The current research on ST elevation myocardial infarction (STEMI) patients has been mostly limited to Door-to-Balloon (D-to-B) time. This study aimed to compare the effects of different hospital admission modes to on the time metrics of patients undergoing primary percutaneous coronary intervention (PPCI). It also examined the effects of these modes on in-hospital mortality and other influencing factors. The goal was to prompt healthcare facilities at all levels, including chest hospitals, the Centers for Disease Control and Prevention (CDC), and communities to take measures to enhance the treatment outcomes for patients with STEMI. A total of 1053 cases of STEMI patients admitted to Tianjin Chest Hospital from December 2016 to December 2023 and successfully underwent PPCI were selected for this study. They were divided into three groups based on the admission modes: the ambulances group (363 cases), the self-presentation group (305 cases), and the transferred group (385 cases). Multivariate logistic regression was used to explore the impact of different modes of hospital admission on the standard-reaching rate of key treatment time metrics. The results showed that the S-to-FMC time of transferred patients (OR = 0.434, 95% CI 0.316-0.596, P < 0.001) and self-presentation patients (OR = 0.489, 95% CI 0.363-0.659, P < 0.001) were more likely to exceed the standard than that of ambulance patients; The cath lab pre-activation time of self-presented patients was also less likely to meet the standard than that of ambulance patients (OR = 0.695, 95% CI 0.499-0.967, P = 0.031); D-to-W time of self-presentation patients was less likely to reach the standard than that of ambulance patients (OR = 0.323, 95% CI 0.234-0.446, P < 0.001);However, the FMC-to-ECG time of self-presentation patients was more likely to reach the standard than that of ambulance patients (OR = 2.601, 95% CI 1.326-5.100, P = 0.005). The Cox proportional hazards model analysis revealed that for ambulance patients, the time spent at each key treatment time point is shorter, leading to lower in-hospital mortality rate (HR0.512, 95% CI 0.302-0.868, P = 0.013) compared to patients admitted by other means. We found that direct arrival of STEMI patients to the PCI hospital via ambulance at the onset of the disease significantly reduces the S-to-FMC time, FMC-to-ECG time, D-to-W time, and catheterization room activation time compared to patients who self-present. This admission mode enhances the likelihood of meeting the benchmark standards for each time metric, consequently enhancing patient outcomes.

UNASSIGNED: Over the past 25 years, diagnosis and therapy for acute aortic dissection (AAD) have evolved. We aimed to study the effects of these iterative changes in care.
UNASSIGNED: Patients with nontraumatic AAD enrolled in the International Registry of Acute Aortic Dissection (61 centers; 15 countries) were divided into time-based tertiles (groups) from 1996 to 2022. The impact of changes in diagnostics, therapeutic care, and in-hospital and 3-year mortality was assessed. Cochran-Armitage trend and Jonckheere-Terpstra tests were conducted to test for any temporal trend.
UNASSIGNED: Each group consisted of 3785 patients (mean age, ≈62 years old; ≈65.5% males); nearly two-thirds had type A AAD. Over time, the rates of hypertension increased from 77.8% to 80.4% (P=0.002), while smoking (34.1% to 30.6%, P=0.033) and atherosclerosis decreased (25.6%-16.6%; P<0.001). Across groups, the percentage of surgical repair of type A AAD increased from 89.1% to 92.5% (P<0.001) and was associated with decreased hospital mortality (from 24.1% in group 1 to 16.7% in group 3; P<0.001). There was no difference in 3-year survival (P=0.296). For type B AAD, stent graft therapy (thoracic endovascular aortic repair) was used more frequently (22.3%-35.9%; P<0.001), with a corresponding decrease in open surgery. Endovascular in-hospital mortality decreased from 9.9% to 6.2% (P=0.003). As seen with the type A AAD cohort, overall 3-year mortality for patients with type B AAD was consistent over time (P=0.084).
UNASSIGNED: Over 25 years, substantial improvements in-hospital survival were associated with a more aggressive surgical approach for patients with type A AAD. Open surgery has been partially supplanted by thoracic endovascular aortic repair for complicated type B AAD, and in-hospital mortality has decreased over the time period studied. Postdischarge survival for up to 3 years was similar over time.

BACKGROUND: The COVID-19 pandemic brought greater focus to the rural mortality penalty in the U.S., which describes the greater mortality rate in rural compared to urban areas. Although it is widely thought that issues such as access to care, age structure of the population, and differences in behavior are likely drivers of the rural mortality penalty, few studies have attempted to tie delayed access to care in rural populations to healthcare outcomes quantitatively. Therefore, it is critical to try and understand these factors to enable more effective public health policy.
METHODS: We performed a cross-sectional analysis of a population of patients with COVID-19 who were admitted to hospitals in the United States between 3/1/2020 and 2/26/2023 to better understand factors leading to outcome disparities amongst groups that all had some level of access to hospital care. Nevertheless, it is widely thought that rural populations often experience delayed access to care, due to transportation and other constraints. Therefore, we hypothesized that deteriorated patient condition at admission likely explained some of the observed difference in mortality between rural and urban populations.
RESULTS: Our results supported our hypothesis, showing that the rural mortality penalty persists in this population and that by multiple measures, rural patients were likely to be admitted in worse condition, had worse overall health, and were older.
CONCLUSIONS: Although the pandemic threw the rural mortality penalty into sharp relief, it is important to remember that it existed prior to the pandemic and will continue to exist until effective interventions are implemented. This study demonstrates the critical need to address the underlying factors that resulted in rural-dwelling patients being admitted to the hospital in worse condition than their urban-dwelling counterparts during the COVID-19 pandemic, which likely affected other healthcare outcomes as well.

BACKGROUND: From March 7 to April 7, 2020, the Community of Madrid (CoM), Spain, issued interventions in response to the COVID-19 epidemic, including hospital referral triage protocols for long-term care facility (LTCF) residents (March 18-25). Those with moderate to severe physical disability and cognitive impairment were excluded from hospital referral. This research assesses changes in the association between daily hospital referrals and the deaths of LTCF residents attributable to the triage protocols.
METHODS: Daily hospital referrals and all-cause mortality from January to June 2020 among LTCF residents and the CoM population aged 65 + were obtained. Significant changes in LTCF resident daily hospital referrals time series, and in-LTCF and in-hospital daily deaths, were examined with tests for breaks and regimes in time series. Multivariate time series analyses were conducted to test changes in the associations between LTCF resident hospital referrals with daily deaths in-hospital and in-LTCF, and in the CoM population aged 65 + when the triage protocols were implemented.
RESULTS: Among LTCF residents, hospital referrals declined sharply from March 6 to March 23, 2020. Increases in LTCF residents\' daily deaths occurred from March 7 to April 1, followed by a decrease reaching pre-epidemic levels after April 28. The daily ratio of in-hospital deaths to in-LTCF deaths reached its lowest values from March 9 to April 19, 2020. The four versions of the triage protocol, published from March 18 to March 25 had no impact on further changes in the association of hospital referrals with daily deaths of LTCF residents in-hospital or in-LTCF.
CONCLUSIONS: While LTCF residents\' deaths increased, hospital referrals of LTCF residents decreased with the introduction of the CoM governmental interventions on March 7. They were implemented before the enactment of the triage protocols, protecting hospitals from collapse while overlooking the need for standards of care within LTCFs. The CoM triage protocols sanctioned the existing restrictions on hospital referrals of LTCF residents.

OBJECTIVE: To examine the role of justice-involved status on in-hospital mortality among nonelderly adults during the second year of the COVID-19 pandemic.
METHODS: This retrospective cohort study used data from the 2021 State Inpatient Databases (SIDs) for 20 US states, which included discharges from general acute care hospitals among adults aged 18-64 years hospitalized for at least 24 hours. The main outcome was all-cause in-hospital mortality and the primary comparison was justice-involved status. We used logistic regression to estimate the odds ratios (ORs) and 95% confidence intervals (CIs), with adjustment for sociodemographic factors, Elixhauser comorbidities, COVID-19 diagnosis, admission acuity, other clinical features, metropolitan area and seasonality. We randomly split the data into a 50% training and 50% validation set. With the latter, we evaluated the performance of our final model.
RESULTS: The study population included 4,712,441 discharges (1.1% justice-involved; mean [SD] age 47.5 [12.8] years; 47.0% women; 63.6% White, 21.8% Black, 11.8% Hispanic, 1.8% Asian/Pacific Islander [API], and 1.0% American Indian/Alaska Native [AIAN]). Among these, 102,735 in-hospital deaths (2.2%) occurred. In the multivariate analysis, in-hospital mortality was about 40% less likely among justice-involved patients (OR 0.6, 95% CI 0.5 to 0.7, P-value < 0.01). The final validated model showed excellent discrimination (area under the curve [AUC] for the receiver operator characteristic 0.953, 95%CI 0.952 to 0.954) and good calibration (Brier score 0.014, calibration belt P-value 0.186).
CONCLUSIONS: In this cohort study, justice-involved status was independently associated with lower in-hospital mortality. Future studies should examine pre-admission and post-discharge outcomes.

UNASSIGNED: Ulinastatin has been applied in a series of diseases associated with inflammation but its clinical effects remain somewhat elusive.
UNASSIGNED: We aimed to investigate the potential effects of ulinastatin on organ failure patients admitted to the intensive care unit (ICU).
UNASSIGNED: This is a single-center retrospective study on organ failure patients from 2013 to 2019. Patients were divided into two groups according to using ulinastatin or not during hospitalization. Propensity score matching was applied to reduce bias. The outcomes of interest were 28-day all-cause mortality, length of ICU stay, and mechanical ventilation duration.
UNASSIGNED: Of the 841 patients who fulfilled the entry criteria, 247 received ulinastatin. A propensity-matched cohort of 608 patients was created. No significant differences in 28-day mortality between the two groups. Sequential organ failure assessment (SOFA) was identified as the independent risk factor associated with mortality. In the subgroup with SOFA ≤ 10, patients received ulinastatin experienced significantly shorter time in ICU (10.0 d [interquartile range, IQR: 7.0∼20.0] vs 15.0 d [IQR: 7.0∼25.0]; p = .004) and on mechanical ventilation (222 h [IQR:114∼349] vs 251 h [IQR: 123∼499]; P = .01), but the 28-day mortality revealed no obvious difference (10.5% vs 9.4%; p = .74).
UNASSIGNED: Ulinastatin was beneficial in treating patients in ICU with organ failure, mainly by reducing the length of ICU stay and duration of mechanical ventilation.

This article aims to examine the effects of weekend admission on in-hospital mortality for patients with acute myocardial infarction (AMI) in Brazil. Information from the Hospital Information System of the Unified Health System (SIH/SUS) of urgently admitted patients diagnosed with acute myocardial infarction (AMI) between 2008 and 2018 was used, made available through the Hospital Admission Authorization (AIH). Multivariable logistic regression models, controlling for observable patient characteristics, hospital characteristics and year and hospital-fixed effects, were used. The results were consistent with the existence of the weekend effect. For the model adjusted with the inclusion of all controls, the chance of death observed for individuals hospitalized on the weekend is 14% higher. Our results indicated that there is probably an important variation in the quality of hospital care depending on the day the patient is hospitalized. Weekend admissions were associated with in-hospital AMI mortality in Brazil. Future research should analyze the possible channels behind the weekend effect to support public policies that can effectively make healthcare equitable.

UNASSIGNED: Ischemic stroke is a leading cause of mortality and disability globally, necessitating accurate prediction of intra-hospital mortality (IHM) for improved patient care. This study aimed to develop a practical nomogram for personalized IHM risk prediction in ischemic stroke patients.
UNASSIGNED: A retrospective study of 422 ischemic stroke patients (April 2020 - December 2021) from Chongqing Medical University\'s First Affiliated Hospital was conducted, with patients divided into training (n=295) and validation (n=127) groups. Data on demographics, comorbidities, stroke risk factors, and lab results were collected. Stroke severity was assessed using NIHSS, and stroke types were classified by TOAST criteria. Least absolute shrinkage and selection operator (LASSO) regression was employed for predictor selection and nomogram construction, with evaluation through ROC curves, calibration curves, and decision curve analysis.
UNASSIGNED: LASSO regression and multivariate logistic regression identified four independent IHM predictors: age, admission NIHSS score, chronic obstructive pulmonary disease (COPD) diagnosis, and white blood cell count (WBC). A highly accurate nomogram based on these variables exhibited excellent predictive performance, with AUCs of 0.958 (training) and 0.962 (validation), sensitivities of 93.2% and 95.7%, and specificities of 93.1% and 90.9%, respectively. Calibration curves and decision curve analysis validated its clinical applicability.
UNASSIGNED: Age, admission NIHSS score, COPD history, and WBC were identified as independent IHM predictors in ischemic stroke patients. The developed nomogram demonstrated high predictive accuracy and practical utility for mortality risk estimation. External validation and prospective studies are warranted for further confirmation of its clinical efficacy.

BACKGROUND: ARDS (acute respiratory distress syndrome) is the most severe form of acute hypoxic respiratory failure. Most studies related to ARDS have excluded patients with hematologic diseases, let alone allogeneic hematopoietic stem cell transplantation (allo-HSCT) recipients. Numerous patients experiencing severe hypoxic respiratory failure do not meet the Berlin definition due to the limitations of diagnosis and treatment. A new definition of ARDS, remove some diagnosis restrictions, was proposed in 2023. Based on the 2023 new definition of ARDS, we investigated the clinical features of ARDS in allo-HSCT recipients and reported risk factors for in-hospital mortality in allo-HSCT recipients defined by the Berlin definition and the new definition of ARDS respectively.
METHODS: From Jan 2016 to Dec 2020, 135 allo-HSCT recipients identified with the new definition and 87 identified with the Berlin definition at three teaching hospitals were retrospectively included in this study. Variables (demographic information, characteristics of hematologic disease and ARDS episode, laboratory tests and SOFA score) with P < 0.05 in univariate logistic regression analysis were included in multivariate stepwise logistic regression analysis. Adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) were reported.
RESULTS: Under the new definition, SOFA score (OR = 1.351, 95% CI: 1.146-1.593, P < 0.01) were found as an independent risk factor for in-hospital mortality in ARDS after allo-HSCT, while SpO2/FiO2 (OR = 0.984, 95% CI: 0.972-0.996, P < 0.01) was a protective factor. The infusion of peripheral-derived stem cells was found to be a protective factor against in-hospital mortality in post-transplantation ARDS compared with the infusion of bone marrow-derived stem cells (OR = 0.726, 95% CI: 0.164-3.221, P = 0.04). Under the Berlin definition, PaO2/FiO2 (OR = 0.977, 95% CI: 0.961-0.993, P = 0.01, lactate (OR = 7.337, 95% CI: 1.313-40.989, P < 0.01) and AST (OR = 1.165, 95% CI: 1.072-1.265, P < 0.01) were independently associated with in-hospital mortality.
CONCLUSIONS: These prognostic risk factors we found in allo-HSCT recipients may contribute to closer monitoring and ARDS prevention strategies. These findings require confirmation in prospective, large sample size studies.

Research on the severity and prognosis of sepsis with or without progressive delirium is relatively insufficient. We constructed a prediction model of the risk factors for 28-day mortality in patients who developed sepsis or sepsis-associated delirium. The modeling group of patients diagnosed with Sepsis-3 and patients with progressive delirium of related indicators were selected from the MIMIC-IV database. Relevant independent risk factors were determined and integrated into the prediction model. Receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow (HL) test were used to evaluate the prediction accuracy and goodness-of-fit of the model. Relevant indicators of patients with sepsis or progressive delirium admitted to the intensive care unit (ICU) of a 3A hospital in Xinjiang were collected and included in the verification group for comparative analysis and clinical validation of the prediction model. The total length of stay in the ICU, hemoglobin levels, albumin levels, activated partial thrombin time, and total bilirubin level were the five independent risk factors in constructing a prediction model. The area under the ROC curve of the predictive model (0.904) and the HL test result (χ2 = 8.518) indicate a good fit. This model is valuable for clinical diagnosis and treatment and auxiliary clinical decision-making.