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.

Few studies have examined the risk factors associated with the type of acute respiratory failure (ARF) in patients with acute exacerbation of chronic obstructive pulmonary disease (COPD). This study evaluated the clinical characteristics and prognosis of patients hospitalized for acute exacerbation of COPD based on the type of ARF. The medical charts of hospitalized patients with acute exacerbation of COPD between 2016 and 2021 were retrospectively reviewed. We classified ARF into 2 types: type 1 ARF with PaO2 < 60 mm Hg in room air or a ratio of arterial partial pressure to fractional inspired oxygen < 300, and type 2 ARF with PaCO2 > 45 mm Hg and arterial pH < 7.35. A total of 435 patients were enrolled in study, including 170 participants without ARF, 165 with type 1 ARF, and 100 with type 2 ARF. Compared with the non-ARF group, the frequency of high-flow nasal cannula, noninvasive ventilation, intensive care unit admissions, and in-hospital deaths was higher in the ARF group compared with the non-ARF group. The ARF group had higher 1-year mortality group (hazard ratio [HR], 2.809; 95% confidence interval [CI], 1.099-7.180; P = .031) and readmission within 1-year rates (HR, 1.561; 95% CI, 1.061-2.295; P = .024) than the non-ARF group. The type 1 ARF group had a higher risk of 1-year mortality (HR, 3.022; 95% CI, 1.041-8.774; P = .042) and hospital readmission within 1-year (HR, 2.053; 95% CI, 1.230-3.428; P = .006) compared with the non-ARF group. There was no difference in mortality and readmission rates between the type 1 and type 2 ARF groups. In conclusion, patients with type 1 ARF rather than type 2 ARF had higher mortality and readmission rates than those without ARF. The prognoses of patients with type 1 and type 2 ARF were similar.

Elevated red blood cell distribution width (RDW) can be associated with disease severity. However, studies on RDW for the prognosis of elderly patients with non-traumatic coma (NTC) are lacking. This study aims to examine the relationship between RDW and outcomes in elderly patients with NTC. This observational cohort study included elderly patients (aged ≥ 65 years) with NTC between January 2022 and December 2022. We measured RDW upon patient arrival at the emergency department (ED). We conducted a multivariable analysis using logistic regression of relevant covariates to predict in-hospital mortality. Survival curves based on 30-day mortality were designed using the Kaplan-Meier method. The primary outcome was in-hospital mortality, and the secondary outcome was 30-day mortality. A total of 689 patients were included in the study, and in-hospital mortality was 29.6% (n = 204). Our results found that the RDWs of non-survivors were significantly greater than those of survivors (14.6% vs 13.6%). Multivariable analysis showed that RDWs at ED arrival were independently associated with in-hospital mortality (odds ratio, 1.126; 95% confidence interval, 1.047-1.212; P < .001). The Kaplan-Meier curve indicated that the survival probability of patients with a low RDW was greater than those with a high RDW. Having a high RDW at ED arrival was associated with in-hospital mortality in elderly patients with NTC.

Cardiovascular surgery risk prediction models are widely applied in medical practice. However, they have been criticized for their low methodological quality and scarce external validation. An additional limitation added in Latin America is that most of these models have been developed in the United States or Europe, which present marked geographical differences. The objective of this study is to characterize the postoperative clinical events of cardiovascular surgeries with the use of cardiopulmonary bypass pump in a local setting and to evaluate the prediction of postoperative mortality using the EuroSCORE II predictive model.
Cross-sectional study in an urban university hospital in Buenos Aires. Patients ≥21 years of age were included, with a clinical indication for on-pump cardiovascular surgery. Patients with incomplete clinical data regarding EuroSCORE II variables or in-hospital survival, ≥95 years of age, or undergoing heart transplantation were excluded.
195 patients were enrolled. Postoperative mortality estimated by EuroSCORE II presented a clear underestimation of risk (3.0% vs 7.7%). Discrimination (AUC = 0.82; 95% CI 0.74-0.92) and goodness of fit of the model were adequate (χ2 = 7.91; p = 0.4418). The most frequent postoperative complications were postoperative heart failure (35.9%), vasoplegic shock (13.3%), and cardiogenic shock (10.26%).
The EuroSCORE II is an appropriate tool to discriminate between different risk categories in patients undergoing on-pump cardiovascular surgery, although it underestimates the risk.
Los modelos de predicción de riesgo de cirugías cardiovasculares se aplican ampliamente a la práctica médica. Sin embargo, han sido criticados por su baja calidad metodológica y escasa validación externa. En América Latina se agrega la limitación de que la mayoría de estos modelos fueron desarrollados en Estados Unidos o Europa, existiendo diferencias geográficas marcadas.
El objetivo de este estudio es caracterizar los eventos clínicos postoperatorios de cirugías cardiovasculares con uso de bomba de circulación extracorpórea en un escenario local y evaluar la predicción de mortalidad postoperatoria del modelo predictivo EuroSCORE II.
Corte transversal en un hospital universitario urbano de Buenos Aires. Se incluyeron a pacientes ≥21 años de edad, con indicación de cirugía cardiovascular con uso de bomba. Se excluyeron a pacientes con datos clínicos incompletos respecto a las variables del EuroSCORE II o respecto a la sobrevida intrahospitalaria, con ≥95 años de edad o sometidos a trasplante cardíaco.
Se enrolaron 195 pacientes. La mortalidad postoperatoria estimada por el EuroSCORE II presentó una clara subestimación del riesgo (3,0% vs 7,7%). La discriminación (AUC = 0,82; IC95% 0,74-0,92) y la bondad del ajuste del modelo fueron adecuadas (χ2 = 7,91; p = 0,4418). Las complicaciones postoperatorias más frecuentes fueron insuficiencia cardíaca postoperatoria (35,9%), shock vasopléjico (13,3%) y shock cardiogénico (10,26%).
El EuroSCORE II es una herramienta apropiada para discriminar entre diferentes categorías de riesgo en pacientes sometidos a cirugías cardiovasculares con uso de bomba, si bien subestima el riesgo.

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.

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: Research on the impact of reduced time to emergent surgery in trauma patients has yielded inconsistent results. Therefore, this study investigated the relationship between waiting emergent surgery time (WEST) and outcomes in trauma patients. Methods: This retrospective, multicenter study used data from the Tzu Chi Hospital trauma database. The primary clinical outcomes were in-hospital mortality, intensive care unit (ICU) admission, and prolonged hospital length of stay (LOS) of ≥30 days. Results: A total of 15,164 patients were analyzed. The median WEST was 444 min, with an interquartile range (IQR) of 248-848 min for all patients. Patients who died in the hospital had a shorter median WEST than did those who survived (240 vs. 446 min, p < 0.001). Among the trauma patients with a WEST of <2 h, the median time was 79 min (IQR = 50-100 min). No significant difference in WEST was observed between the survival and mortality groups for patients with a WEST of <120 min (median WEST: 85 vs. 78 min, p < 0.001). Multivariable logistic regression analysis revealed that WEST was not associated with an increased risk of in-hospital mortality (adjusted odds ratio [aOR] = 1.05, 95% confidence interval [CI] = 0.17-6.35 for 30 min ≤ WEST < 60 min; aOR = 1.12, 95% CI = 0.22-5.70 for 60 min ≤ WEST < 90 min; and aOR = 0.60, 95% CI = 0.13-2.74 for WEST ≥ 90 min). Conclusions: Our findings do not support the \"golden hour\" concept because no association was identified between the time to definitive care and in-hospital mortality, ICU admission, and prolonged hospital stay of ≥30 days.

BACKGROUND: Previous studies have shown that an elevated triglyceride-glucose (TyG) index was associated with all-cause mortality in both general adult individuals and critically ill adult patients. However, the relationship between the TyG index and clinical prognosis in pediatric patients admitted to the intensive care unit (ICU) remains unknown. We aimed to investigate the association of the TyG index with in-hospital all-cause mortality in critically ill pediatric patients.
METHODS: A total of 5706 patients in the Pediatric Intensive Care database were enrolled in this study. The primary outcome was 30-day in-hospital all-cause mortality, and secondary outcome was 30-day in-ICU all-cause mortality. The restricted cubic spline (RCS) curves and two-piecewise multivariate Cox hazard regression models were performed to explore the relationship between the TyG index and outcomes.
RESULTS: The median age of the study population was 20.5 [interquartile range (IQR): 4.8, 63.0] months, and 3269 (57.3%) of the patients were male. The mean TyG index level was 8.6 ± 0.7. A total of 244 (4.3%) patients died within 30 days of hospitalization during a median follow-up of 11 [7, 18] days, and 236 (4.1%) patients died in ICU within 30 days of hospitalization during a median follow-up of 6 [3, 11] days. The RCS curves indicated a U-shape association between the TyG index and 30-day in-hospital and in-ICU all-cause mortality (both P values for non-linear < 0.001). The risk of 30-day in-hospital all-cause mortality was negatively correlated with the TyG index until it bottoms out at 8.6 (adjusted hazard ratio [HR], 0.72, 95% confidence interval [CI] 0.55-0.93). However, when the TyG index was higher than 8.6, the risk of primary outcome increased significantly (adjusted HR, 1.51, 95% CI 1.16-1.96]). For 30-day in-ICU all-cause mortality, we also found a similar relationship (TyG < 8.6: adjusted HR, 0.75, 95% CI 0.57-0.98; TyG ≥ 8.6: adjusted HR, 1.42, 95% CI 1.08-1.85). Those results were consistent in subgroups and various sensitivity analysis.
CONCLUSIONS: Our study showed that the association between the TyG index and 30-day in-hospital and in-ICU all-cause mortality was nonlinear U-shaped, with a cutoff point at the TyG index of 8.6 in critically ill pediatric patients. Our findings suggest that the TyG index may be a novel and important factor for the short-term clinical prognosis in pediatric patients.

BACKGROUND: The operative outcomes of thoracoabdominal aortic aneurysms (TAAAs) are challenged by high operative mortality and disabling complications. This study aimed to explore the baseline clinical, anatomical, and procedural risk factors that impact early and late outcomes following open repair of TAAAs.
METHODS: We reviewed the medical records of 290 patients who underwent open repair of TAAAs between 1992 and 2020 at a tertiary referral center. Determinants of early mortality (within 30 days or in hospital) were analyzed using multivariable logistic regression models, while those of overall follow-up mortality were explored using multivariable Cox proportional hazards models and landmark analyses.
RESULTS: The rates of early mortality and spinal cord deficits were 13.1% and 11.0%, respectively, with Crawford extent II showing the highest rates. In the logistic regression models, older age (P < 0.001), high cardiopulmonary bypass (CPB) time (P < 0.001), and low surgical volume of the surgeon (P < 0.001) emerged as independent factors significantly associated with early mortality. During follow-up (median, 5.0 years; interquartile range, 1.1-7.6 years), 82 late deaths occurred (5.7%/patient-year). Cox proportional hazards models demonstrated that older age (P < 0.001) and low hemoglobin level (P = 0.032) were significant risk factors of overall mortality, while the landmark analyses revealed that the significant impacts of low surgical volume (P = 0.017), high CPB time (P = 0.002), and Crawford extent II (P = 0.017) on mortality only remained in the early postoperative period, without significant late impacts (all P > 0.05).
CONCLUSIONS: There were differential temporal impacts of perioperative risk variables on mortality in open repair of TAAAs, with older age and low hemoglobin level having significant impacts throughout the postoperative period, and low surgical volume, high CPB time, and Crawford extent II having impacts in the early postoperative phase.

Individuals affected by human immunodeficiency virus (HIV) have a growing demand for coronary artery bypass grafting (CABG) due to heightened risk for cardiovascular diseases and extended life expectancy. However, CABG outcomes in HIV patients are not well-established, with insights only from small case series studies. This study conducted a comprehensive, population-based examination of in-hospital CABG outcomes in HIV patients. Patients underwent CABG were identified in National Inpatient Sample from Q4 2015-2020. Patients with age < 18 years and concomitant procedures were excluded. A 1:5 propensity-score matching was used to address preoperative group differences. Among patients who underwent CABG, 613 (0.36%) had HIV and were matched to 3119 out of 167,569 non-HIV patients. For selected HIV patients, CABG is relatively safe, presenting largely similar outcomes. After matching, HIV and non-HIV patients had comparable in-hospital mortality rates (2.13% vs. 1.67%, p = 0.40). Risk factors associated with mortality among HIV patients included previous CABG (aOR = 14.32, p = 0.01), chronic pulmonary disease (aOR = 8.24, p < 0.01), advanced renal failure (aOR = 7.49, p = 0.01), and peripheral vascular disease (aOR = 6.92, p = 0.01), which can be used for preoperative risk stratification. While HIV patients had higher acute kidney injury (AKI; 26.77% vs. 21.77%, p = 0.01) and infection (8.21% vs. 4.18%, p < 0.01), other complications were comparable between the groups.