Trends in hip fracture rates in spain from 2001 to 2018.

The present study includes the longest period of analysis with the highest number of hip fracture episodes (756,308) described in the literature for Spain. We found that the age-adjusted rates progressively decreased from 2005 to 2018. We believe that this is significant because it may mean that measures such as prevention and treatment of osteoporosis, or programs promoting healthy lifestyles, have had a positive impact on hip fracture rates. PURPOSE: To describe the evolution of cases and rates of hip fracture (HF) in patients 65 years or older in Spain from 2001 to 2018 and examine trends in adjusted rates. METHODS: Retrospective, observational study including patients ≥65 years with acute HF. Data from 2001 to 2018 were obtained from the Spanish National Record of the Minimum Basic Data Set of the Ministry of Health. We analysed cases of HF, crude incidence and age-adjusted rates by sex, length of hospital stay (LOS) and in-hospital mortality, and used joinpoint regression analysis to explore temporal trends. RESULTS: We identified 756,308 HF cases. Mean age increased 2.5 years, LOS decreased 4.5 days and in-hospital mortality was 5.5-6.5%. Cases of HF increased by 49%. Crude rate per 100,000 was 533.3 (95% confidence interval [CI], 532.1-534.5), increasing 14.0% (95%CI, 13.7-14.2). Age-adjusted HF incidence rate increased by 6.9% from 2001 (535.7; 95%CI, 529.9-541.5) to 2005 (572.4; 95%CI, 566.7-578.2), then decreased by 13.3% until 2017 (496.1, 95%CI, 491.7-500.6). Joinpoint regression analysis indicated a progressive increase in age-adjusted incidence rates of 1.9% per year from 2001 to 2005 and a progressive decrease of -1.1% per year from 2005 to 2018. A similar pattern was identified in both sexes. CONCLUSIONS: Crude incidence rates of HF in Spain in persons ≥65 years from 2001 to 2018 have gradually increased. Age-adjusted rates show a significant increase from 2001 to 2005 and a progressive decrease from 2005 to 2018.

Critical appraisal and assessment of bias among studies evaluating risk prediction models for in-hospital and 30-day mortality after percutaneous coronary intervention: a systematic review.

OBJECTIVE: We systematically assessed prediction models for the risk of in-hospital and 30-day mortality in post-percutaneous coronary intervention (PCI) patients. DESIGN: Systematic review and narrative synthesis. DATA SOURCES: Searched PubMed, Web of Science, Embase, Cochrane Library, CINAHL, CNKI, Wanfang Database, VIP Database and SinoMed for literature up to 31 August 2023. ELIGIBILITY CRITERIA: The included literature consists of studies in Chinese or English involving PCI patients aged ≥18 years. These studies aim to develop risk prediction models and include designs such as cohort studies, case-control studies, cross-sectional studies or randomised controlled trials. Each prediction model must contain at least two predictors. Exclusion criteria encompass models that include outcomes other than death post-PCI, literature lacking essential details on study design, model construction and statistical analysis, models based on virtual datasets, and publications such as conference abstracts, grey literature, informal publications, duplicate publications, dissertations, reviews or case reports. We also exclude studies focusing on the localisation applicability of the model or comparative effectiveness. DATA EXTRACTION AND SYNTHESIS: Two independent teams of researchers developed standardised data extraction forms based on CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies to extract and cross-verify data. They used Prediction model Risk Of Bias Assessment Tool (PROBAST) to assess the risk of bias and applicability of the model development or validation studies included in this review. RESULTS: This review included 28 studies with 38 prediction models, showing area under the curve values ranging from 0.81 to 0.987. One study had an unclear risk of bias, while 27 studies had a high risk of bias, primarily in the area of statistical analysis. The models constructed in 25 studies lacked clinical applicability, with 21 of these studies including intraoperative or postoperative predictors. CONCLUSION: The development of in-hospital and 30-day mortality prediction models for post-PCI patients is in its early stages. Emphasising clinical applicability and predictive stability is vital. Future research should follow PROBAST's low risk-of-bias guidelines, prioritising external validation for existing models to ensure reliable and widely applicable clinical predictions. PROSPERO REGISTRATION NUMBER: CRD42023477272.

Hospital accreditation in Mexico fails to improve the quality of healthcare: lessons from an impact evaluation.

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.

MORTALITY RISK ASSESSMENT AMONG PATIENTS, HOSPITALIZED FOR COVID-19.

In Georgia, the number of confirmed cases of Coronavirus were 1,85,5289. Among them, 17 132 patients died. Information on risk factors for mortality is insufficient. The purpose of our research is to evaluate clinical features of heavy patients with severe COVID and determine prognostic factors of outcome. Factors associated with critical COVID-19 included older age and certain chronic medical conditions. The clinical material of 250 chronically ill COVID-19 patients admitted to the intensive care unit was retrospectively studied. We divided the patients into two groups. The dead and the survivors. Demographic data, comorbidities, chronic diseases, results of ultrasound, cardiography, computed tomography and laboratory characteristics were studied. In patients with chronic diseases, in the intensive care unit during COVID-19, the relative chance of survival decreases: CRP3 - OR=0.98(95% CI:0.97-0.99Hydrothorax- OR=0.24(95% CI:0.06-0.95); Sepsis/Septic shock - OR=0.07(95% CI:0.01-0.39); WBC - OR=0.86(95% CI:0.74-0.99); Mechanical lung ventilation - OR=0.01(95% CI:0.00-0.05)); increase survival relative chance- pO2 - OR=1.03(95% CI:1.0-1.06). Predictors of mortality in patients with chronic diseases: coagulation characteristics, inflammatory markers, sepsis, and artificial lung ventilation. Risk factors for covid-19 mortality need to be studied to increase pandemic preparedness.

The prognostic value of the combined neutrophil-to-lymphocyte ratio (NLR) and neutrophil-to-platelet ratio (NPR) in sepsis.

Sepsis is a severe disease characterized by high mortality rates. Our aim was to develop an early prognostic indicator of adverse outcomes in sepsis, utilizing easily accessible routine blood tests. A retrospective analysis of sepsis patients from the MIMIC-IV database was conducted. We performed univariate and multivariate regression analyses to identify independent risk factors associated with in-hospital mortality within 28 days. Logistic regression was utilized to combine the neutrophil-to-lymphocyte ratio (NLR) and the neutrophil-to-platelet ratio (NPR) into a composite score, denoted as NLR_NPR. We used ROC curves to compare the prognostic performance of the models and Kaplan-Meier survival curves to assess the 28 day survival rate. Subgroup analysis was performed to evaluate the applicability of NLR_NPR in different subpopulations based on specific characteristics. This study included a total of 1263 sepsis patients, of whom 179 died within 28 days of hospitalization, while 1084 survived beyond 28 days. Multivariate regression analysis identified age, respiratory rate, neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-platelet ratio (NPR), hypertension, and sequential organ failure assessment (SOFA) score as independent risk factors for 28 day mortality in septic patients (P < 0.05). Additionally, in the prediction model based on blood cell-related parameters, the combined NLR_NPR score exhibited the highest predictive value for 28 day mortality (AUC = 0.6666), followed by NLR (AUC = 0.6456) and NPR (AUC = 0.6284). Importantly, the performance of the NLR_NPR score was superior to that of the commonly used SOFA score (AUC = 0.5613). Subgroup analysis showed that NLR_NPR remained an independent risk factor for 28 day in-hospital mortality in the subgroups of age, respiratory rate, and SOFA, although not in the hypertension subgroup. The combined use of NLR and NPR from routine blood tests represents a readily available and reliable predictive marker for 28 day mortality in sepsis patients. These results imply that clinicians should prioritize patients with higher NLR_NPR scores for closer monitoring to reduce mortality rates.

Long-term outcomes following mitral valve replacement in children at heart center Leipzig: a 20-year analysis.

BACKGROUND: Although mitral valve repair is the preferred surgical strategy in children with mitral valve disease, there are cases of irreparable severe dysplastic valves that require mitral valve replacement. The aim of this study is to analyze long-term outcomes following mitral valve replacement in children in a tertiary referral center. METHODS: A total of 41 consecutive patients underwent mitral valve replacement between February 2001 and February 2021. The study data was prospectively collected and retrospectively analyzed. Primary outcomes were in-hospital mortality, long-term survival, and long-term freedom from reoperation. RESULTS: Median age at operation was 23 months (IQR 5-93), median weight was 11.3 kg (IQR 4.8-19.4 kg). One (2.4%) patient died within the first 30 postoperative days. In-hospital mortality was 4.9%. Four (9.8%) patients required re-exploration for bleeding, and 2 (4.9%) patients needed extracorporeal life support. Median follow-up was 11 years (IQR 11 months - 16 years). Long-term freedom from re-operation after 1, 5, 10 and 15 years was 97.1%, 93.7%, 61.8% and 42.5%, respectively. Long-term survival after 1, 5, 10 and 15 years was 89.9%, 87%, 87% and 80.8%, respectively. CONCLUSION: If MV repair is not feasible, MV replacement offers a good surgical alternative for pediatric patients with MV disease. It provides good early- and long-term outcomes.

Sarcopenia, sarcopenic obesity and the clinical outcome of the older inpatients with COVID-19 infection: a prospective observational study.

OBJECTIVE: We aimed to investigate the impact of sarcopenia and sarcopenic obesity (SO) on the clinical outcome in older patients with COVID-19 infection and chronic disease. METHODS: We prospectively collected data from patients admitted to Huadong Hospital for COVID-19 infection between November 1, 2022, and January 31, 2023. These patients were included from a previously established comprehensive geriatric assessment (CGA) cohort. We collected information on their pre-admission condition regarding sarcopenia, SO, and malnutrition, as well as their medical treatment. The primary endpoint was the incidence of intubation, while secondary endpoints included in-hospital mortality rates. We then utilized Kaplan-Meier (K-M) survival curves and the log-rank tests to compare the clinical outcomes related to intubation or death, assessing the impact of sarcopenia and SO on patient clinical outcomes. RESULTS: A total of 113 patients (age 89.6 ± 7.0 years) were included in the study. Among them, 51 patients had sarcopenia and 39 had SO prior to hospitalization. Intubation was required for 6 patients without sarcopenia (9.7%) and for 18 sarcopenia patients (35.3%), with 16 of these being SO patients (41%). Mortality occurred in 2 patients without sarcopenia (3.3%) and in 13 sarcopenia patients (25.5%), of which 11 were SO patients (28%). Upon further analysis, patients with SO exhibited significantly elevated risks for both intubation (Hazard Ratio [HR] 7.43, 95% Confidence Interval [CI] 1.26-43.90, P < 0.001) and mortality (HR 6.54, 95% CI 1.09-39.38, P < 0.001) after adjusting for confounding factors. CONCLUSIONS: The prevalence of sarcopenia or SO was high among senior inpatients, and both conditions were found to have a significant negative impact on the clinical outcomes of COVID-19 infection. Therefore, it is essential to regularly assess and intervene in these conditions at the earliest stage possible.

Linguistic isolation correlates with length of stay and mortality for pediatric oncology patients in California.

OBJECTIVE: To evaluate social drivers of health and how they impact pediatric oncology patients' clinical outcomes during pediatric intensive care unit (PICU) admission via correlation with patient ZIP codes. METHODS: Demographic, clinical, and outcome variables from Virtual Pediatric Systems®, LLC for oncology patients (2009-2021) in California PICUs (excluding postoperative) using 3-digit ZIP Codes with social drivers of health variables linguistic isolation, poverty, race/ethnicity, and education abstracted from American Community Survey data for 3-digit ZIP Codes using the Environmental Protection Agency's EJScreen tool. Outcomes of length of stay (LOS), mortality, acuity scores, were compared with social variables. RESULTS: Positive correlation between mortality and minority racial groups (Hispanic/Latino) across ZIP Codes (correlation coefficients of 0.45 (95% CI: 0.22-0.64, p < 0.001) in 2017, 0.50 (95% CI: 0.27-0.68, p < 0.001) in 2018, 0.33 (95% CI: 0.07-0.54, p = 0.013) in 2020, and 0.32 (95% CI: 0.06-0.53, p = 0.018) in 2021). Median PICU length of stay significantly correlated with linguistic isolation (coefficient of 0.42 (95% CI: 0.18-0.61, p = 0.001) in 2021 versus -0.41 (95% CI: -0.61 to -0.16, p = 0.002) in 2019), which included PRISMIII (n = 7417). Mixed effects logistic regression model for other constant variables (PRISMIII, cancer type, race/ethnicity, year), random effect of patient, linguistic isolation (percentage as a continuous value) was significantly associated (95% CI: 1.01-1.06; p = 0.02) with mortality; (OR = 1.03). CONCLUSIONS: Linguistic isolation was correlated with LOS and mortality, however variable year to year.

A multivariable analysis to predict variations in hospital mortality using systems-based factors of healthcare delivery to inform improvements to healthcare design within the English NHS.

Over the last decade, the strain on the English National Health Service (NHS) has increased. This has been especially felt by acute hospital trusts where the volume of admissions has steadily increased. Patient outcomes, including inpatient mortality, vary between trusts. The extent to which these differences are explained by systems-based factors, and whether they are avoidable, is unclear. Few studies have investigated these relationships. A systems-based methodology recognises the complexity of influences on healthcare outcomes. Rather than clinical interventions alone, the resources supporting a patient's treatment journey have near-equal importance. This paper first identifies suitable metrics of resource and demand within healthcare delivery from routinely collected, publicly available, hospital-level data. Then it proceeds to use univariate and multivariable linear regression to associate such systems-based factors with standardised mortality. Three sequential cross-sectional analyses were performed, spanning the last decade. The results of the univariate regression analyses show clear relationships between five out of the six selected predictor variables and standardised mortality. When these five predicators are included within a multivariable regression analysis, they reliably explain approximately 36% of the variation in standardised mortality between hospital trusts. Three factors are consistently statistically significant: the number of doctors per hospital bed, bed occupancy, and the percentage of patients who are placed in a bed within four hours after a decision to admit them. Of these, the number of doctors per bed had the strongest effect. Linear regression assumption testing and a robustness analysis indicate the observations have internal validity. However, our empirical strategy cannot determine causality and our findings should not be interpreted as established causal relationships. This study provides hypothesis-generating evidence of significant relationships between systems-based factors of healthcare delivery and standardised mortality. These have relevance to clinicians and policymakers alike. While identifying causal relationships between the predictors is left to the future, it establishes an important paradigm for further research.

Clinical value identification of RDW on in-hospital death in unruptured abdominal aortic aneurysm.

This study aimed to identify highly valuable blood indicators for predicting the clinical outcomes of patients with aortic aneurysms (AA). Baseline data of 1180 patients and 16 blood indicators were obtained from the public Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. The association of blood indicators with 4 types of clinical outcomes was analyzed, and the prediction performance of core indicators on different outcomes was next evaluated. Then, we explored the detailed association between core indicators and key outcomes among subgroups. Finally, a machine learning model was established to improve the prediction performance. Generalized linear regression analysis indicated that only red cell volume distribution width (RDW) was commonly associated with 4 end-points including surgery requirement, ICU stay requirement, length of hospital stay, and in-hospital death (all P < .05). Further, RDW showed the best performance for predicting in-hospital death by receiver operating characteristic (ROC) analysis. The significant association between RDW and in-hospital death was then determined by 3 logistic regression models adjusting for different variables (all P < .05). Stratification analysis showed that their association was mainly observed in unruptured AA and abdominal AA (AAA, all P < .05). We subsequently established an RDW-based model for predicting the in-hospital death only in patients with unruptured AAA. The favorable prediction performance of the RDW-based model was verified in training, validation, and test sets. RDW was found to make the greatest contribution to in-hospital death within the model. RDW had favorable clinical value for predicting the in-hospital death of patients, especially in unruptured AAA.

A method for predicting mortality in acute mesenteric ischemia: Machine learning.

BACKGROUND: This study aimed to develop and validate an artificial intelligence model using machine learning (ML) to predict hospital mortality in patients with acute mesenteric ischemia (AMI). METHODS: A total of 122 patients diagnosed with AMI at Sakarya University Training and Research Hospital between January 2011 and June 2023 were included in the study. These patients were divided into a training cohort (n=97) and a validation cohort (n=25), and further categorized as survivors and non-survivors during hospitalization. Serum-based laboratory results served as features. Hyperfeatures were eliminated using Recursive Feature Elimination (RFE) in Python to optimize outcomes. ML algorithms and data analyses were performed using Python (version 3.7). RESULTS: Of the patients, 56.5% were male (n=69) and 43.5% were female (n=53). The mean age was 71.9 years (range 39-94 years). The mortality rate during hospitalization was 50% (n=61). To achieve optimal results, the model incorporated features such as age, red cell distribution width (RDW), C-reactive protein (CRP), D-dimer, lactate, globulin, and creatinine. Success rates in test data were as follows: logistic regression (LG), 80%; random forest (RF), 60%; k-nearest neighbor (KN), 52%; multilayer perceptron (MLP), 72%; and support vector classifier (SVC), 84%. A voting classifier (VC), aggregating votes from all models, achieved an 84% success rate. Among the models, SVC (sensitivity 1.0, specificity 0.77, area under the curve (AUC) 0.90, Confidence Interval (95%): (0.83-0.84)) and VC (sensitivity 1.0, specificity 0.77, AUC 0.88, Confidence Interval (95%): (0.83-0.84)) were noted for their effectiveness. CONCLUSION: Independent risk factors for mortality were identified in patients with AMI. An efficient and rapid method using various ML models to predict mortality has been developed.

A comparative assessment of ACS NSQIP-predicted and actual surgical risk outcomes of robotic transhiatal esophagectomy for esophageal adenocarcinoma resection at a high volume institution.

Esophageal adenocarcinoma incidence is increasing in Western nations. There has been a shift toward minimally invasive approaches for transhiatal esophagectomy (THE). This study compares the outcomes of robotic THE for esophageal adenocarcinoma resection at our institution with the predicted metrics from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). With Institutional Review Board (IRB) approval, we prospectively followed 83 patients who underwent robotic THE from 2012 to 2023. Predicted outcomes were determined using the ACS NSQIP Surgical Risk Calculator. Our outcomes were compared with these predicted outcomes and with general outcomes for transhiatal esophagectomy reported in ACS NSQIP, which includes a mix of surgical approaches. The median age of patients was 70 years, with a body mass index (BMI) of 26.4 kg/m2 and a male prevalence of 82%. The median length of stay was 7 days. The rates of any complications and in-hospital mortality were 16% and 5%, respectively. Seven patients (8%) were readmitted within a 30-day postoperative window. The median survival is anticipated to surpass 95 months. Our outcomes were generally aligned with or surpassed the predicted ACS NSQIP metrics. The extended median survival of over 95 months highlights the potential effectiveness of robotic THE in the resection of esophageal adenocarcinoma. Further exploration into its long-term survival benefits and outcomes is warranted, along with studies that provide a more direct comparison between robotic and other surgical approaches.

Endothelial biomarkers (Von willebrand factor, BDCA3, urokinase) as predictors of mortality in COVID-19 patients: cohort study.

BACKGROUND: SARS-CoV-2 is a systemic disease that affects endothelial function and leads to coagulation disorders, increasing the risk of mortality. Blood levels of endothelial biomarkers such as Von Willebrand Factor (VWF), Thrombomodulin or Blood Dendritic Cell Antigen-3 (BDCA3), and uUokinase (uPA) increase in patients with severe disease and can be prognostic indicators for mortality. Therefore, the aim of this study was to determine the effect of VWF, BDCA3, and uPA levels on mortality. METHODS: From May 2020 to January 2021, we studied a prospective cohort of hospitalized adult patients with polymerase chain reaction (PCR)-confirmed COVID-19 with a SaO2 ≤ 93% and a PaO2/FiO2 ratio < 300. In-hospital survival was evaluated from admission to death or to a maximum of 60 days of follow-up with Kaplan-Meier survival curves and Cox proportional hazard models as independent predictor measures of endothelial dysfunction. RESULTS: We recruited a total of 165 subjects (73% men) with a median age of 57.3 ± 12.9 years. The most common comorbidities were obesity (39.7%), hypertension (35.4%) and diabetes (30.3%). Endothelial biomarkers were increased in non-survivors compared to survivors. According to the multivariate Cox proportional hazard model, those with an elevated VWF concentration ≥ 4870 pg/ml had a hazard ratio (HR) of 4.06 (95% CI: 1.32-12.5) compared to those with a lower VWF concentration adjusted for age, cerebrovascular events, enoxaparin dose, lactate dehydrogenase (LDH) level, and bilirubin level. uPA and BDCA3 also increased mortality in patients with levels ≥ 460 pg/ml and ≥ 3600 pg/ml, respectively. CONCLUSION: The risk of mortality in those with elevated levels of endothelial biomarkers was observable in this study.

Machine learning-based prediction of clinical outcomes after traumatic brain injury: Hidden information of early physiological time series.

AIMS: To assess the predictive value of early-stage physiological time-series (PTS) data and non-interrogative electronic health record (EHR) signals, collected within 24 h of ICU admission, for traumatic brain injury (TBI) patient outcomes. METHODS: Using data from TBI patients in the multi-center eICU database, we focused on in-hospital mortality, neurological status based on the Glasgow Coma Score (mGCS) motor subscore at discharge, and prolonged ICU stay (PLOS). Three machine learning (ML) models were developed, utilizing EHR features, PTS signals collected 24 h after ICU admission, and their combination. External validation was performed using the MIMIC III dataset, and interpretability was enhanced using the Shapley Additive Explanations (SHAP) algorithm. RESULTS: The analysis included 1085 TBI patients. Compared to individual models and existing scoring systems, the combination of EHR and PTS features demonstrated comparable or even superior performance in predicting in-hospital mortality (AUROC = 0.878), neurological outcomes (AUROC = 0.877), and PLOS (AUROC = 0.835). The model's performance was validated in the MIMIC III dataset, and SHAP algorithms identified six key intervention points for EHR features related to prognostic outcomes. Moreover, the EHR results (All AUROC >0.8) were translated into online tools for clinical use. CONCLUSION: Our study highlights the importance of early-stage PTS signals in predicting TBI patient outcomes. The integration of interpretable algorithms and simplified prediction tools can support treatment decision-making, contributing to the development of accurate prediction models and timely clinical intervention.

Prognostic Significance of Thrombocytopenia and Mean Platelet Volume in COPD Patients with Acute Exacerbations in ICU Settings.

BACKGROUND Platelets have important modulatory effects on inflammatory and immune-mediated pathways. Thrombocytopenia is a critical condition that is frequently encountered in the intensive care unit (ICU) and increases mortality. This retrospective study of 472 patients admitted to the ICU with acute exacerbation of chronic obstructive pulmonary disease (COPD) aimed to evaluate thrombocytopenia and mean platelet volume (MPV) with prognosis and patient mortality. MATERIAL AND METHODS A total of 472 patients diagnosed with COPD according to GOLD criteria and hospitalized in the tertiary ICU between 1 April 2018 and 11 May 2021 were included in the study. Platelets were calculated by the impetance method and MPV was simultaneously calculated based on the platelet histogram. Patients with platelet count ≤100×109/L and >100×109/L and patients with MPV values <7 fl, 7-11 fl, and >11fl were compared in terms of mortality and prognosis. RESULTS The mortality rate in COPD patients with thrombocytopenia was high, at 61.5%. Thrombocytopenia (P=.002), high MPV (P=.006) Acute Physiology and Chronic Health Evaluation-2 (APACHE-II) score (P=.025), length of stay (LOS) in the ICU (P=.009), mechanical ventilation duration (P<.001), leukocytosis (P<.001), high Sequential Organ Failure Assessment (SOFA) score (P<.001), LOS in the hospital (P=.035), and hypoalbuminemia (P<.001) were significantly associated with mortality. CONCLUSIONS Thrombocytopenia, high MPV, high APACHE-II and SOFA scores, LOS in the ICU and hospital, duration of mechanical ventilation, leukocytosis, and hypoalbuminemia predict mortality in COPD patients. Since infection-sepsis, hypoalbuminemia, and hypoxia can worsen this situation, ensuring early infection control, providing albumin support, and preventing hypoxia contribute significantly to reducing thrombocytopenia and mortality.

Temporal trends and prognostic impact of reperfusion modalities in Tunisian patients presenting with ST-elevation myocardial infarction: A 20-year analysis.

INTRODUCTION: With the advent of reperfusion therapies, management of patients presenting with ST-elevation myocardial infarction (STEMI) has witnessed significant changes during the last decades. AIM: We sought to analyze temporal trends in reperfusion modalities and their prognostic impact over a 20-year period in patients presenting with STEMI the Monastir region (Tunisia). METHODS: Patients from Monastir region presenting for STEMI were included in a 20-year (1998-2017) single center registry. Reperfusion modalities, early and long-term outcomes were studied according to five four-year periods. RESULTS: Out of 1734 patients with STEMI, 1370 (79%) were male and mean age was 60.3 ± 12.7 years. From 1998 to 2017, primary percutaneous coronary intervention (PCI) use significantly increased from 12.5% to 48.3% while fibrinolysis use significantly decreased from 47.6% to 31.7% (p<0.001 for both). Reperfusion delays for either fibrinolysis or primary PCI significantly decreased during the study period. In-hospital mortality significantly decreased from 13.7% during Period 1 (1998-2001) to 5.4% during Period 5 (2014-2017), (p=0.03). Long-term mortality rate (mean follow-up 49.4 ± 30.7 months) significantly decreased from 25.3% to 13% (p<0.001). In multivariate analysis, age, female gender, anemia on-presentation, akinesia/dyskinesia of the infarcted area and use of plain old balloon angioplasty were independent predictors of death at long-term follow-up whereas primary PCI use and preinfaction angina were predictors of long-term survival. CONCLUSIONS: In this long-term follow-up study of Tunisian patients presenting for STEMI, reperfusion delays decreased concomitantly to an increase in primary PCI use. In-hospital and long-term mortality rates significantly decreased from 1998 to 2017.

Unplanned Hospital Admissions in Patients With Solid Tumors in Brazil: Causes and Progressive Disease's Impact on Outcomes.

PURPOSE: Most patients with cancer will be hospitalized throughout the disease course. However, most evidence on the causes and outcomes of these hospitalizations comes from administrative data or small retrospective studies from high-income countries. METHODS: This study is a retrospective cohort of patients with solid tumors hospitalized from February 1, 2021, to December 31, 2021, in a tertiary cancer center in São Paulo, Brazil. We collected data on cancer diagnosis, symptoms at admission, hospitalization diagnosis, and survival clinical outcomes during in-hospital stay (in-hospital mortality) and after discharge (readmission rates and overall survival [OS]). Progressive disease (PD) diagnosis during admission was retrieved from manual chart review if explicitly stated by the attending physician. We modeled in-hospital mortality and postdischarge OS with logistic regression and Cox proportional hazards models, respectively. RESULTS: A total of 3,726 unique unplanned admissions were identified. The most common symptoms at admission were pain (40.6%), nausea (16.8%), and dyspnea (16.1%). PD (34.0%), infection (31.1%), and cancer pain (13.4%) were the most frequent reasons for admission. The in-hospital mortality rate was 18.9%. Patients with PD had a high in-hospital mortality rate across all tumor groups and higher odds of in-hospital death (odds ratio, 3.5 [95% CI, 3.0 to 4.2]). The 7-, 30-, and 90-day readmission rates were 11.9%, 33.5%, and 54%, respectively. The postdischarge median OS (mOS) was 12.6 months (95% CI, 11.6 to 13.7). Poorer postdischarge survival was observed among patients with PD (mOS, 5 months v 18 months; P < .001; hazard ratio, 2.4 [95% CI, 2.1 to 2.6]). CONCLUSION: PD is a common diagnosis during unplanned hospitalizations and is associated with higher in-hospital mortality rates and poorer OS after discharge. Oncologists should be aware of the prognostic implications of PD during admission and align goals of care with their patients.

[A multicenter clinical study of critically ill patients with sepsis complicated with acute kidney injury in Beijing: incidence, clinical characteristics and outcomes].

OBJECTIVE: To investigate the epidemiological characteristics and prognosis of critically ill patients with sepsis combined with acute kidney injury (AKI) in intensive care unit (ICU) in Beijing, and to analyze the risk factors associated with in-hospital mortality among these critically ill patients. METHODS: Data were collected from the Beijing AKI Trial (BAKIT) database, including 9 049 patients consecutively admitted to 30 ICUs in 28 tertiary hospitals in Beijing from March 1 to August 31, 2012. Patients were divided into non-AKI and non-sepsis group, AKI and non-sepsis group, non-AKI and sepsis group, AKI and sepsis group. Clinical data recorded included demographic characteristics, primary reasons for ICU admission, comorbidities, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation II(APACHE II) within 24 hours of ICU admission, physiological and laboratory indexes, treatment in the ICU, AKI staging based on the Kidney Disease: Improving Global Outcomes (KDIGO), as well as the prognostic indicators including length of stay in ICU, length of stay in hospital, ICU and in-hospital mortality. The primary endpoint was discharge or in-hospital death. Multivariate Logistic regression analysis was used to investigate the risk factors for hospital death in ICU patients. Kaplan-Meier survival curve was drawn to analyze the cumulative survival of ICU patients during hospitalization. RESULTS: A total of 3 107 critically ill patients were ultimately enrolled, including 1 259 cases in the non-AKI and non-sepsis group, 931 cases in the AKI and non-sepsis group, 264 cases in the non-AKI and sepsis groups, and 653 cases in the AKI and sepsis group. Compared with the other three group, patients in the AKI and sepsis group were the oldest, had the lowest mean arterial pressure (MAP), and the highest APACHE II score, SOFA score, blood urea nitrogen (BUN), and serum creatinine (SCr) levels, and they also had the highest proportion of receiving mechanical ventilation, requiring vasopressor support, and undergoing renal replacement therapy (RRT), all P < 0.01. Of these 3 107 patients, 1 584 (51.0%) were diagnosed with AKI, and the incidence of AKI in patients with sepsis was significantly higher than in those without sepsis [71.2% (653/917) vs. 42.5% (931/2 190), P < 0.01]. The highest proportion of KDIGO 0 stage was observed in the non-sepsis group (57.5%), while the highest proportion of KDIGO 3 stage was observed in the sepsis group (32.2%). Within the same KDIGO stage, the mortality of patients with sepsis was significantly higher than that of non-sepsis patients (0 stage: 17.8% vs. 3.1%, 1 stage: 36.3% vs. 7.4%, 2 stage: 42.7% vs. 17.1%, 3 stage: 54.6% vs. 28.6%, AKI: 46.1% vs. 14.2%). The ICU mortality (38.7%) and in-hospital mortality (46.1%) in the AKI and sepsis group were significantly higher than those in the other three groups. Kaplan-Meier survival curves further showed that the cumulative survival rate of patients with AKI and sepsis during hospitalization was significantly lower than that of the other three groups (53.9% vs. 96.9%, 85.8%, 82.2%, Log-Rank: χ 2 = 379.901, P < 0.001). Subgroup analysis showed that among surviving patients, length of ICU stay and total length of hospital stay were significantly longer in the AKI and sepsis group than those in the other three groups (both P < 0.01). Multivariate regression analysis showed that age, APACHE II score and SOFA score within 24 hours of ICU admission, coronary heart disease, AKI, sepsis, and AKI combined with sepsis were independent risk factors for ICU mortality in patients (all P < 0.05). After adjusting for covariates, AKI, sepsis, and sepsis combined with AKI were significantly associated with higher ICU and in-hospital mortality, with the highest ICU mortality [adjusted odds ratio (OR) = 14.82, 95% confidence interval (95%CI) was 8.10-27.12; Hosmer-Lemeshow test: P = 0.816] and in-hospital mortality (adjusted OR = 7.40, 95%CI was 4.94-11.08; Hosmer-Lemeshow test: P = 0.708) observed in patients with sepsis combined with AKI. CONCLUSIONS: The incidence of AKI is high in sepsis patients, and those with both AKI and sepsis have a higher disease burden, more abnormalities in physiological and laboratory indicators, and significantly increased ICU and in-hospital mortality. Among surviving patients, the length of ICU stay and total length of hospital stay are also longer in the AKI and sepsis group. Age, APACHE II score and SOFA score within 24 hours of ICU admission, coronary heart disease, AKI, and sepsis are independent risk factors for in-hospital mortality in ICU patients.

[Epidemiological analysis of in patients with sepsis in a large tertiary general hospital in Southwest China].

OBJECTIVE: To analyze the epidemiological characteristics of hospitalized patients diagnosed with sepsis in a large class III general hospital in Southwest China in a period of 2 years, and to explore the risk factors related to death in patients with sepsis. METHODS: A retrospective study was conducted to select patients with sepsis admitted to Sichuan Provincial People's Hospital from September 1, 2021 to August 31, 2023, and general characteristics such as gender, age, discharge diagnosis, discharge department, hospitalization cost, length of stay, and prognosis during hospitalization were collected. The baseline of two groups of patients was compared, and the risk factors of in-hospital cause of death in patients with sepsis were analyzed by multivariate Logistic regression. RESULTS: A total of 3 568 patients with sepsis were included with median age of 58 (35, 74) years old. Of all patients, there were 2 147 males (60.17%). The median length of hospitalization was 13 (8, 24) days, and the median hospitalization cost was 3.98 (1.87, 8.83) ten thousand yuan. The departments with more than 100 cases of sepsis in 2 years were central intensive care unit (ICU), pediatrics department, nephrology department, emergency medicine department, emergency intensive care unit (EICU), infectious department, respiratory medicine department, hematology department, neonatal care unit and emergency surgical department. A total of 1 210 patients (33.91%) admitted to ICU (including central ICU and EICU). The hospitalization cost of ICU patients were higher [6.7 (3.1, 15.5) ten thousand yuan], the hospitalization duration was longer [9 (3, 17) days], and the mortality was higher [35.29% (427/1 210)]. Among 3 568 patients with sepsis, 448 died and 3 120 survived during hospitalization. The age, male proportion and hospitalization cost of patients with sepsis in the death group were significantly higher than those in the survival group [age (years old): 75 (60, 86) vs. 57 (30, 71), male proportion: 67.86% (304/448) vs. 59.07% (1 843/3 120), hospitalization cost (ten thousand yuan): 6.7 (3.0, 16.9) vs. 3.7 (1.8, 8.1)], the ratio of diabetes mellitus was significantly lower than that of survival group [4.91% (22/448) vs. 10.45% (326/3 120)], the length of hospitalization was shorter than that of survival group [days: 10.0 (3.0, 19.0) vs. 13.0 (8.0, 24.0)], the differences were statistically significant (all P < 0.01). Multivariate Logistic regression analysis showed that male [odds ratio (OR) = 0.75, 95% confidence interval (95%CI) was 0.59-0.96], elder (OR = 1.04, 95%CI was 1.03-1.05) and diabetes (OR = 0.32, 95%CI was 0.19-0.54) were independent risk factors for in-hospital death in patients with sepsis (all P < 0.05). CONCLUSIONS: Sepsis is a heavy burden in Southwest China, especially for ICU, with high mortality, high hospitalization costs, and heavy economic burden on patients and society. Male, elder and diabetes were independent risk factors for in-hospital death of sepsis patients.

Comparative analysis of geriatric hip fracture management outcomes in teaching and nonteaching hospitals in Jordan.

Hip fractures are common orthopedic injuries that have significant impacts on patients and healthcare systems. Previous studies have shown varying outcomes for hip fracture management in different settings, with diverse postoperative outcomes and complications. While teaching hospital settings have been investigated, no studies have specifically examined hip fracture outcomes in teaching hospitals in Jordan or the broader Middle East region. Therefore, the aim of this study was to investigate this important outcome. A cohort comprising 1268 patients who underwent hip fracture fixation from 2017 to 2020 was analyzed for nine distinct outcomes. These outcomes encompassed time to surgery, ICU admissions, perioperative hemoglobin levels, length of hospital stay, readmission rates, revision procedures, and mortality rates at three time points: in-hospital, at 6-months, and at 1-year post-surgery. The analysis of 1268 patients (616 in teaching hospitals, 652 in non-teaching hospitals) showed shorter mean time to surgery in teaching hospitals (2.2 days vs. 3.6 days, p < 0.01), higher ICU admissions (17% vs. 2.6%, p < 0.01), and more postoperative blood transfusions (40.3% vs. 12.1%, p < 0.01). In-hospital mortality rates were similar between groups (2.4% vs. 2.1%, p = 0.72), as were rates at 6-months (3.1% vs. 3.5%, p = 0.65) and 1-year post-surgery (3.7% vs. 3.7%, p = 0.96). Geriatric hip fracture patients in teaching hospitals have shorter surgery times, more ICU admissions, and higher postoperative blood transfusion rates. However, there are no significant differences in readmission rates, hospital stays, or mortality rates at various intervals.