Healthcare quality in low- and middle-income countries poses a significant challenge, contributing to heightened mortality rates from treatable conditions. The accreditation of health facilities was part of the former health reform in Mexico, proposed as a mechanism to enhance healthcare quality. This study assesses the performance of hospital accreditation in Mexico, utilizing indicators of effectiveness, efficiency, and safety. Employing a longitudinal approach with controlled interrupted time series analysis (C-ITSA) and fixed effects panel analysis, administrative data from general hospitals in Mexico is scrutinized. Results reveal that hospital accreditation in Mexico fails to enhance healthcare quality and, disconcertingly, indicates deteriorating performance associated with increased hospital mortality. Amidst underfunded health services, the implemented accreditation model proves inadequately designed to uplift care quality. A fundamental redesign of the public hospital accreditation model is imperative, emphasizing incentives for structural enhancement and standardized processes. Addressing the critical challenge of improving care quality is urgent for Mexico\'s healthcare system, necessitating swift action to achieve effective access as a benchmark for universal healthcare coverage.

UNASSIGNED: The COVID-19 pandemic posed a worldwide challenge, leading to radical changes in surgical services. The primary objective of the study was to assess the impact of COVID-19 on elective and emergency surgeries in a Brazilian metropolitan area. The secondary objective was to compare the postoperative hospital mortality before and during the pandemic.
UNASSIGNED: Time-series cohort study including data of all patients admitted for elective or emergency surgery at the hospitals in the Public Health System of Federal District, Brazil, between March 2018 and February 2022, using data extracted from the Hospital Information System of Brazilian Ministry of Health (SIH/DATASUS) on September 30, 2022. A causal impact analysis was used to evaluate the impact of COVID-19 on elective and emergency surgeries and hospital mortality.
UNASSIGNED: There were 174,473 surgeries during the study period. There was a reduction in overall (absolute effect per week: -227.5; 95% CI: -307.0 to -149.0), elective (absolute effect per week: -170.9; 95% CI: -232.8 to -112.0), and emergency (absolute effect per week: -57.7; 95% CI: -87.5 to -27.7) surgeries during the COVID-19 period. Comparing the surgeries performed before and after the COVID-19 onset, there was an increase in emergency surgeries (53.0% vs 68.8%, P < 0.001) and no significant hospital length of stay (P = 0.112). The effect of the COVID-19 pandemic on postoperative hospital mortality was not statistically significant (absolute effect per week: 2.1, 95% CI: -0.01 to 4.2).
UNASSIGNED: Our study showed a reduction in elective and emergency surgeries during the COVID-19 pandemic, possibly due to disruptions in surgical services. These findings highlight that it is crucial to implement effective strategies to prevent the accumulation of surgical waiting lists in times of crisis and improve outcomes for surgical patients.

This study determined whether compared to conventional mechanical ventilation (MV), extracorporeal membrane oxygenation (ECMO) is associated with decreased hospital mortality or fibrotic changes in patients with COVID-19 acute respiratory distress syndrome. A cohort of 72 patients treated with ECMO and 390 with conventional MV were analyzed (February 2020-December 2021). A target trial was emulated comparing the treatment strategies of initiating ECMO vs no ECMO within 7 days of MV in patients with a PaO2/FiO2 < 80 or a PaCO2 ≥ 60 mmHg. A total of 222 patients met the eligibility criteria for the emulated trial, among whom 42 initiated ECMO. ECMO was associated with a lower risk of hospital mortality (hazard ratio [HR], 0.56; 95% confidence interval [CI] 0.36-0.96). The risk was lower in patients who were younger (age < 70 years), had less comorbidities (Charlson comorbidity index < 2), underwent prone positioning before ECMO, and had driving pressures ≥ 15 cmH2O at inclusion. Furthermore, ECMO was associated with a lower risk of fibrotic changes (HR, 0.30; 95% CI 0.11-0.70). However, the finding was limited due to relatively small number of patients and differences in observability between the ECMO and conventional MV groups.

BACKGROUND: Femoral neck fracture (FNF) accounts for approximately 3.58% of all fractures in the entire body, exhibiting an increasing trend each year. According to a survey, in 1990, the total number of hip fractures in men and women worldwide was approximately 338,000 and 917,000, respectively. In China, FNFs account for 48.22% of hip fractures. Currently, many studies have been conducted on postdischarge mortality and mortality risk in patients with FNF. However, there have been no definitive studies on in-hospital mortality or its influencing factors in patients with severe FNF admitted to the intensive care unit.
OBJECTIVE: In this paper, 3 machine learning methods were used to construct a nosocomial death prediction model for patients admitted to intensive care units to assist clinicians in early clinical decision-making.
METHODS: A retrospective analysis was conducted using information of a patient with FNF from the Medical Information Mart for Intensive Care III. After balancing the data set using the Synthetic Minority Oversampling Technique algorithm, patients were randomly separated into a 70% training set and a 30% testing set for the development and validation, respectively, of the prediction model. Random forest, extreme gradient boosting, and backpropagation neural network prediction models were constructed with nosocomial death as the outcome. Model performance was assessed using the area under the receiver operating characteristic curve, accuracy, precision, sensitivity, and specificity. The predictive value of the models was verified in comparison to the traditional logistic model.
RESULTS: A total of 366 patients with FNFs were selected, including 48 cases (13.1%) of in-hospital death. Data from 636 patients were obtained by balancing the data set with the in-hospital death group to survival group as 1:1. The 3 machine learning models exhibited high predictive accuracy, and the area under the receiver operating characteristic curve of the random forest, extreme gradient boosting, and backpropagation neural network were 0.98, 0.97, and 0.95, respectively, all with higher predictive performance than the traditional logistic regression model. Ranking the importance of the feature variables, the top 10 feature variables that were meaningful for predicting the risk of in-hospital death of patients were the Simplified Acute Physiology Score II, lactate, creatinine, gender, vitamin D, calcium, creatine kinase, creatine kinase isoenzyme, white blood cell, and age.
CONCLUSIONS: Death risk assessment models constructed using machine learning have positive significance for predicting the in-hospital mortality of patients with severe disease and provide a valid basis for reducing in-hospital mortality and improving patient prognosis.

The Coronavirus Disease 2019 (COVID-19) has caused a global health crisis. Mortality predictors in critically ill patients remain under investigation. A retrospective cohort study included 201 patients admitted to the intensive care unit (ICU) due to COVID-19. Data on demographic characteristics, laboratory findings, and mortality were collected. Logistic regression analysis was conducted with various independent variables, including demographic characteristics, clinical factors, and treatment methods. The study aimed to identify key risk factors associated with mortality in an ICU. In an investigation of 201 patients comprising non-survivors (n = 80, 40%) and Survivors (n = 121, 60%), we identified several markers significantly associated with ICU mortality. Lower Interleukin 6 and White Blood Cells levels at both 24- and 48-hours post-ICU admission emerged as significant indicators of survival. The study employed logistic regression analysis to evaluate risk factors for in-ICU mortality. Analysis results revealed that demographic and clinical factors, including gender, age, and comorbidities, were not significant predictors of in-ICU mortality. Ventilator-associated pneumonia was significantly higher in Survivors, and the use of antibiotics showed a significant association with increased mortality risk in the multivariate model (OR: 11.2, p = 0.031). Our study underscores the significance of monitoring Il-6 and WBC levels within 48 hours of ICU admission, potentially influencing COVID-19 patient outcomes. These insights may reshape therapeutic strategies and ICU protocols for critically ill patients.

UNASSIGNED: Extracellular particles (EPs), particularly extracellular vesicles, play a crucial role in regulating various pathological mechanisms, including immune dysregulations post-trauma. Their distinctive expression of cell-specific markers and regulatory cargo such as cytokines or micro-ribonucleic acid suggests their potential as early biomarkers for organ-specific damage and for identifying patients at risk for complications and mortality. Given the critical need for reliable and easily assessable makers to identify at-risk patients and guide therapeutic decisions, we evaluated the early diagnostic value of circulating EPs regarding outcomes in severely injured multiple-trauma patients.
UNASSIGNED: Plasma samples were collected from 133 severely injured trauma patients (Injury Severity Score (ISS) ≥16) immediately upon arrival at the emergency department (ED). Patients were categorized into survivors and non-survivors. Injury characteristics and outcomes related to sepsis, pneumonia, or early (<1 day after admission) and late mortality were assessed. Circulating EPs, cytokine profiles, and blood counts of platelets and leukocytes were determined. Receiver operating characteristic analyses were conducted.
UNASSIGNED: Despite no significant differences in injury pattern or severity, non-survivors exhibited significantly elevated counts of circulating EPs compared to survivors. The optimal cut-off for EPs <200 nm indicating non-survivors was 17380/µl plasma, with a sensitivity of 77% and a specificity of 61% in predicting in-hospital mortality. Later non-survivors received significantly higher numbers of units of packed red blood cells [8.54 ± 5.45 vs. 1.29 ± 0.36 units], had higher serum lactate [38.00 ± 7.51 vs. 26.98 ± 1.58 mg/dL], significantly lower platelet counts [181.30 ± 18.06 vs. 213.60 ± 5.85 *10³/µL] and lower heart rates [74.50 ± 4.93 vs. 90.18 ± 2.06 beats/minute] upon arrival at the ED compared to survivors.
UNASSIGNED: Our results demonstrate the high diagnostic potential of elevated concentrations of circulating EPs <200 nm for identifying patients at risk of mortality after severe trauma. This parameter shows comparable sensitivity to established clinical predictors. Early evaluation of EPs concentration could complement assessment markers in guiding early therapeutic decisions.

Fatty liver disease has been identified as a marker of malnutrition in different clinical settings. Recently, the COntrolling NUTritional status score (CONUT score) emerged as a promising tool for malnutrition assessment. Our aim was to evaluate short-term outcomes among patients with malnutrition-related liver steatosis in an Internal Medicine department. Furthermore, we evaluated the association of the CONUT score with malnutrition-related liver steatosis. Data from 247 patients hospitalized in an Internal Medicine department were retrospectively collected. The study population was stratified into three groups based on hepatic radiodensity assessed with computed tomography: mild steatosis (≥56.1 HU), moderate steatosis (between 49.7 and 56 HU), and severe steatosis (≤49.6 HU). We then calculated the CONUT score. Severe steatosis patients had higher in-hospital mortality (18.2 vs. 15.5%) and longer in-hospital stays compared with the mild steatosis group (length of in-hospital stay longer than 12 days: 45% vs. 40%). Logistic regression analysis showed that severe steatosis was not significantly associated with in-hospital all-cause death, while a high CONUT score was an independent risk factor for sepsis. We found an independent relationship between malnutrition-associated liver steatosis and the CONUT score. These results identified the CONUT score as a tool for nutritional assessment of hospitalized patients.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is associated with high case fatality and significant healthcare costs. Recent studies emphasize the critical role of nutritional status in affecting outcomes in neurological disorders. This study investigates the relationship between the Prognostic Nutrition Index (PNI) and in-hospital complications and case fatality among patients with ICH.
METHODS: A retrospective analysis was performed using data from the Changhua Christian Hospital Clinical Research Database between January 2015 and December 2022. Patients under 20 or over 100 years of age or with incomplete medical data were excluded. We utilized restricted cubic spline models, Kaplan-Meier survival analysis, and ROC analysis to assess the association between PNI and clinical outcomes. Propensity score matching analysis was performed to balance these clinical variables between groups.
RESULTS: In this study, 2402 patients with spontaneous ICH were assessed using the median PNI value of 42.77. The cohort was evenly divided between low and high PNI groups, predominantly male (59.1%), with an average age of 64 years. Patients with lower PNI scores at admission had higher in-hospital complications and increased 28- and 90-day case fatality rates.
CONCLUSIONS: Our study suggests that PNI could serve as a valuable marker for predicting medical complications and case fatality in patients with spontaneous ICH.

Background: The efficacy of veno-venous extracorporeal membrane oxygenation (VV-ECMO) as rescue therapy for refractory COVID-19-related ARDS (C-ARDS) is still debated. We describe the cohort of C-ARDS patients treated with VV-ECMO at our ECMO center, focusing on factors that may affect in-hospital mortality and describing the time course of lung mechanics to assess prognosis. Methods: We performed a prospective observational study in the intensive care unit at the \"Città della Salute e della Scienza\" University Hospital in Turin, Italy, between March 2020 and December 2021. Indications and management of ECMO followed the Extracorporeal Life Support Organization (ELSO) guidelines. Results: The 60-day in-hospital mortality was particularly high (85.4%). Non-survivor patients were more frequently treated with non-invasive ventilatory support and steroids before ECMO (95.1% vs. 57.1%, p = 0.018 and 73.2% vs. 28.6%, p = 0.033, respectively), while hypertension was the only pre-ECMO factor independently associated with in-hospital mortality (HR: 2.06, 95%CI: 1.06-4.00). High rates of bleeding (85.4%) and superinfections (91.7%) were recorded during ECMO, likely affecting the overall length of ECMO (18 days, IQR: 10-24) and the hospital stay (32 days, IQR: 24-47). Static lung compliance was lower in non-survivors (p = 0.031) and differed over time (p = 0.049), decreasing by 48% compared to initial values in non-survivors. Conclusions: Our data suggest the importance of considering NIS among the common ECMO eligibility criteria and changes in lung compliance during ECMO as a prognostic marker.

Background and Objectives: Iodinated Contrast Media (ICM) is used daily in many imaging departments worldwide. The main risk associated with ICM is hypersensitivity. When a severe hypersensitivity reaction is not properly managed and treated swiftly, it may be fatal. Currently, there is no data to demonstrate how ICM sensitivity affects the prognosis of cardiac patients, especially those diagnosed with ST elevation myocardial infarction (STEMI), in whom urgent coronary angiography is indicated. This study aimed to identify and characterize this relationship. Materials and Methods: We included patients hospitalized with STEMI between 2016 and 2019 from the National Inpatient Sample. The population was compared based on ICM sensitivity status, sensitive vs. non-sensitive. The primary endpoint was in-hospital mortality, with additional endpoints: length of stay and in-hospital complications. Results: The study included 664,620 STEMI patients, of whom 4905 (0.7%) were diagnosed with ICM sensitivity. ICM-sensitive patients were older, more often white, females, and had more comorbidities and cardiovascular risk factors. Both groups show similarities in management but are slightly less probable to undergo PCI or CABG. Multivariable logistic regression models found that the ICM-sensitive population had similar odds of in-hospital mortality (OR: 1.02, 95% CI: 0.89-1.16) and MACCE (OR: 1.05, 95% CI: 0.95-1.16), and less major bleeding (OR: 0.73, 95% CI: 0.60-0.87). Conclusions: Our study found that ICM sensitivity status was not a significant factor for worse prognosis in patients hospitalized with STEMI.