BACKGROUND: A previous study reported significant excess mortality among non-COVID-19 patients due to disrupted surgical care caused by resource prioritization for COVID-19 cases in France. The primary objective was to investigate if a similar impact occurred for medical conditions and determine the effect of hospital saturation on non-COVID-19 hospital mortality during the first year of the pandemic in France.
METHODS: We conducted a nationwide population-based cohort study including all adult patients hospitalized for non-COVID-19 acute medical conditions in France between March 1, 2020 and 31 May, 2020 (1st wave) and September 1, 2020 and December 31, 2020 (2nd wave). Hospital saturation was categorized into four levels based on weekly bed occupancy for COVID-19: no saturation (< 5%), low saturation (> 5% and ≤ 15%), moderate saturation (> 15% and ≤ 30%), and high saturation (> 30%). Multivariate generalized linear model analyzed the association between hospital saturation and mortality with adjustment for age, sex, COVID-19 wave, Charlson Comorbidity Index, case-mix, source of hospital admission, ICU admission, category of hospital and region of residence.
RESULTS: A total of 2,264,871 adult patients were hospitalized for acute medical conditions. In the multivariate analysis, the hospital mortality was significantly higher in low saturated hospitals (adjusted Odds Ratio/aOR = 1.05, 95% CI [1.34-1.07], P < .001), moderate saturated hospitals (aOR = 1.12, 95% CI [1.09-1.14], P < .001), and highly saturated hospitals (aOR = 1.25, 95% CI [1.21-1.30], P < .001) compared to non-saturated hospitals. The proportion of deaths outside ICU was higher in highly saturated hospitals (87%) compared to non-, low- or moderate saturated hospitals (81-84%). The negative impact of hospital saturation on mortality was more pronounced in patients older than 65 years, those with fewer comorbidities (Charlson 1-2 and 3 vs. 0), patients with cancer, nervous and mental diseases, those admitted from home or through the emergency room (compared to transfers from other hospital wards), and those not admitted to the intensive care unit.
CONCLUSIONS: Our study reveals a noteworthy \"dose-effect\" relationship: as hospital saturation intensifies, the non-COVID-19 hospital mortality risk also increases. These results raise concerns regarding hospitals\' resilience and patient safety, underscoring the importance of identifying targeted strategies to enhance resilience for the future, particularly for high-risk patients.

BACKGROUND: Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data.
METHODS: 2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups.
RESULTS: Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF.
CONCLUSIONS: Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles.

BACKGROUND: Stroke-associated pneumonia (SAP) and gastrointestinal bleeding (GIB) are common medical complications after stroke. The previous study suggested a strong association between SAP and GIB after stroke. However, little is known about the time sequence of SAP and GIB. In the present study, we aimed to verify the association and clarify the temporal sequence of SAP and GIB after ischemic stroke.
METHODS: Patients with ischemic stroke from in-hospital Medical Complication after Acute Stroke study were analyzed. Data on occurrences of SAP and GIB during hospitalization and the intervals from stroke onset to diagnosis of SAP and GIB were collected. Multiple logistic regression was used to evaluate the association between SAP and GIB. Kruskal-Wallis test was used to compare the time intervals from stroke onset to diagnosis of SAP and GIB.
RESULTS: A total of 1129 patients with ischemic stroke were included. The median length of hospitalization was 14 days. Overall, 86 patients (7.6%; 95% CI, 6.1-9.2%) developed SAP and 47 patients (4.3%; 95% CI, 3.0-5.3%) developed GIB during hospitalization. After adjusting potential confounders, SAP was significantly associated with the development of GIB after ischemic stroke (OR = 5.13; 95% CI, 2.02-13.00; P < 0.001). The median time from stroke onset to diagnosis of SAP was shorter than that of GIB after ischemic stroke (4 days vs. 5 days; P = 0.039).
CONCLUSIONS: SAP was associated with GIB after ischemic stroke, and the onset time of SAP was earlier than that of GIB. It is imperative to take precautions to prevent GIB in stroke patients with SAP.

Given the existing uncertainty regarding the effectiveness and safety of switching from low-molecular-weight heparin (LMWH) to direct oral anticoagulants (DOACs) in patients with cancer-associated venous thrombosis (CAT), we conducted a comprehensive population-based cohort study utilizing electronic health database in Hong Kong. A total of 4356 patients with CAT between 2010 and 2022 were included, with 1700 (39.0%) patients switching to DOAC treatment. Compared to continuous LMWH treatment, switching to DOACs was associated with a significantly lower risk of hospitalization due to venous thromboembolism (HR: 0.49 [95% CI = 0.35-0.68]) and all-cause mortality (HR: 0.67 [95% CI = 0.61-0.74]), with no significant difference in major bleeding (HR: 1.04 [95% CI = 0.83-1.31]) within six months. These findings provide reassurance regarding the effectiveness and safety of switching from LMWH to DOACs among patients with CAT, including vulnerable patient groups.

OBJECTIVE: Cellulitis is the most common cause of skin-related hospitalisations, and the mortality of patients with sepsis remains high. Some stratification models have been developed, but their performance in external validation has been unsatisfactory. This study was designed to develop and compare different models for predicting patients with cellulitis developing sepsis during hospitalisation.
METHODS: This is a retrospective cohort study.
METHODS: This study included both the development and the external-validation phases from two independent large cohorts internationally.
METHODS: A total of 6695 patients with cellulitis in the Medical Information Mart for Intensive care (MIMIC)-IV database were used to develop models with different machine-learning algorithms. The best models were selected and then externally validated in 2506 patients with cellulitis from the YiduCloud database of our university. The performances and robustness of selected models were further compared in the external-validation group by area under the curve (AUC), diagnostic accuracy, sensitivity, specificity and diagnostic OR.
METHODS: The primary outcome of interest in this study was the development based on the Sepsis-3.0 criteria during hospitalisation.
RESULTS: Patient characteristics were significantly different between the two groups. In internal validation, XGBoost was the best model, with an AUC of 0.780, and AdaBoost was the worst model, with an AUC of 0.585. In external validation, the AUC of the artificial neural network (ANN) model was the highest, 0.830, while the AUC of the logistic regression (LR) model was the lowest, 0.792. The AUC values changed less in the boosting and ANN models than in the LR model when variables were deleted.
CONCLUSIONS: Boosting and neural network models performed slightly better than the LR model and were more robust in complex clinical situations. The results could provide a tool for clinicians to detect hospitalised patients with cellulitis developing sepsis early.

OBJECTIVE: Peripheral artery disease (PAD) has not only been associated with recurrent hospitalization for acute decompensated heart failure (ADHF) but is also associated with chronic kidney disease (CKD), a known risk factor for worse heart failure outcomes. The interaction of CKD with PAD in post-discharge ADHF outcomes is not well known.
METHODS: Since 2005, hospitalizations for ADHF were sampled from 4 US regions by the Atherosclerosis Risk in Communities (ARIC) study and classified by physician review. We examined the adjusted association of PAD with 1-year ADHF readmissions, in patients with and without CKD (defined by glomerular filtration rate [GFR] ≤60 mL/min/1.73 m2 [stage 3a or worse]).
RESULTS: From 2005 to 2018, there were 1049 index hospitalizations for patients with ADHF (mean age 77 years, 66 % white) with creatinine data, who were discharged alive. Of these, 155 (15 %) had PAD and 66 % had CKD. In comparison to those without PAD, patients with PAD had more comorbid conditions and higher 1-year ADHF readmission rates, irrespective of CKD status. After adjustment, PAD was associated with a greater risk of 1-year ADHF readmissions, both for patients with concomitant CKD (HR, 1.70; 95 % CI: 1.29-2.24) and those without CKD (HR, 1.97; 95 % CI: 1.14-3.40); p-interaction = 0.8.
CONCLUSIONS: Among patients hospitalized with ADHF, those with concurrent PAD have more prevalent cardiovascular comorbidities and higher likelihood of 1-year ADHF readmission, irrespective of CKD status. Integrating a more holistic approach in management of patients with concomitant heart failure, PAD and CKD may be an important strategy to improve the prognosis in this vulnerable population.

This study analyzes and summarizes the assessment tools, current situation, and influencing factors of venous thromboembolism (VTE) prevention knowledge, attitudes, and practices (KAP) among patients. This study aimed to provide a reference basis for developing targeted health education plans and intervention strategies for patients to improve their knowledge and beliefs concerning VTE prevention. This study aimed to increase the implementation rate of VTE prevention measures and ultimately reduce the incidence of VTE.The current studies found that the factors influencing knowledge, attitude, and practice of VTE prevention in hospitalized patients include demographic factors (age, sex, education level, occupation), disease-related factors (treatment stage, injury site, and wards), and other factors (receiving VTE-related knowledge education and having medical workers at home).

Concerns have been raised about the effectiveness of using process-centered indicators to assess the quality of diabetes care in Korea. This study aims to examine the factors influencing the performance of regular HbA1c testing and to explore its association with health outcomes, including hospitalization and mortality. We utilized a retrospective cohort design with a 4-year follow-up period, involving 159,452 adult patients newly diagnosed with type 2 diabetes (E11 in International Classification of Diseases, 10th Edition) in 2011. We established a national population database by merging the Korea National Health Insurance (KNHI) claims database and the KNHI Qualification Database of South Korea. The proportion of diabetic patients who underwent regular HbA1c testing at least once a year in the first 3 years was determined to be 33.8%. In comparison, patients who did not receive regular tests during the same period exhibited significantly increased odds of hospitalization (diabetes/CVD/renal, OR, 1.23, 95% CI, 1.12-1.34; diabetes, OR, 1.36, 95% CI, 1.17-1.57). Additionally, this nonpatient group experienced a higher risk of mortality (OR: 1.56, 95% CI: 1.36-1.80). This study supports the positive impact of regular HbA1c testing on health outcomes for individuals with type 2 diabetes. To increase the current 33% rate of regular HbA1c testing, developing patient-customized management policies is essential. Priority should be given to diabetic patients aged 65 or older, living in rural areas, and those belonging to low-income families (medical aid).

To investigate the trends of hospital admissions concerning diseases of the eye and adnexa in Australia in the past 2 decades. This is a descriptive ecological study on the population level that examined hospitalization data for the duration between 1998 and 2021 in Australia. Hospitalization data were extracted from the National Hospital Morbidity Database. The chi-squared test was utilized to assess the difference in admission rates between the years 1998 and 2021. Hospital admission rate for diseases of the eye and adnexa increased by 1.20-fold (from 852.32 [95% confidence interval [CI] 848.16-856.47] in 1998 to 1873.72 [95% CI 1868.48-1878.96] in 2021 per 100,000 persons, P < .01). The most common cause of hospitalization for diseases of the eye and adnexa was disorders of the lens (65.7%), followed by disorders of the choroid and retina (15.6%), followed by disorders of the eyelid, lacrimal system, and orbit (7.7%). Hospital admission rate among males increased by 1.25-fold (from 737.67 [95% CI 732.18-743.16] in 1998 to 1657.19 [95% CI 1650.19-1664.20] in 2021 per 100,000 persons). Hospital admission rate among females increased less sharply by 1.03-fold (from 965.37 [95% CI 959.14-971.59] in 1998 to 1964.35 [95% CI 1956.80-1971.90] in 2021 per 100,000 persons). There are clear gender and age roles in the epidemiology of hospital admissions related to eye and adnexa disorders. Lens disorders were the most common cause of hospital admission. The admission rate increase during the past decades could be due to increases in life expectancy, lifestyle changes, and improvements in screening protocols.

OBJECTIVE: To estimate hospital services utilisation and cost among the Indonesian population enrolled in the National Health Insurance (NHI) program before and after COVID-19 hospital treatment.
METHODS: 28,159 Indonesian NHI enrolees treated with laboratory-confirmed COVID-19 in hospitals between May and August 2020 were compared to 8,995 individuals never diagnosed with COVID-19 in 2020. A difference-in-difference approach is used to contrast the monthly all-cause utilisation rate and total claims of hospital services between these two groups. A period of nine months before and three to six months after hospital treatment were included in the analysis.
RESULTS: A substantial short-term increase in hospital services utilisation and cost before and after COVID-19 treatment was observed. Using the fifth month before treatment as the reference period, we observed an increased outpatient visits rate in 1-3 calendar months before and up to 2-4 months after treatment (p<0.001) among the COVID-19 group compared to the comparison group. We also found a higher admissions rate in 1-2 months before and one month after treatment (p<0.001). Consequently, increased hospital costs were observed in 1-3 calendar months before and 1-4 calendar months after the treatment (p<0.001). The elevated hospital resource utilisation was more prominent among individuals older than 40. Overall, no substantial increase in hospital outpatient visits, admissions, and costs beyond four months after and five months before COVID-19 treatment.
CONCLUSIONS: Individuals with COVID-19 who required hospital treatment had considerably higher healthcare resource utilisation in the short-term, before and after the treatment. These findings indicated that the total cost of treating COVID-19 patients might include the pre- and post-acute period.