regression results suggest that the Serious Accidents Punishment Act has been effective in reducing injury-related healthcare usage, highlighting the necessity of gender-specific interventions and the potential impact on lowering inpatient visits, although causality remains uncertain without further analysis. Key messages • The Serious Accidents Punishment Act significantly reduced occupational injury rates in Korea, especially among women, demonstrating effective public health intervention. • Interrupted time series analysis reveals Serious Accidents Punishment Act’s impact on reducing healthcare usage for occupational injuries, highlighting the need for gender-specific approaches.

Twenty-year trends in excess costs of chronic obstructive pulmonary disease.

Several major risk factors for chronic obstructive pulmonary disease (COPD), such as population aging, smoking rates, and air pollution levels are rapidly changing, causing inevitable changes in the population burden of COPD. We determined the excess direct costs of COPD and their trend from 2001 to 2020. Using administrative health data from British Columbia, Canada, we created a retrospective matched cohort of physician-diagnosed COPD patients and non-COPD individuals. Excess direct medical costs (2020 $CAD) were estimated by analysing hospital records, outpatient services, medications, and community-care services. Comorbidity classes were assessed using the International Classification of Diseases codes. Excess COPD costs were estimated as the adjusted difference in direct medical costs between COPD and non-COPD cohorts. There were 208 554 and 404 703 individuals in the COPD and non-COPD cohorts, respectively (47.8% female; mean baseline age 69.1 and 68.2 years, respectively). Direct medical costs for COPD were $9224 per patient-year (/PY), compared to $3396/PY for non-COPD, giving rise to excess costs of $5828/PY (95% confidence interval [CI] 5759-5897). Excess costs increased by 48% over the study period. Excess costs due to comorbidities were $3588/PY (95% CI 3554-3622), with cardiovascular-related conditions alone exceeding the costs attributed to COPD ($1375/PY versus $904/PY). Despite multifaceted prevention and management initiatives, COPD-related economic burden is increasing, with the majority of costs due to comorbid conditions. Rising per-patient costs, combined with the flat or increasing prevalence of COPD in many jurisdictions, indicates a significant increase in COPD burden.

Validation Study of the Claims-Based Algorithm Using the International Classification of Diseases Codes to Identify Patients With Coronavirus Disease in Japan From 2020 to 2022: The VENUS Study.

We validated claims-based algorithms using the International Classification of Diseases, Tenth Revision (ICD-10) to identify patients with the first-ever coronavirus disease (COVID-19) onset between May 2020 and August 2022. The study cohort was comprised of residents of one municipality enrolled in a public insurance program. This study used data provided by the municipality, including residents' insurer-based medical claims data linked to the Health Center Real-time Information-Sharing System (HER-SYS). The HER-SYS data included positive results from COVID-19 tests and were used as reference standards. Claims-based algorithms #1 and #2 were U07.1, B34.2, with and without suspicious diagnoses, respectively. Claims-based algorithms #3 and #4 were U07.1 with and without suspicious diagnoses, respectively. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each algorithm. The study cohort included 165 038 residents, including 13 402 residents were the reference standard. For the entire period, the sensitivity, specificity, PPV, and NPV were 55.7% (95% confidence interval: 54.8%-56.5%), 65.4% (65.2%-65.6%), 11.5% (11.3%-11.8%), and 98.9% (98.8%-99.0%) for Algorithm #1, and 67.0% (66.2%-67.8%), 88.1% (87.9%-88.3%), 31.6% (31.1%-32.2%), and 97.8% (97.7%-97.8%) for Algorithm #2, and 52.9% (52.0%-53.7%), 67.1% (66.9%-67.3%), 11.5% (11.2%-11.8%), and 98.3% (98.3%-98.4%) for Algorithm #3, 62.6% (61.8%-63.4%), 88.5% (88.3%-88.7%), 30.9% (30.3%-31.4%), and 97.3% (97.2%-97.4%) for Algorithm #4, respectively. Our study showed that the validity of claims-based algorithms consisting of COVID-19-related ICD-10 codes to identify patients with first-onset COVID-19 is limited.

Antepartum risk factors and outcomes of massive transfusion for elective cesarean section: a nationwide retrospective cohort study

BackgroundPostpartum hemorrhage is one of the leading causes of maternal mortality and morbidity. The etiology of postpartum hemorrhage exhibits variations in relation to the mode of birth; consequently, risk factors for massive transfusion in elective cesarean section might diverge from those encountered in vaginal birth or emergency cesarean section. The main purpose of this study was to investigate antepartum risk factors of massive transfusion for elective cesarean section.MethodsWe conducted a retrospective cohort study based on data from a nationwide system that collected inpatient medical records from tertiary hospitals in mainland China. We included women who had undergone elective cesarean section from January 2013 to August 2018. Primary outcome was massive transfusion defined as transfusion of more than eight units of red blood cells on the day of childbirth. Candidate risk factors were identified by the 10th revision of International Classification of Diseases Codes of admission diagnoses. The relationship between each factor and massive transfusion was assessed using multivariable logistic regression.ResultsA total of 294,695 women were included and 572 of them received massive transfusion (incidence: 194 per 100,000 elective cesarean sections). Maternal age [adjusted odds ratio (aOR) 1.22; 95% confidence interval (CI) 1.10–1.48], anemia (aOR 1.66; 95% CI 1.34–2.05), thrombocytopenia (aOR 3.54; 95% CI 2.39–5.05), coagulopathy (aOR 25.92; 95% CI 8.59–69.50), hypoalbuminemia (aOR 2.97; 95% CI 1.86–4.53), hepatic dysfunction (aOR 1.65; 95% CI 1.04–2.47), uterine scar (aOR 1.39; 95% CI 1.15–1.67), multiple pregnancy (aOR 2.84; 95% CI 1.74–4.38), polyhydramnios (aOR 2.52; 95% CI 1.19–4.68) and placenta previa (aOR 25.03; 95% CI 21.04–29.77) were associated with massive blood transfusion for elective cesarean section. Among the women receiving massive blood transfusion, 7 (1.2%) died during hospitalization, 126 (22.0%) needed hysterectomy, 25 (4.4%) uterine packing and 57 (10.0%) uterine artery ligation.ConclusionsTen risk factors of massive transfusion were identified in women undergoing elective cesarean section. Our findings may facilitate blood products preparation and provide opportunities for applying prophylactic strategies prior to cesarean section for women at high risk of massive transfusion.

Development and Validation of a Diagnostic Algorithm for Down Syndrome Using Birth Certificate and International Classification of Diseases Codes.

We aimed to develop an algorithm that accurately identifies children with Down syndrome (DS) using administrative data. We identified a cohort of children born between 2000 and 2017, enrolled in the Tennessee Medicaid Program (TennCare), who either had DS coded on their birth certificate or had a diagnosis listed using an International Classification of Diseases (ICD) code (suspected DS), and who received care at Vanderbilt University Medical Center, a comprehensive academic medical center, in the United States. Children with suspected DS were defined as having DS if they had (a) karyotype-confirmed DS indicated on their birth certificate; (b) karyotype-pending DS indicated on their birth certificate (or just DS if test type was not specified) and at least two healthcare encounters for DS during the first 6 years of life; or (c) at least three healthcare encounters for DS, with the first and last encounter separated by at least 30 days, during the first six years of life. The positive predictive value (PPV) of the algorithm and 95% confidence interval (CI) were reported. Of the 411 children with suspected DS, 354 (86.1%) were defined as having DS by the algorithm. According to medical chart review, the algorithm correctly identified 347 children with DS (PPV = 98%, 95%CI: 96.0-99.0%). Of the 57 children the algorithm defined as not having DS, 50 (97.7%, 95%CI: 76.8-93.9%) were confirmed as not having DS by medical chart review. An algorithm that accurately identifies individuals with DS using birth certificate data and/or ICD codes provides a valuable tool to study DS using administrative data.

Polycystic ovary syndrome underdiagnosis patterns by individual-level and spatial social vulnerability measures.

To use electronic health records (EHR) data at Boston Medical Center (BMC) to identify individual-level and spatial predictors of missed diagnosis, among those who meet diagnostic criteria for PCOS. The BMC Clinical Data Warehouse was used to source patients who presented between October 1, 2003 and September 30, 2015 for any of the following: androgen blood tests, hirsutism, evaluation of menstrual regularity, pelvic ultrasound for any reason, or PCOS. Algorithm PCOS cases were identified as those with International Classification of disease (ICD) codes for irregular menstruation and either an ICD code for hirsutism, elevated testosterone lab, or polycystic ovarian morphology as identified using natural language processing on pelvic ultrasounds. Logistic regression models were used to estimate odds ratios (ORs) of missed PCOS diagnosis by age, race/ethnicity, education, primary language, body mass index (BMI), insurance type and social vulnerability index (SVI) score. In the 2003-2015 BMC-EHR PCOS at-risk cohort (n=23,786), there were 1,199 physician-diagnosed PCOS cases and 730 algorithm PCOS cases. In logistic regression models controlling for age, year, education, and SVI scores, Black/African American patients were more likely to have missed a PCOS diagnosis (OR = 1.69 [95% CI, 1.28, 2.24]) compared to non-Hispanic White patients, and relying on Medicaid or charity for insurance was associated with an increased odds of missed diagnosis when compared to private insurance (OR = 1.90 [95% CI, 1.47, 2.46], OR = 1.90 [95% CI, 1.41, 2.56], respectively). Higher SVI scores were associated with increased odds of missed diagnosis in univariate models. We observed individual-level and spatial disparities within the PCOS diagnosis. Further research should explore drivers of disparities for earlier intervention.

ACUTE PANCREATITIS IN AKMOLA REGION ACCORDING TO EMERGENCY SURGERY

Background: Acute pancreatitis is a major issue in surgical practice, with high complications and mortality rates. It severely affects patient quality of life and places a significant economic strain on healthcare systems, making its study crucial for public health. This study aims to analyze trends in acute pancreatitis incidence in the Akmola region from 2009 to 2022. Materials and methods: The study is based on a retrospective analysis of data from the Ministry of Health of the Republic of Kazakhstan according to the International Classification of Diseases-10 code: K85. Methods of health statistics and time series analysis were used to assess the dynamics of morbidity. Results: There was an increase in the total number of hospitalizations from 865 cases in 2009 to 1.061 in 2022. The percentage of surgical interventions decreased from 5.7% to 4.2%, while the share of conservative treatment increased to 95.8%. The mortality rate among operated patients was 20.4% in 2019 and increased to 33.3% in 2022. The incidence of hospitalization increased from 117.1 per 100000 population in 2009 to 144.6 per 100000 population in 2022, with a decrease in the rate of late visits from 42.6 to 36.1 per 100000 population, respectively. Conclusion: It has been established that for patients in the second group according to the Enhanced Recovery After Surgery strategy, hemodynamic support and effective pain management can contribute to early patient mobilization after surgery. Early mobilization, in turn, can expedite recovery and reduce the length of hospital stay, ultimately leading to potential cost savings. Conclusion. The study highlights the need to improve medical approaches to acute pancreatitis in the Akmola region. The results indicate the critical importance of early diagnosis and timely hospitalization to reduce complications and mortality. Additional research is needed to develop more effective clinical protocols.

Atrial flutter and sick sinus syndrome

BackgroundSick sinus syndrome (SSS) is a common condition resulting in reduced quality of life, syncope, and permanent pacemaker (PPM) implantation, but predictors have not been elucidated. Whereas atrial arrhythmias are frequently associated with SSS, we hypothesized that atrial flutter (AFL) would strongly predict SSS, given shared relationships with right atrial and particularly crista terminalis fibrosis. ObjectiveThe study aimed to assess the impact of AFL on the occurrence of SSS and associated syncope and PPM implantation. MethodsHealth care databases were used to identify adults aged ≥18 years receiving hospital-based care in California in 2005–2019. International Classification of Diseases codes were used to identify diagnoses and procedures. Patients were classified on the basis of the presence of AFL and atrial fibrillation (AF). Cox proportional hazards models adjusting for demographics and comorbidities were employed. ResultsWe included 29,357,609 individuals (54% female; mean age, 46 years), 101,243 with AFL alone, 1,674,680 with AF alone, and 284,547 with AF and AFL. After adjustment for age, sex, race and ethnicity, and comorbidities, AF, AFL, and both arrhythmias were each associated with increased risk of SSS and associated syncope and PPM implantation (all P < .001). In the population with AF, an additional AFL diagnosis conferred a higher risk for development of SSS (hazard ratio [HR],1.62; 95% confidence interval, 1.59–1.64), syncope (HR, 1.63; 1.54–1.72), and PPM implantation (HR, 1.74; 1.70–1.79). ConclusionAFL is associated with an increased risk of incident SSS and its adverse consequences, especially in patients with coexisting AF. AFL may be useful for risk stratification strategies to predict, to prevent, and to treat SSS.

PheW2P2V: a phenome-wide prediction framework with weighted patient representations using electronic health records.

Electronic health records (EHRs) provide opportunities for the development of computable predictive tools. Conventional machine learning methods and deep learning methods have been widely used for this task, with the approach of usually designing one tool for one clinical outcome. Here we developed PheW2P2V, a Phenome-Wide prediction framework using Weighted Patient Vectors. PheW2P2V conducts tailored predictions for phenome-wide phenotypes using numeric representations of patients' past medical records weighted based on their similarities with individual phenotypes. PheW2P2V defines clinical disease phenotypes using Phecode mapping based on International Classification of Disease codes, which reduces redundancy and case-control misclassification in real-life EHR datasets. Through upweighting medical records of patients that are more relevant to a phenotype of interest in calculating patient vectors, PheW2P2V achieves tailored incidence risk prediction of a phenotype. The calculation of weighted patient vectors is computationally efficient, and the weighting mechanism ensures tailored predictions across the phenome. We evaluated prediction performance of PheW2P2V and baseline methods with simulation studies and clinical applications using the MIMIC-III database. Across 942 phenome-wide predictions using the MIMIC-III database, PheW2P2V has median area under the receiver operating characteristic curve (AUC-ROC) 0.74 (baseline methods have values ≤0.72), median max F1-score 0.20 (baseline methods have values ≤0.19), and median area under the precision-recall curve (AUC-PR) 0.10 (baseline methods have values ≤0.10). PheW2P2V can predict phenotypes efficiently by using medical concept embeddings and upweighting relevant past medical histories. By leveraging both labeled and unlabeled data, PheW2P2V reduces overfitting and improves predictions for rare phenotypes, making it a useful screening tool for early diagnosis of high-risk conditions, though further research is needed to assess the transferability of embeddings across different databases. PheW2P2V is fast, flexible, and has superior prediction performance for many clinical disease phenotypes across the phenome of the MIMIC-III database compared to that of several popular baseline methods.

Identifying Patients With Primary Biliary Cholangitis and Cirrhosis Using Administrative Data in a National Cohort.

The accuracy of administrative codes to capture patients with both primary biliary cholangitis (PBC) and cirrhosis could be challenging because of the potential for incorrect coding due to the old nomenclature "Primary Biliary Cirrhosis." Therefore, the aim of this study was to examine the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for PBC and cirrhosis. This was a retrospective cohort study using data from the VA Corporate Data Warehouse. Eligibility criteria included adult patients diagnosed to have PBC and cirrhosis based on one inpatient or two outpatient ICD 9 or 10 codes, and were validated against chart review of each participant. We identified 1408 patients who were found to have ICD codes for both cirrhosis and PBC. The ICD 9/10 codes for PBC and cirrhosis had a PPV of 0.75 (95% CI 0.73-0.75) for cirrhosis, 0.75 for PBC (95% CI 0.73-0.78), and 0.52 (0.50-0.55) for PBC and cirrhosis. When portal hypertension was combined with ICD 9/10 codes, the PPV of cirrhosis improved to 0.92 (0.90-0.94), and that of PBC cirrhosis improved to 0.64 (0.60-0.67). By combining ICD 9/10 codes for portal hypertension and receipt of ursodeoxycholic acid (UDCA), the PPV for cirrhosis improved to 0.91 (0.88-0.94), PBC increased to 0.78 (0.74-0.82), and that for PBC cirrhosis to 0.69 (0.65-0.74). In a large national cohort, the use of ICD 9/10 codes had modest reliability for identifying participants with PBC and cirrhosis. The PPV for cirrhosis can be improved by incorporating ICD 9/10 codes for portal hypertension with receipt of UDCA.

Association Between Admission Systolic Blood Pressure and Outcomes in Patients with Isolated Traumatic Brain Injury: A Cross-National Multicenter Cohort Study.

The optimal prehospital blood pressure in patients following traumatic brain injury (TBI) remains controversial. We aimed to assess the association between the systolic blood pressure (SBP) at emergency department triage and patient outcomes following isolated moderate-to-severe TBI. We conducted a cross-national multicenter retrospective cohort study using the Pan-Asia Trauma Outcomes Study database from January 1, 2016, to November 30, 2018. The enrollees were adult patients with isolated moderate-to-severe TBI defined by the International Classification of Diseases code, a Glasgow Coma Scale (GCS) <13 at triage, and a nonhead Abbreviated Injury Scale ≤3. The studied variables were SBPs at triage categorized into different ranges. The primary outcome was 30-day mortality, and the secondary outcome was poor functional status at hospital discharge defined by the modified Rankin Scale ≥4. Multivariable logistic regression was applied to adjust for confounders including country, sex, age, mechanism of injury, prehospital vascular access, respiratory rate, GCS, oxygen saturation, intubation, Injury Severity Score, head surgery, intensive care unit admission, and length of hospital stay. Subgroup analyses were performed on different severity of TBI. A total of 785 patients (median age, 42 years; male patients 77.5%; mean SBP at triage, 136.3 ± 33.1 mmHg) were included in the primary analysis. The lowest 30-day mortality rate existed in patients with SBP of 100-119 mmHg. Taking it as baseline, the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) of SBP <100 mmHg, 120-139 mmHg, 140-159 mmHg, and ≥160 mmHg were 7.05 (2.51-19.78), 3.14 (1.14-8.65), 2.91 (1.04-8.17), and 3.28 (1.14-9.42). As for the secondary outcome, the aORs and 95% CIs were 1.36 (0.68-2.68) of <100 mmHg, 0.99 (0.57-1.70) of 120-139 mmHg, 1.23 (0.67-2.25) of 140-159 mmHg, and 1.52 (0.78-2.95) of ≥160 mmHg. Subgroup analyses revealed trends of the best outcomes in both moderate and severe TBI patients with SBP 100-119 mmHg, whereas statistical significance appeared only in patients with severe TBI. SBP of 110-119 mmHg at triage is associated with the lowest 30-day mortality in patients following isolated moderate-to-severe TBI and possibly related to a better functional outcome.