Principal Diagnosis Research Articles

The impact of obesity on ventilator-associated pneumonia, a US nationwide study

BackgroundVentilator-associated pneumonia (VAP) is one of the leading causes of mortality in patients with critical care illness. Since obesity is highly prevalent, we wanted to study its impact on the outcomes of patients who develop VAP.MethodsUsing the National Inpatient Sample (NIS) database from 2017 to 2020, we conducted a retrospective study of adult patients with a principal diagnosis of VAP with a secondary diagnosis with or without obesity according to 10th revision of the International Statistical Classification of Diseases (ICD-10) codes. Several demographics, including age, race, and gender, were analyzed. The primary endpoint was mortality, while the secondary endpoints included tracheostomy, length of stay in days, and patient charge in dollars. Multivariate logistic regression model analysis was used to adjust for confounders, with a p-value less than 0.05 considered statistically significant.ResultsThe study included 3832 patients with VAP, 395 of whom had obesity. The mean age in both groups was around 58 years, and 68% of the group with obesity were females compared to 40% in females in the group without obesity. Statistically significant comorbidities in the obesity group included a Charlson Comorbidity Index score of three and above, diabetes mellitus, hypertension, chronic kidney disease, and sleep apnea. Rates and odds of mortality were not significantly higher in the collective obesity group 39 (10%) vs. 336 (8.5%), p-value 0.62, adjusted odds ratio 1.2, p-value 0.61). The rates and odds of tracheostomy were higher in the obesity group but not statistically significant. Obese patients were also found to have a longer hospitalization. Upon subanalysis of the data, no evidence of racial disparities was found in the care of VAP for both the obese and control groups.ConclusionsObesity was not found to be an independent risk factor for worse outcomes in patients who develop VAP in the intensive care unit.

The variation in preventable hospitalization in patients with type 2 diabetes in Kentucky before and after the Medicaid expansion.

Hospitalizations are more resource intensive and expensive than outpatient care. Therefore, type 2 diabetes-related preventable hospitalization are a major topic of research efficiency in the healthcare system. Analyze county level variation in type 2 diabetes-related preventable hospitalization rates in Kentucky before the Medicaid expansion (2010-2013) and after the Medicaid expansion (2014-2017). Geographic mapping and cluster analysis. Data for a state of the United States of America. We used the KID data to generate geographic mapping for type 2 diabetes-related preventable hospitalizations to visualize rates. We included all Kentucky discharges of age 18 years and older with the ICD9/10 principal diagnosis code for type 2 diabetes. Then, we conducted cluster analysis techniques to compare county-level variation in type 2 diabetes-related preventable hospitalization rates across Kentucky counties pre- and post-Medicaid expansion. County type 2 diabetes-related preventable hospitalization pre- and post-Medicaid expansion. From 2010-2017, type 2 diabetes-related preventable hospitalization discharge rates reduced significantly in the period of the post-Medicaid expansion (P=.001). The spatial statistics analysis revealed a significant spatial clustering of counties with similar rates of type 2 diabetes-related preventable hospitalization in the south, east, and southeastern Kentucky pre- and post-Medicaid expansion (positive z-score and positive Moran's Index value (P>.05). Also, there was a significant clustering of counties with low type 2 diabetes-related preventable hospitalization rates in the north, west, and central regions of the state pre-Medicaid expansion and post-Medicaid expansion (positive z-score and positive Moran's Index value (P>.05). Kentucky counties in the southeast have experienced a significant clustering of highly avoidable hospitalization rates during both periods. Focusing on the vulnerable counties and the economic inequality in Kentucky could lead to efforts to lowering future type 2 diabetes-related preventable hospitalization rates. We used de-identified data which does not provide insights into the frequency of hospitalizations per patient. An individual patient may be hospitalized several times and counted as several individuals.

Do they stay, or do they go? Children presenting to five emergency departments across New South Wales, Australia with acute burn injuries: a retrospective review

ObjectiveThe overall objective of the study was to describe the disposition status of children presenting with a burn injury to five emergency departments (ED) across New South Wales (NSW), Australia.DesignA...

Association between age-related macular degeneration and risk of incident cancer

Background/aimsAge-related macular degeneration (AMD) and cancer may share similar risk factors, indicating possible common pathogenic pathways. We aimed to describe the site-specific cancer risk based on the relationship of AMD...

Factors Affecting Mortality and Distribution of Co-morbidities in Chronic Obstructive Pulmonary Disease

Objectives: Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide. This study aims to identify the rules associated with major comorbidities in patients with COPD and analyze how they affect death, thereby suggesting patient management measures that are efficient and can improve the quality of medical care.Methods: For this purpose, among the Korea Disease Control and Prevention Agency’s discharge injury in-depth survey data of more than 3 million cases from 2006 to 2021, adult patients aged 19 years or older with a principal diagnosis of chronic obstructive pulmonary disease were targeted. <i>χ</i><sup>2</sup>-test and independent sample t-test were performed to analyze the distribution of deaths by demographic characteristics, and ARM (Association Rule Mining) was analyzed for association rules for comorbidities. Logistic regression analysis was performed on factors influencing death.Results: As a result of the analysis, the mortality rate was high in patients over 75 years of age, patients admitted to the emergency room, and patients discharged from medical institutions with more than 1,000 beds. The prevalence of comorbidities was high for E11 (Type 2 diabetes mellitus) and I10 (essential hypertension). As a result of analyzing the impact on death based on major association rules, other sepsis (A41) and essential hypertension (I10), other sepsis (A41) and pneumonia, organism unspecified (J18), sequelae of tuberculosis (B90) and J96 (respiratory Failure, NEC), sequelae of tuberculosis (B90), and I27 (other pulmonary heart diseases) were found to have a high probability of death.Conclusions: Based on the major association rules affecting death, we propose to apply them to a clinical decision support system for efficient patient management and personalized treatment.

дилатационной кардиомиопатией Клинический случай медицинской реабилитации пациента с дилатационной кардиомиопатией

The paper provides a clinical case of physical and medical rehabilitation of patient D born in 1963. Principal diagnosis established in 2018 according to ICD-10: I42.0 dilated cardiomyopathy. Laboratory testing revealed DNA of herpes virus 6 (HHV6), positive test for cytomegalovirus (CMV) DNA, 6.0×102 copies/mL, positive test for the Epstein–Barr virus (EBV) DNA, 7.2×103 copies/mL. In April 2018, the patient underwent successful surgery, implantation of the biventricular bypass system supplemented by membrane oxygenation. Physical rehabilitation was performed that yielded positive results.

The association between high mobility group box 1 (HMGB1) and Interleukin-18 (IL-18) serum concentrations in COVID-19 inpatients

BackgroundHigh mobility group box 1 (HMGB1) and interleukin-18 (IL-18) are involved in various non-coronavirus disease pathogenesis and are reported as potential biomarkers for coronavirus disease (COVID-19). However, their association with COVID-19 pathogenesis has not yet been explored. AimThis study aimed to investigate the association between HMGB1 and IL-18 concentrations in the sera of COVID-19 patients versus non-COVID-19 patients. Material and methodsWe used stored serum samples obtained from 30 COVID-19 patients and 30 non-COVID-19 patients. We collected data on age, gender, treatment status, principal diagnosis, and comorbidity from patient medical records. HMGB1 and IL-18 concentrations were analyzed in the serum by enzyme-linked immunosorbent assay (ELISA). The swab samples’ RT-PCR cycle threshold (CT) values were obtained from the laboratory database. ResultsHMGB1 concentrations were increased in the COVID-19 inpatients and non-COVID-19 inpatients compared to non-COVID-19 outpatients (COVID-19 inpatients vs. non-COVID-19 outpatients: 151.33 (90.27–192.38) vs. 80.75 (54.16–128.72) ng/ml; p = 0.0316; non-COVID-19 inpatients vs. non-COVID-19 outpatients: 152.66 (104.04–288.51) vs. 80.75 (54.16–128.72) ng/ml; p = 0.0199). IL-18 concentrations were also higher in the COVID-19 inpatients and non-COVID-19 inpatients compared to non-COVID-19 outpatients (COVID-19 inpatients vs. non-COVID-19 outpatients: 620.00 (461.50–849.6) vs. 403.10 (372.70–556.90) pg/ml; p = 0.0376; non-COVID-19 inpatients vs. non-COVID-19 outpatients: 835.70 (558.30–1602.00) vs. 403.10 (372.70–556.90) pg/ml; p = 0.0026). Moreover, HMGB1 was associated with IL-18 concentrations in the sera of COVID-19 inpatients (p = 0.0337; r = 0.5500). ConclusionThe association of HMGB1 and IL-18 in COVID-19 might indicate the potential for a dangerous cycle leading to a cytokine storm to occur.

Suicide death and other-cause mortality in psychiatric patients: A South Korean study using nationwide claims data

IntroductionIt is well-known that suicide and excess mortality are high in patients with psychiatric illnesses and this has long been an important issue in the field of mental health. We aim to investigate suicide and other-cause deaths in patients with psychiatric illnesses. MethodsThis retrospective, population-based cohort was based on the National Health Insurance claims data of the first admission with a principal diagnosis of major psychiatric disorder between 2010 and 2011, and followed up to 2020. A total of 95,855 participants were enrolled. Suicide and other-cause mortality were assessed through Log-rank test and Kaplan-Meier curve. ResultsThere were 95,855 patients, with an average age of 48.2 years. The number of suicide deaths and other-cause deaths was 2408 (288.1 per 100,000 person-years) and 15,192 (1817.6 per 100,000 person-years), respectively. The rate of healthcare utilization prior to suicide was 95.0 %, and the rate of utilization prior to one week before suicide was 43.5 %. The risk of suicide was highest in patients with depression, followed by alcohol use disorder, schizophrenia, and bipolar disorder. ConclusionsThis study revealed various factors related to healthcare utilization associated with suicide and other-cause deaths in psychiatric patients. Educating frontline healthcare professionals, psychiatrists, emergency department personnel, and general practice doctors using such as Gatekeeper program is important to prevent suicides.

Usage Patterns of Traditional Chinese Medicine for Patients with Bipolar Disorder: A Population-Based Study in Taiwan.

Patients with bipolar disorder (BD) receive traditional Chinese medicine (TCM) for clinical needs unmet with psychotropic medications. However, the clinical characteristics of practices and outcomes of TCM in BD are not fully understood. This cohort study investigated the clinical characteristics, principal diagnoses, TCM interventions, and TCM prescriptions in patients with BD. Data for a total of 12,113 patients with BD between 1996 and 2013 were withdrawn from Taiwan's longitudinal health insurance database 2000 (LHID 2000). The chi-square test was used for categorical variables, and the independent t-test was used for continuous variables. A p-value less than 0.05 indicated significance. One thousand three hundred nineteen patients who visited TCM clinics after the diagnosis of BD were in the TCM group, while those who never visited TCM were in the non-TCM group (n = 1053). Compared to the non-TCM group, patients in the TCM group had younger average age, a higher percentage of female individuals, more comorbidities of anxiety and alcohol use disorders, and higher mood stabilizer usage rates. The TCM group exhibited pain-related indications, including joint pain, myalgia, myositis, headache, and sleep disturbances. Corydalis yanhusuo and Shu-Jing-Huo-Xue-Tang were the most useful single herbs and herbal formulae. Physicians need to be aware of the use of TCM in patients with BD.

Hospital admissions and outcomes for systolic and diastolic heart failure in Spain between 2016 and 2019: A population-based study

Background and purposeIn Spain there is a lack of population data that specifically compare hospitalization for systolic and diastolic heart failure (HF). We assessed clinical characteristics, in-hospital mortality and 30-day cardiovascular readmission rates differentiating by HF type. MethodsWe conducted a retrospective observational study of patients discharged with the principal diagnosis of HF from The National Health System’ acute hospital during 2016–2019, distinguishing between systolic and diastolic HF. The source of the data was the Minimum Basic Data Set. The risk-standardized in-hospital mortality ratio and risk-standardized 30-day cardiovascular readmission ratio were calculated using multilevel risk adjustment models. Results190,200 episodes of HF were selected. Of these, 163,727 (86.1%) were classified as diastolic HF and were characterized by older age, higher proportion of women, diabetes mellitus, dementia and renal failure than those with systolic HF. In the multilevel risk adjustment models, diastolic HF was a protective factor for both in-hospital mortality (Odds ratio-OR-: 0.79; 95% confidence interval [CI], 0.75−0.83; p < 0.001) and 30-day cardiovascular readmission versus systolic HF (OR: 0.93; 95%CI: 0.88−0.97; p = 0.002). ConclusionsIn Spain, between 2016 and 2019, hospitalization episodes for HF were mostly due to diastolic HF. According to the multilevel risk adjustment models, diastolic HF compared to systolic HF was a protective factor for both in-hospital mortality and 30-day cardiovascular readmission.

Postpartum readmission risk: a comparison between stillbirths and live births

Stillbirth occurs more commonly among pregnant people with comorbid conditions and obstetrical complications. Stillbirth also independently increases maternal morbidity and imparts a psychosocial hazard when compared with live birth. These distinct needs and burden may increase the risk for postpartum readmission after stillbirth. This study aimed to examine the risk for maternal postpartum readmission after stillbirth in comparison with live birth and to identify indications for readmission and the associated risk factors. This was a retrospective cohort of patients with singleton stillbirths or live births, delivered at ≥20 weeks' gestation, who were identified from the 2019 Nationwide Readmissions Database. The primary outcome was all-cause readmission within 6 weeks of discharge from the childbirth hospitalization. The association between stillbirth (vs live birth) and risk for readmission was assessed using multivariable regression models with adjustment for maternal age, sociodemographic characteristics, maternal and obstetrical conditions, and delivery characteristics. Within the stillbirth group, risk factors for readmission were further examined using multivariable regression. The secondary outcomes included principal indication for readmission (categorized based on principal diagnosis code of the readmission hospitalization) and timing of readmission (number of weeks after childbirth hospitalization). Differences in these secondary outcomes were compared between the stillbirth and live birth groups using chi-square tests. All analyses accounted for the complex sample design to generate nationally representative estimates. Postpartum readmission occurred in 2.7% of 16,636 patients with stillbirths, whereas it occurred in 1.6% of 2,870,677 patients with live births (unadjusted risk ratio, 1.65; 95% confidence interval, 1.47-1.86). The higher risk for readmission after stillbirth (vs live birth) persisted after adjusting for maternal, obstetrical, and delivery characteristics (adjusted risk ratio, 1.27; 95% confidence interval, 1.11-1.46). The distribution of principal indication for readmission differed after stillbirth and after live birth and included hypertension (30.2% vs 39.5%; unadjusted risk ratio, 0.76; 95% confidence interval, 0.63-0.93), mental health or substance use disorders (6.8% vs 3.6%; unadjusted risk ratio, 1.90; 95% confidence interval, 1.15-3.16), and venous thromboembolism (5.8% vs 2.0%; unadjusted risk ratio, 2.87; 95% confidence interval, 1.60-5.17). Among patients with stillbirths, 56.0% of readmissions occurred within 1 week, 71.8% within 2 weeks, and 88.1% within 4 weeks; the timing of readmission did not differ significantly between the stillbirth and live birth cohorts. Pregestational diabetes (adjusted risk ratio, 1.87; 95% confidence interval, 1.20-2.93), gestational diabetes (adjusted risk ratio, 1.67; 95% confidence interval, 1.03-2.71), hypertensive disorders of pregnancy (adjusted risk ratio, 1.80; 95% confidence interval, 1.31-2.47), obesity (adjusted risk ratio, 1.46; 95% confidence interval, 1.01-2.12), and primary cesarean delivery (adjusted risk ratio, 1.74; 95% confidence interval, 1.17-2.58) were associated with a higher risk for readmission after stillbirth, whereas higher household income was associated with a lower risk for readmission (eg, adjusted risk ratio for income ≥$82,000 vs $1-$47,999, 0.48; 95% confidence interval, 0.30-0.77). When compared with live births, the risk for postpartum readmission was higher after stillbirths, even after adjustment for differences in the patient demographic and clinical characteristics. Readmission for mental health or substance use disorders and venous thromboembolism is more common after stillbirths than after live births.

A Novel Method for Assessing Risk-Adjusted Diagnostic Coding Specificity for Depression Using a U.S. Cohort of over One Million Patients.

Depression is a prevalent and debilitating mental health condition that poses significant challenges for healthcare providers, researchers, and policymakers. The diagnostic coding specificity of depression is crucial for improving patient care, resource allocation, and health outcomes. We propose a novel approach to assess risk-adjusted coding specificity for individuals diagnosed with depression using a vast cohort of over one million inpatient hospitalizations in the United States. Considering various clinical, demographic, and socioeconomic characteristics, we develop a risk-adjusted model that assesses diagnostic coding specificity. Results demonstrate that risk-adjustment is necessary and useful to explain variability in the coding specificity of principal (AUC = 0.76) and secondary (AUC = 0.69) diagnoses. Our approach combines a multivariate logistic regression at the patient hospitalization level to extract risk-adjusted probabilities of specificity with a Poisson Binomial approach at the facility level. This method can be used to identify healthcare facilities that over- and under-specify diagnostic coding when compared to peer-defined standards of practice.

Variations in Suicide Risk and Risk Factors After Hospitalization for Depression in Finland, 1996-2017

Although incidence of suicide in depression varies remarkably temporally, risk factors have been modeled as constant and remain uncharted in the short term. How effectively factors measured at one point in time predict risk at different time points is unknown. To examine the absolute risk and risk factors for suicide in hospitalized patients with depression starting from the first days after discharge up to 2 years and to evaluate whether the size of relative risk by factor displays temporal patterns over consecutive phases of follow-up. This population-based study using Finnish registers (hospital discharge, population, and cause of death registers) included all hospitalizations for depression as the principal diagnosis in Finland from 1996 to 2017, with a maximum follow-up of 2 years. Data were analyzed from January 2022 to November 2023. Incidence rate (IR), IR ratios, hazard functions, and hazard ratios for suicide by consecutive time periods (0 to 3 days, 4 to 7 days, 7 to 30 days, 31 to 90 days, 91 to 365 days, and 1 to 2 years) since discharge. This study included 193 197 hospitalizations among 91 161 individuals, of whom 51 197 (56.2%) were female, and the mean (SD) age was 44.0 (17.3) years. Altogether, patients were followed up to 226 615 person-years. A total of 1219 men and 757 women died of suicide. Incidence of suicide was extremely high during the first days after discharge (IR of 6062 [95% CI, 4963-7404] per 100 000 on days 0 to 3; IR of 3884 [95% CI, 3119-4835] per 100 000 on days 4 to 7) and declined thereafter. Several factors were associated with risk of suicide over the first days after discharge. Current suicide attempt by hanging or firearms increased the risk of suicide most on days 0 to 3 (IR ratio, 18.9; 95% CI, 3.1-59.8) and on days 0 to 7 (IR ratio, 10.1; 95% CI, 1.7-31.5). Temporal patterns of the size of the relative risk diverged over time, being constant, declining, or increasing. Clinical factors had the strongest association immediately. Relative risk remained constant among men and even increased among those with alcohol or substance use disorder. In this study, patients hospitalized for depression had extremely high risk of suicide during the first days after discharge. Thereafter, incidence declined steeply but remained high. Within the periods of the highest risk of suicide, several factors increased overall risk manyfold. Risk factors' observed potencies varied over time and had characteristic temporal patterns.

Changes in the numbers of hospital-based abortions and outpatient early medical abortions in Victoria, 2012-22: a retrospective cohort study.

To assess changes in the monthly numbers of hospital-based abortions and outpatient early medical abortions in Victoria during January 2012 - March 2022, with a particular interest in the impact of the coronavirus disease 2019 (COVID-19) pandemic. Population-based retrospective cohort study; time series analysis of Victorian Admitted Episodes Dataset (VAED) and Pharmaceutical Benefits Scheme (PBS) data. All admitted care episodes in Victoria during 1 January 2012 - 31 March 2022 with medical abortion as the principal diagnosis; all PBS claims for mifepristone-misoprostol (MS-2 Step) during 1 January 2015 (date of listing) - 31 March 2022. Changes in monthly numbers (with 95% confidence intervals [CIs]) of admissions for hospital-based and outpatient early medical abortions during the pre-pandemic period (January 2012 - March 2020), the first full month of the COVID-19 pandemic (April 2020), and the pandemic period (May 2020 - March 2022). The monthly number of hospital-based abortions declined in Victoria during the pre-pandemic period (slope, -2.92 [95% CI, -3.45 to -2.38] per month); the rate of decline was greater during the pandemic period (slope, -5.74 [95% CI, -10.5 to -0.96] per month). The monthly number of outpatient early medical abortions increased during the pre-pandemic period (slope, 5.94 [95% CI, 5.34-6.34] per month); it declined during the first month of the pandemic (slope, -26.4 [95% CI, -70.1 to -17.3] per month), but did not significantly change thereafter. The total monthly number of abortions during the pandemic period did not deviate markedly from the pre-pandemic median value. The pre-pandemic declines in monthly numbers of abortions in major city hospitals, in private hospitals, or at earlier than 14 weeks' gestation intensified during the pandemic period. During January 2015 - March 2020, 14 634 of 103 496 abortions were outpatient medical abortions (14%); during the pandemic period, 11 154 of 33 056 abortions were outpatient medical abortions (33%). The use of outpatient early medical abortion has steadily increased in Victoria since the PBS listing of mifepristone-misoprostol, which helped ensure access to abortion during the COVID-19 pandemic. Outpatient medical abortions may eventually outnumber surgical early abortions in Victoria, but they are not always appropriate: hospitals will continue to be essential for comprehensive abortion care.

Factors affecting treatment outcomes of hospital injury patients in Korea.

To analyze the characteristics of hospital injured patients and the factors that affect treatment results. We used the data from the Korea National Hospital Discharge In-depth Injury Survey from 2019 to 2021 of the Korea Disease Control and Prevention Agency (KDCA), 18,037 people who experienced hospital injury accidents were analyzed. In a retrospective cross-sectional study, general characteristics and injury-related characteristics of patients with hospital-acquired injuries were collected. The data were analyzed using chi-square test and logistic regression analysis of complex sampling design. The significance of all statistical analyses was verified at the p-value (<0.05) level. Variables that significantly affected the death of patients with hospital injuries were gender, age, route of admission, type of hospital injury, principal diagnosis, and length of stay (p < 0.05). The risk of death was 3.174 times (95% confidence interval: 2.376-4.238) higher when neoplasm was the principal diagnosis compared to cases with principal diagnosis of other systems. It is necessary to do patient safety education to help medical personnel be more aware of groups of patients who had a high risk of death from hospital damage, such as male and elderly patients, patients who admitted through the emergency room, and patients whose principal diagnosis was neoplasm, circulatory system, or respiratory system disease.

Abstract TMP42: Reducing 30-day Stroke Readmissions Using a Multi-Step Quality Improvement Approach

Background: Thirty-day all-cause readmissions occur in about 12% of acute ischemic stroke (AIS) patients, are associated with a 4-fold increase in mortality, and are associated with increased cost utilization. Therefore, reducing 30-day readmissions in AIS patients is of paramount importance. In this study, we aimed to test the effect of a multi-step quality improvement (QI) initiative on readmission rates in hospitalized AIS patients. Methods: We included all patients discharged from a Comprehensive Stroke Center with a diagnosis of AIS or TIA over a 3-year period. The pre-intervention period was 1/1/2020 - 9/30/2021. The approach was instituted on 10/1/2021. After a 3-month washout, the post-intervention period was 1/1/2022 - 6/30/2023. Intervention measures are below.1. An inpatient checklist was instituted to help providers identify and address common problems before AIS/TIA patients were discharged.2. Complex patients discharged home would receive a call shortly after discharge to ensure good understanding of their care and next steps. Such patients were also scheduled to follow up in a rapid access clinic within 2 weeks of discharge.3. Complex patients discharged to a facility required a handoff call to the facility’s accepting provider.4. All readmissions were reviewed in our monthly QI meeting, with efforts to identify preventable causes.We used t-tests to compare mean observed to expected (O:E) length of stay and mortality metrics between the pre- and post-intervention periods. We used Chi Square tests to compare overall readmission rates. Results: Over the study period, 2532 patients were discharged with a principal diagnosis of AIS or TIA, and the all-cause 30-day readmission rate was 8.8% (223/2532). Compared to pre-intervention, the post-intervention period had a lower 30-day readmission rate (7.6% vs. 10.2%, p = 0.023), a non-significantly lower mean O:E mortality rate (0.71 vs. 0.82, p = 0.252), and a non-significantly lower mean O:E hospital length of stay (0.92 vs. 0.88, p = 0.13). Conclusion: At a Comprehensive Stroke Center, a multi-step approach for transitions of care was associated with reduced all-cause readmission rates without increasing hospital length of stay or mortality. Our findings require external validation.

Predicting preterm birth using auto-ML frameworks: a large observational study using electronic inpatient discharge data.

To develop and compare different AutoML frameworks and machine learning models to predict premature birth. The study used a large electronic medical record database to include 715,962 participants who had the principal diagnosis code of childbirth. Three Automatic Machine Learning (AutoML) were used to construct machine learning models including tree-based models, ensembled models, and deep neural networks on the training sample (N = 536,971). The area under the curve (AUC) and training times were used to assess the performance of the prediction models, and feature importance was computed via permutation-shuffling. The H2O AutoML framework had the highest median AUC of 0.846, followed by AutoGluon (median AUC: 0.840) and Auto-sklearn (median AUC: 0.820), and the median training time was the lowest for H2O AutoML (0.14 min), followed by AutoGluon (0.16 min) and Auto-sklearn (4.33 min). Among different types of machine learning models, the Gradient Boosting Machines (GBM) or Extreme Gradient Boosting (XGBoost), stacked ensemble, and random forrest models had better predictive performance, with median AUC scores being 0.846, 0.846, and 0.842, respectively. Important features related to preterm birth included premature rupture of membrane (PROM), incompetent cervix, occupation, and preeclampsia. Our study highlights the potential of machine learning models in predicting the risk of preterm birth using readily available electronic medical record data, which have significant implications for improving prenatal care and outcomes.

Ingresos en fines de semana y festivos por insuficiencia cardiaca descompensada y mortalidad intrahospitalaria. ¿Un efecto acumulativo de los «días no laborables»?

Introduction and objectivesThe aim of this study was to analyze whether nonelective admissions in patients with heart failure (HF) on nonworking days (NWD) are associated with higher in-hospital mortality. MethodsWe conducted a retrospective (2018-2019) observational study of episodes of nonelective admissions in patients aged 18 years and older discharged with a principal diagnosis of HF in acute general hospitals of the Spanish National Health System. NWD at admission were defined as Fridays after 14:00hours, Saturdays, Sundays, and national and regional holidays. In-hospital mortality was analyzed with logistic regression models. The length of NWD was considered as an independent continuous variable. Propensity score matching was used as a sensitivity analysis. ResultsWe selected 235 281 episodes of nonelective HF admissions. When the NWD periods were included in the in-hospital mortality model, the increases in in-hospital mortality compared with weekday admission were as follows: 1 NWD day (OR, 1.11; 95%CI, 1.07-1.16); 2 days (OR, 1.13; 95%CI, 1.09-1.17); 3 (OR, 1.16; 95%CI, 1.05-1.27); and ≥4 days (OR, 1.20; 95%CI, 1.09-1.32). There was a statistically significant association between a linear increase in NWD and higher risk-adjusted in-hospital mortality (chi-square trend P=.0002). After propensity score matching, patients with HF admitted on NWD had higher in-hospital mortality than those admitted on weekdays (OR, 1.11; average treatment effect, 12.2% vs 11.1%; P<.001). ConclusionsWe found an association between admissions for decompensated HF on an NWD and higher in-hospital mortality. The excess mortality is likely not explained by differences in severity. In this study, the “weekend effect” tended to increase as the NWD period became longer.Full English text available from:www.revespcardiol.org/en

Clinical outcomes of myocardial infarction with non-obstructive coronary arteries presenting with diabetic ketoacidosis: a propensity score-matched analysis

Introduction and ObjectiveThere is a paucity of data on patients with myocardial infarction with nonobstructive coronary arteries (MINOCA) and a decompensated diabetic state, diabetic ketoacidosis (DKA). Therefore, we aimed to investigate the outcomes of patients with MINOCA presenting with or without DKA.MethodsWe conducted this retrospective propensity score-matched analysis from January 1, 2015, to December 4, 2022. The patients with a principal admission diagnosis of ST-Elevation MI (STEMI) and discharge labeled as MINOCA (ICD-10-CM code 121.9) with DKA were analyzed. We performed a comparative analysis for MINOCA with and without DKA before and after propensity score matching for primary and secondary endpoints.ResultsThree thousand five hundred sixty-three patients were analyzed, and 1150 (32.27%) presented with DKA, while 2413 (67.72%) presented as non-DKA. The DKA cohort had over two-fold mortality (5.56% vs. 1.19%; p = 0.024), reinfarction (5.82% vs. 1.45%; p = 0.021), stroke (4.43% vs. 1.36%; p = 0.035), heart failure (6.89% vs. 2.11%; p = 0.033), and cardiogenic shock (6.43% vs. 1.78%; p = 0.025) in a propensity score-matched analysis. There was an increased graded risk of MINOCA with DM (RR (95% CI): 0.50 (0.36–0.86; p = 0.023), DKA (RR (95% CI): 0.46 (0.24–0.67; p = 0.001), and other cardiovascular (CV) risk factors.ConclusionDKA complicates a portion of MINOCA and is associated with increased mortality and major adverse cardiovascular events (MACE).

Racial/Ethnic Disparities in Aortic Valve Replacement Among Medicare Beneficiaries in the United States, 2012-2019

PurposeThere are concerns that transcatheter or surgical aortic valve replacement (TAVR/SAVR) procedures are preferentially available to White patients. Our objective was to examine differences in utilization of aortic valve replacement and outcomes by race/ethnicity in the US for patients with aortic stenosis. MethodsWe performed a serial cross-sectional cohort study of 299,976 Medicare beneficiaries hospitalized with principal diagnosis of aortic stenosis between 2012 and 2019 stratified by self-reported race/ethnicity (Black, Hispanic, Asian, Native American, and White). Outcomes included aortic valve replacement rates within 6 months of index hospitalization and associated procedural outcomes, including 30-day readmission, 30-day and 1-year mortality. ResultsWithin 6 months of an index admission for aortic stenosis, 86.8% (122,457 SAVR; 138,026 TAVR) patients underwent aortic valve replacement. Overall, compared with White people, Black (HR 0.87 [0.85-0.89]), Hispanic (0.92 [0.88-0.96]), and Asian (0.95 [0.91-0.99]) people were less likely to receive aortic valve replacement. Among patients who were admitted emergently/urgently, White patients (41.1%, 95% CI, 40.7-41.4) had a significantly higher aortic valve replacement rate compared with Black (29.6%, 95% CI, 28.3-30.9), Hispanic (36.6%, 95% CI, 34.0-39.3), and Asian patients (35.4%, 95% CI, 32.3-38.9). Aortic valve replacement rates increased annually for all race/ethnicities. There were no significant differences in 30-day or 1-year mortality by race/ethnicity. ConclusionsAortic valve replacement rates within 6 months of aortic stenosis admission are lower for Black, Hispanic, and Asian people compared to White people. These race-related differences in aortic stenosis treatment reflect complex issues in diagnosis and management, warranting a comprehensive reassessment of the entire care spectrum for disadvantaged populations.