Higher Risk Of In-hospital Mortality Research Articles

Screening Oropharyngeal Dysphagia in Older Adults

This study investigated the use of the Eating Assessment Tool 10 (EAT-10) in predicting clinical outcomes in older adults hospitalized with COVID-19 infections between February and June 2021. The EAT-10 was performed for all patients. Thirty one percent and 23% of the 153 patients had oropharyngeal dysphagia risk and in-hospital mortality, respectively. Older age (hazard ratio: 1.08; 95% confidence interval, 1.03-1.13; P = .003) and higher EAT-10 score (hazard ratio: 1.02; 95% confidence interval, 1.01-1.04; P = .043) were associated with in-hospital mortality. Older age and having increased risk of oropharyngeal dysphagia were independently associated with a higher risk of in-hospital mortality in older patients with COVID-19.

Establishment and validation of an artificial intelligence web application for predicting postoperative in-hospital mortality in patients with hip fracture: a National cohort study of 52,707 cases.

In-hospital mortality following hip fractures is a significant concern, and accurate prediction of this outcome is crucial for appropriate clinical management. Nonetheless, there is a lack of effective prediction tools in clinical practice. By utilizing artificial intelligence and machine learning techniques, this study aims to develop a predictive model that can assist clinicians in identifying geriatric hip fracture patients at a higher risk of in-hospital mortality. A total of 52,707 geriatric hip fracture patients treated with surgery from 90 hospitals were included in this study. The primary outcome was postoperative in-hospital mortality. The patients were randomly divided into two groups, with a ratio of 7:3. The majority of patients, assigned to the training cohort, were used to develop the AI models. The remaining patients, assigned to the validation cohort, were used to validate the models. Various machine learning algorithms, including logistic regression (LR), decision tree (DT), naïve Bayesian (NB), neural network (NN), eXGBoosting machine (eXGBM), and random forest (RF), were employed for model development. A comprehensive scoring system, incorporating 10 evaluation metrics, was developed to assess the prediction performance, with higher scores indicating superior predictive capability. Based on the best machine learning-based model, an AI application was developed on the Internet. In addition, a comparative testing of prediction performance between doctors and the AI application. The eXGBM model exhibited the best prediction performance, with an AUC of 0.908 (95% CI: 0.881-0.932), as well as the highest accuracy (0.820), precision (0.817), specificity (0.814), and F1 score (0.822), and the lowest Brier score (0.120) and log loss (0.374). Additionally, the model showed favorable calibration, with a slope of 0.999 and an intercept of 0.028. According to the scoring system incorporating 10 evaluation metrics, the eXGBM model achieved the highest score (56), followed by the RF model (48) and NN model (41). The LR, DT, and NB models had total scores of 27, 30, and 13, respectively. The AI application has been deployed online at https://in-hospitaldeathinhipfracture-l9vhqo3l55fy8dkdvuskvu.streamlit.app/, based on the eXGBM model. The comparative testing revealed that the AI application's predictive capabilities significantly outperformed those of the doctors in terms of AUC values (0.908 vs. 0.682, P<0.001). The eXGBM model demonstrates promising predictive performance in assessing the risk of postoperative in-hospital mortality among geriatric hip fracture patients. The developed AI model serves as a valuable tool to enhance clinical decision-making.

Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study.

Acute myocardial infarction (AMI) is one of the most severe cardiovascular diseases and is associated with a high risk of in-hospital mortality. However, the current deep learning models for in-hospital mortality prediction lack interpretability. This study aims to establish an explainable deep learning model to provide individualized in-hospital mortality prediction and risk factor assessment for patients with AMI. In this retrospective multicenter study, we used data for consecutive patients hospitalized with AMI from the Chongqing University Central Hospital between July 2016 and December 2022 and the Electronic Intensive Care Unit Collaborative Research Database. These patients were randomly divided into training (7668/10,955, 70%) and internal test (3287/10,955, 30%) data sets. In addition, data of patients with AMI from the Medical Information Mart for Intensive Care database were used for external validation. Deep learning models were used to predict in-hospital mortality in patients with AMI, and they were compared with linear and tree-based models. The Shapley Additive Explanations method was used to explain the model with the highest area under the receiver operating characteristic curve in both the internal test and external validation data sets to quantify and visualize the features that drive predictions. A total of 10,955 patients with AMI who were admitted to Chongqing University Central Hospital or included in the Electronic Intensive Care Unit Collaborative Research Database were randomly divided into a training data set of 7668 (70%) patients and an internal test data set of 3287 (30%) patients. A total of 9355 patients from the Medical Information Mart for Intensive Care database were included for independent external validation. In-hospital mortality occurred in 8.74% (670/7668), 8.73% (287/3287), and 9.12% (853/9355) of the patients in the training, internal test, and external validation cohorts, respectively. The Self-Attention and Intersample Attention Transformer model performed best in both the internal test data set and the external validation data set among the 9 prediction models, with the highest area under the receiver operating characteristic curve of 0.86 (95% CI 0.84-0.88) and 0.85 (95% CI 0.84-0.87), respectively. Older age, high heart rate, and low body temperature were the 3 most important predictors of increased mortality, according to the explanations of the Self-Attention and Intersample Attention Transformer model. The explainable deep learning model that we developed could provide estimates of mortality and visual contribution of the features to the prediction for a patient with AMI. The explanations suggested that older age, unstable vital signs, and metabolic disorders may increase the risk of mortality in patients with AMI.

Global longitudinal strain as a predictor of mortality in patients with cardiogenic shock

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Aarhus University Dagmar Marshalls Fond. Background The assessment of left ventricular (LV) function through transthoracic echocardiography (TTE) is essential for guiding diagnosis and treatment in cases of cardiogenic shock (CS). Myocardial global longitudinal strain (GLS) provides an objective and reproducible measure of systolic function, independently predicting outcomes in acute heart failure, regardless of left ventricular ejection fraction (LVEF). However, whether assessment of GLS can predict mortality in patients with CS remains unknown. Purpose In this study, we aimed to evaluate the prognostic significance of GLS in patients with CS. Methods Data from cardiac intensive care unit (CICU) patients admitted between 2007 and 2018 with CS who received vasoactive agents and/or mechanical circulatory support were analysed. GLS (as absolute values) and biplane LVEF were measured via TTE performed within 24 hours of CICU admission. Patients with CS were categorised based on the GLS quartile: mild (GLS &amp;gt;9.7%), moderate (7.0% &amp;lt; GLS &amp;lt;9.6%), severe (5.0% &amp;lt; GLS &amp;lt; 6.9%), and very severe (GLS ≤ 4.9%). CICU and in-hospital mortality were compared across GLS categories, and the relationship between GLS and mortality was assessed using multivariable logistic regression. Results The study included 626 patients with a median age of 68.6 years, a median LVEF of 31% (IQR 24 to 40%), and a median GLS of 7.0% (IQR 5.0 to 9.7%). In-hospital mortality was 29.1%. As GLS deteriorated, there was an increasing need for vasopressors (P&amp;lt;0.001). Patients with progressively lower GLS exhibited significantly higher CICU and in-hospital mortality across the GLS quartiles (Figure A; P&amp;lt;0.001). Patients in the severe (adjusted OR 2.67; p&amp;lt;0.001) and very severe category (adjusted OR 3.54; P&amp;lt;0.001) had significantly increased risk of in-hospital death compared with mild category. In multivariable analysis, every 1% decrease in GLS corresponded to a 14% higher risk of in-hospital mortality (P&amp;lt;0.001). Finally, GLS outperformed LVEF for discrimination of in-hospital mortality (P=0.002), and when both measurements were included in the same multivariable model, only GLS remained significant. When patients were divided according to whether they had GLS and/or LVEF below the median value, patients with low GLS had higher mortality irrespective of the LVEF (Figure B). Conclusion In patients with CS, GLS assessment surpasses LVEF in its prognostic value and improves risk stratification. Routine evaluation of GLS should be considered for patients with CS.Figure AFigure B

The significance of metabolic alkalosis on acute decompensated heart failure: the ALCALOTIC study.

To determine the prevalence and the impact on prognosis of metabolic alkalosis (MA) in patients admitted for acute heart failure (AHF). The ALCALOTIC is a multicenter, observational cohort study that prospectively included patients admitted for AHF. Patients were classified into four groups according to their acid-base status on admission: acidosis, MA, respiratory alkalosis, and normal pH (reference group for comparison). Primary endpoint was all-cause in-hospital mortality, and secondary endpoints included 30/90-day all-cause mortality, all-cause readmission, and readmission for HF. Associations between endpoints and acid-base alterations were estimated in a multivariate Cox regression model including sex, age, comorbidities, and Barthel index and expressed as hazard ratio (HR) with 95% confidence interval (95% CI). Six hundred sixty-five patients were included (84years and 57% women), and 40% had acid-base alterations on admission: 188 (28%) acidosis and 78 (12%) alkalosis. The prevalence (95% CI) of MA was 9% (6.8-11.2%). Patients with MA were more women; had fewer comorbidities, better renal function, and higher left ventricle ejection fraction values; and received more treatment with oral acetazolamide during hospitalization and at discharge. MA was not associated with a higher risk of in-hospital mortality and 30/90-day all-cause mortality or readmissions but was associated with a significant increase in readmissions for HF at 30 and 90days (adjusted HR [95% CI] 3.294 [1.397-7.767], p = 0.006 and 2.314 [1.075-4.978], p = 0.032). The prevalence of MA in patients admitted for AHF was 9%, and its presence was associated with more readmissions for HF but not with all-cause mortality.

Analysis of outcomes and prognostic factor in acute type A aortic dissection complicated with preoperative shock: A single-center study.

Acute type A aortic dissection (ATAAD) is a critical cardiovascular emergency that requires prompt surgical intervention for preserving life, particularly in patients with critical preoperative status. This retrospective study aimed to investigate the clinical features, early and late outcomes, and prognostic factors in patients undergoing aortic repair surgery for ATAAD complicated with preoperative shock. Between April 2007 and July 2020, 694 consecutive patients underwent emergency ATAAD repair at our institution, including 162 (23.3%) presenting with preoperative shock (systolic blood pressure <90 mm Hg), who were classified into the survivor (n = 125) and non-survivor (n = 37) groups according to whether they survived to hospital discharge. The clinical demographics, surgical information, and postoperative complications were compared. Five-year survival and freedom from reoperation rates of survivors were analyzed using the Kaplan-Meier actuarial method. Multivariate logistic regression analysis was used to identify independent risk factors for in-hospital mortality. The in-hospital surgical mortality rate in patients with ATAAD and shock was 22.8%. The non-survivor group showed higher rates of preoperative cardiopulmonary resuscitation, acute myocardial infarction, and cerebral infarction, and was associated with longer cardiopulmonary bypass time, higher rates of total arch replacement and intraoperative extracorporeal membrane oxygenation implementation. The non-survivor group had higher blood transfusion volumes and rates of malperfusion-related complications. Multivariate analysis revealed that preoperative cardiopulmonary resuscitation, prolonged cardiopulmonary bypass time, and total arch replacement were risk factors for in-hospital mortality. For patients who survived to discharge, the 5-year cumulative survival and freedom from aortic reoperation rates were 75.6% (95% confidence interval, 67.6%-83.6%) and 82.6% (95% confidence interval, 74.2%-91.1%), respectively. Preoperative shock in ATAAD is associated with a high risk of in-hospital mortality, particularly in patients who undergo cardiopulmonary resuscitation and complex aortic repair procedures with extended cardiopulmonary bypass. However, late outcomes are acceptable for patients who were stabilized through surgical treatment and survived to discharge.

Development of a nomogram for predicting in-hospital mortality in patients with liver cirrhosis and sepsis

In this study, we aimed to investigate the risk factors associated with in-hospital mortality in patients with cirrhosis and sepsis, establish and validate the nomogram. This retrospective study included patients diagnosed with liver cirrhosis and sepsis in the Medical Information Mart for Intensive Care IV (MIMIC-IV). Models were compared by the area under the curve (AUC), integrated discriminant improvement (IDI), net reclassification index (NRI) and decision curve analysis (DCA). A total of 1,696 patients with cirrhosis and sepsis were included in the final cohort. Our final model included the following 9 variables: age, heartrate, total bilirubin (TBIL), glucose, sodium, anion gap (AG), fungal infections, mechanical ventilation, and vasopressin. The nomogram were constructed based on these variables. The AUC values of the nomograms were 0.805 (95% CI 0.776–0.833), which provided significantly higher discrimination compared to that of SOFA score [0.684 (95% CI 0.647–0.720)], MELD-Na [0.672 (95% CI 0.636–0.709)] and ABIC [0.674(95% CI 0.638–0.710)]. We established the first nomogram for predicting in-hospital mortality in patients with liver cirrhosis and sepsis based on these factors. This nomogram can performs well and facilitates clinicians to identify people at high risk of in-hospital mortality.

Impact of Frailty on Survival and Neurological Outcomes After Cardiac Arrest: A Systematic Review and Meta-Analysis.

To synthesize the evidence on the associations of frailty with the risk of mortality and neurological outcomes in patients with cardiac arrest undergoing cardiopulmonary resuscitation. We conducted a literature search on PubMed, EMBASE, and Scopus. We included observational studies on adult participants (18 years or older) with cardiac arrest. The eligible studies reported frailty assessments using standard tools, and the comparator group comprised nonfrail participants. We used random-effects models for all analyses and expressed pooled effect sizes as odds ratios (ORs) with 95% confidence intervals (CIs). We included data from 12 studies in our analysis. Individuals with frailty exhibited a significantly higher risk of in-hospital mortality (OR, 2.18; 95% CI, 1.62-2.94), and increased 30-day mortality (OR, 1.43; 95% CI, 1.12-1.84) and 12-month mortality (OR, 4.16; 95% CI, 2.32-7.47) than the nonfrail individuals. Frail individuals also displayed lower odds of achieving favorable neurological outcomes upon hospital discharge (OR, 0.32; 95% CI, 0.20-0.50) and at the 30-day follow-up (OR, 0.42; 95% CI, 0.23-0.78). Additionally, they had lower odds of return of successful spontaneous circulation (OR, 0.49; 95% CI, 0.34-0.72). The observed associations between frailty and a higher risk of mortality reduced odds of favorable neurological outcomes, and lower odds of return of successful spontaneous circulation underscore the value of identifying frailty in individuals to achieve more accurate prognoses. Our findings highlight the importance of including frailty assessments as a component of the management plan for patients experiencing cardiac arrest.

Threshold of hyperglycaemia associated with mortality in critically ill patients: a multicentre, prospective, observational study using continuous glucose monitoring

Aims/hypothesisContinuous glucose monitoring (CGM) provides comprehensive information on the exposure to dysglycaemia. This study aimed to investigate the threshold of hyperglycaemia related to mortality risk in critically ill patients using CGM technology.MethodsA total of 293 adult critically ill patients admitted to intensive care units of five medical centres were prospectively included between May 2020 and November 2021. Participants wore intermittently scanned CGM for a median of 12.0 days. The relationships between different predefined time above ranges (TARs), with the thresholds of hyperglycaemia ranging from 7.8 to 13.9 mmol/l (140–250 mg/dl), and in-hospital mortality risk were assessed by multivariate Cox proportional regression analysis. Time in ranges (TIRs) of 3.9 mmol/l (70 mg/dl) to the predefined hyperglycaemic thresholds were also assessed.ResultsOverall, 66 (22.5%) in-hospital deaths were identified. Only TARs with a threshold of 10.5 mmol/l (190 mg/dl) or above were significantly associated with the risk of in-hospital mortality, after adjustment for covariates. Furthermore, as the thresholds for TAR increased from 10.5 mmol/l to 13.9 mmol/l (190 mg/dl to 250 mg/dl), the hazards of in-hospital mortality increased incrementally with every 10% increase in TARs. Similar results were observed concerning the associations between TIRs with various upper thresholds and in-hospital mortality risk. For per absolute 10% decrease in TIR 3.9–10.5 mmol/l (70–190 mg/dl), the risk of in-hospital mortality was increased by 12.1% (HR 1.121 [95% CI 1.003, 1.253]).Conclusions/interpretationA glucose level exceeding 10.5 mmol/l (190 mg/dl) was significantly associated with higher risk of in-hospital mortality in critically ill patients.Graphical

CARDS, a Novel Prognostic Index for Risk Stratification and In-Hospital Monitoring.

Background: Sodium fluctuation is independently associated with clinical deterioration. We developed and validated a prognostic index based on sodium fluctuation for risk stratification and in-hospital monitoring. Methods: This study included 33,323 adult patients hospitalized at a tertiary care hospital in 2014. The first 28,279 hospitalizations were analyzed to develop the model and then the validity of the model was tested using data from 5044 subsequent hospitalizations. We predict in-hospital mortality using age, comorbidity, range of sodium fluctuation, and duration of sodium fluctuation, abbreviated as CARDS. Results: In-hospital mortality was similar in the derivation (0.6%) and validation (0.4%) cohorts. In the derivation cohort, four independent risk factors for mortality were identified using logistic regression: age (66-75, 2 points; >75, 3 points); Charlson comorbidity index (>2, 5 points); range of sodium fluctuation (7-10, 4 points; >10, 10 points); and duration of fluctuation (≤3, 3 points). The AUC was 0.907 (95% CI: 0.885-0.928) in the derivation cohort and 0.932 (95% CI: 0.895-0.970) in the validation cohort. In the derivation cohort, in-hospital mortality was 0.106% in the low-risk group (0-7 points), 1.076% in the intermediate-risk group (8-14 points), and 8.463% in the high-risk group (15-21 points). In the validation cohort, in-hospital mortality was 0.049% in the low-risk group, 1.064% in the intermediate-risk group, and 8.403% in the high-risk group. Conclusions: These results suggest that patients at low, intermediate, and high risk for in-hospital mortality may be identified by CARDS mainly based on sodium fluctuation.

Gender Differences in the Short and Long-Term Outcomes Following Rotational Atherectomy: A Meta-Analysis

BackgroundRotational atherectomy (RA) is used to address complex calcified coronary lesions but data regarding the association between gender and outcomes of patients undergoing RA remained uncertain. We aimed to investigate the short and long-term outcomes of patients undergoing RA based on sex. MethodsA systematic literature search was performed in PubMed, Embase and Cochrane databases from its inception until August 2023 for relevant studies. Endpoints were pooled using the DerSimonian and Laird random-effects model as odd ratio (OR) with 95% confidence intervals (CI). Results7 studies with 8,490 patients (2,565 women and 5,925 men) undergoing RA were included in the study. In terms of periprocedural outcomes, women had a higher risk of in-hospital mortality (OR 2.00, 95% CI 1.08-3.68, p=0.03), coronary dissection (OR 1.80, 95% CI 1.05-3.10, p=0.03), coronary perforation (OR 1.96, 95% CI 1.19-3.23, p=0.01), and stroke (OR 4.22, 95% CI 1.06-16.82, p=0.04) compared to men. There were no significant differences between women and men in terms of MACE (OR 1.43, 95% CI 0.69-2.94, p=0.33), MI (OR 1.35, 95% CI 0.87-2.08, p=0.18), bleeding (OR 1.71, 95% CI 0.88-3.30, p=0.11), and cardiac tamponade (OR 2.30, 95% CI 0.45-11.68, p=0.32). Over a follow-up period of 3 years, results of meta-analysis showed that women had a higher risk of all-cause mortality (OR 1.45, 95% CI 1.19-1.77, p<0.001), long-term MACE (OR 1.38, 95% CI 1.10-1.74, p=0.01), and long-term stroke (OR 3.41, 95% CI 1.63-7.17, p<0.001). The risk of long-term MI was found to be similar between both gender (OR 1.45, 95% CI 0.95-2.22, p=0.09). ConclusionIn conclusion, female gender is associated with adverse periprocedural and long-term outcome following RA. Women consistently demonstrated higher risk of in-hospital mortality, coronary dissection, coronary perforation, and stroke in the periprocedural period. Long-term follow-up further highlighted a heightened risk for women in terms of all-cause mortality and stroke.

Association between chronic obstructive pulmonary disease and in-hospital mortality after percutaneous coronary intervention: a retrospective cohort study in Germany

Chronic obstructive pulmonary disease (COPD) is one of the leading chronic diseases worldwide. However, the impact of COPD on outcome after percutaneous coronary intervention (PCI) remains unclear. In this retrospective cohort study, we analyzed the data of hospitalized patients undergoing PCI in Germany between 2015 and 2019. We compared in-hospital mortality, hospital length of stay and peri-interventional ventilation time (VT) in patients with and without COPD, including different COPD severity grades, COPD with exacerbation (COPDe) and infection (COPDi). We analyzed the data of 3,464,369 cases undergoing PCI. A total of 291,707 patients (8.4%) suffered from COPD. Patients suffering from COPD died more often (2.4% vs. 2.0%; p < 0.001), stayed longer hospitalized (5 days (2–10) vs. 3 days (1–6); p < 0.001), were more frequent (7.2% vs. 3.2%) and longer ventilated (26 h (7–88) vs. 23 h (5–92); p < 0.001). Surprisingly, COPD was associated with a 0.78-fold odds of in-hospital mortality and with reduced VT (− 1.94 h, 95% CI, − 4.34 to 0.43). Mild to severe COPD was associated with a lower risk of in-hospital mortality and reduced VT, whereas very severe COPD, COPDe and COPDi showed a higher risk of in-hospital mortality. We found a paradoxical association between mild to severe COPD and in-hospital mortality, whereas very severe COPD, COPDe and COPDi were associated with higher in-hospital mortality. Further investigations should illuminate, whether comorbidities affect these associations.

Difference in mortality risk predicted by leukocyte and lymphocyte levels in COVID-19 patients infected with the Wild-type, Delta, and Omicron strains.

This study aimed to investigate the changing trends, level differences, and prognostic performance of the leukocyte and lymphocyte levels of patients infected with the Wild strains, Delta strains and Omicron strains to provide a reference for prognostic assessment. In the current study, we conducted a retrospective cross-sectional study to evaluate the changing trends, level differences, and prognostic performance of leukocyte and lymphocyte of different strains at admission and discharge may already exist in patients with coronavirus disease-2019 (COVID-19) infected with the Wild type, Delta, and Omicron strains. A retrospective cross-sectional study was conducted. We recruited and screened the 243 cases infected with the Wild-type strains in Wuhan, the 629 cases infected with the Delta and 116 cases infected strains with the Omicron strains in Xi'an. The leukocyte and lymphocyte levels were compared the cohort of Wild-type infection with the cohort of Delta and the Omicron. The changes in the levels of leukocytes and lymphocytes exhibit a completely opposite trend in patients with COVID-19 infected with the different strains. The lymphocyte level at admission and discharge in patients with COVID-19 infected with Omicron strains (area under curve [AUC] receiver operating characteristic curve [ROC] 72.8-90.2%, 82.8-97.2%) presented better performance compared patients with COVID-19 infected with Wild type strains (AUC ROC 60.9-80.7%, 82.3-97.2%) and Delta strains (AUC ROC 56.1-84.7%, 40.3-93.3%). Kaplan-Meier curves showed that the leukocyte levels above newly established cutoff values and the lymphocyte levels below newly established cutoff values had a significantly higher risk of in-hospital mortality in COVID-19 patients with Wild-type and Omicron strains (P < .01). The levels of leukocyte and lymphocyte at admission and discharge in patients with COVID-19 infected with the Wild type, Delta, and Omicron strains may be differences among strains, which indicates different death risks. Our research may help clinicians identify patients with a poor prognosis for severe acute respiratory syndrome coronavirus 2 infection.

Association between albumin-corrected anion gap and in-hospital mortality of intensive care patients with trauma: A retrospective study based on MIMIC-Ⅲ and Ⅳ databases.

To investigate the correlation between albumin-corrected anion gap(ACAG) within the first 24 hours of admission and in-hospital mortality in trauma patients in intensive care unit(ICU). We utilized the MIMIC-Ⅲ and MIMIC-Ⅳ databases to examine trauma patients admitted to the ICU. The relationship between ACAG and in-hospital mortality in trauma patients was analyzed using Receiver Operating Characteristic(ROC) curve, Kaplan-Meier (K-M) survival curve, and Cox regression model. Propensity score matching (PSM) and subgroup analysis were conducted to enhance stability and reliability of the findings. Mortality at 30-day and 90-day served as secondary outcomes. The study enrolled a total of 1038 patients. The AUC for ACAG (0.701, 95%CI: 0.652-0.749) was notably higher than that for anion gap and albumin. The Log-rank test revealed that the optimal cut-off point of ACAG for predicting in-hospital mortality was determined to be 20.375mmol/L. The multivariate Cox regression analysis demonstrated an independent association between high ACAG level and a higher risk of in-hospital mortality (HR = 3.128, 95% CI: 1.615-6.059). After PSM analysis, a matched cohort consisting of 291 subjects was obtained. We found no signifcant interaction in most stratas. Finally, The in-hospital, 30-day, and 90-day survival rates in the high ACAG group exhibited a statistically decrease compared to those in the low ACAG group both pre- and post-matching. The elevated level of ACAG was found to be independently associated with increased in-hospital mortality among trauma patients in the ICU.

Higher mortality and longer length of stay in hospitalized patients with newly diagnosed diabetes

AimsWe investigated the association between diabetes status at admission and in-hospital outcomes in all hospitalized patients, regardless of the reason for admission. MethodsAll individuals aged 20 years or older who were admitted to Yongin Severance Hospital between March 2020 and February 2022 were included in study. Subjects were categorized into three groups: non-DM, known DM, and newly diagnosed DM, based on medical history, anti-diabetic medications use, and laboratory test. Hospitalization-related outcomes, including in-hospital mortality and length of hospital stay, were compared between groups. Results33,166 participants were enrolled. At hospitalization, 6,572 (19.8 %) subjects were classified as known DM, and another 2,634 (7.9 %) subjects were classified as newly diagnosed DM. In-hospital mortality was highest in newly diagnosed DM (HR 1.89, 95% CI 1.58–2.26, p < 0.001) followed by known DM (HR 1.41, 95% CI 1.18–1.69, p < 0.001) compared to non-DM. Length of hospital stay was significantly longer in newly diagnosed DM (median [IQR] 9.0 [5.0–18.0],days) than known DM (median [IQR] 5.0 [3.0–10.0],days)(p < 0.001) and non-DM (median [IQR] 4.0 [2.0–7.0],days). After adjusting for multiple covariates, newly diagnosed diabetes was independently associated with increased in-hospital mortality (p < 0.001). ConclusionsDiabetes status at admission was closely linked to hospitalization-related outcomes. Notably, individuals with newly diagnosed diabetes demonstrated a higher risk of in-hospital mortality and a prolonged length of hospital stay.

The evaluation of frequency and predictors of delirium and its short-term and long-term outcomes in hospitalized older adults’

BackgroundDelirium is a common complication in hospitalized older adults with multifactorial etiology and poor health outcomes. AimTo determine the frequency and predictors of delirium and its short-term and long-term outcomes in hospitalized older adults. MethodsA prospective observational study was performed in patients aged ≥60 years consecutively admitted to geriatric ward. Potential risk factors were assessed within 24 hours of hospital admission. Delirium screening was performed on admission and daily thereafter throughout the hospital stay using Confusion Assessment Method (CAM). Patients were followed up at 1-year post-discharge. ResultsThe study included 200 patients with mean age 73.1 ± 8.83 years. Incidence and prevalence rate of delirium were 5% and 20% respectively. Multivariable regression analysis revealed emergency admission (OR= 5.12 (1.94–13.57), p=0.001), functional dependency (Katz index of Independence in Activities of Daily Living (Katz-ADL) score <5) 2 weeks before admission (OR= 3.08 (1.30–7.33), p=0.011) and more psychopathological symptoms (higher Brief Psychiatric Rating Scale (BPRS) total score) (OR=1.12 (1.06–1.18), p=0.001) to be independently associated with delirium. Patients in delirium group had significantly high in-hospital mortality (OR= 5.02 (2.12–11.8), p=0.001) and post-discharge mortality (HR= 2.02 (1.13–3.61), p=0.017) and functional dependency (Katz-ADL score <5) (OR= 5.45 (1.49–19.31), p=0.01) at 1-year follow up. ConclusionDelirium is quite frequent in geriatric inpatients and is associated with high in-hospital and post-discharge mortality risk and long-term functional dependency. Emergency admission, pre-hospitalization functional dependency, and more general psychopathological symptoms are independently associated factors. Hence, earliest identification and treatment with early implementation of rehabilitation services is warranted.

Current situation of management of spontaneous pneumothorax in Japan: A cross-sectional cohort study

BackgroundLimited epidemiological information is available on spontaneous pneumothorax. To address this gap, the Japan Society for Pneumothorax and Cystic Lung Disease (JSPCLD) conducted a nationwide retrospective survey to investigate the current epidemiology of spontaneous pneumothorax in Japan. MethodsIn this study, we conducted a retrospective cross-sectional cohort study to demonstrate the clinical features of spontaneous pneumothorax in one year from April 2019 to March 2020, compare patient characteristics and treatment outcomes between primary (PSP) and secondary spontaneous pneumothorax (SSP), and investigate the risk factors associated with in-hospital mortality among patients with SSP. ResultsA total of 1784 patients from 28 institutions were enrolled in the study, with PSP observed in 956 cases (53.6%) and SSP in 817 cases (45.8%). The age distribution showed a biphasic peak caused by the different peaks between PSP and SSP. In-hospital mortality occurred in 42 cases (2.4%) among all patients, with 0 cases (0%) in PSP and 42 cases (5.1%) in SSP. Multivariable analyses revealed that interstitial pneumonia as an underlying disease (odds ratio: 2.4700, 95% confidence interval: 1.1100 to 5.4800, p = 0.0269), performance status≧3 (odds ratio: 7.3900, 95% confidence interval: 3.1900 to 17.2000, p < 0.0001), and lower value of serum albumin on admission (odds ratio: 0.4060, 95% confidence interval: 0.2140 to 0.7690, p = 0.0057) were significantly associated with in-hospital mortality among patients with SSP. ConclusionsSSP patients with poor baseline conditions are at a higher risk for in-hospital mortality. It is crucial to provide close and meticulous management for SSP patients with compromised conditions.

4C mortality score and COVID-19 mortality risk score: an analysis in four different age groups of an Italian population.

To evaluate the prognostic stratification ability of 4C Mortality Score and COVID-19 Mortality Risk Score in different age groups. Retrospective study, including all patients, presented to the Emergency Department of the University Hospital Careggi, between February, 2020 and May, 2021, and admitted for SARS-CoV2. Patients were divided into four subgroups based on the quartiles of age distribution: patients < 57years (G1, n = 546), 57-71years (G2, n = 508), 72-81years (G3, n = 552), and > 82years (G4, n = 578). We calculated the 4C Mortality Score and COVID-19 Mortality Risk Score. The end-point was in-hospital mortality. In the whole population (age 68 ± 16years), the mortality rate was 19% (n = 424), and increased with increasing age (G1: 4%, G2: 11%, G3: 22%, and G4: 39%, p < 0.001). Both scores were higher among non-survivors than survivors in all subgroups (4C-MS, G1: 6 [3-7] vs 3 [2-5]; G2: 10 [7-11] vs 7 [5-8]; G3: 11 [10-14] vs 10 [8-11]; G4: 13 [12-15] vs 11 [10-13], all p < 0.001; COVID-19 MRS, G1: 8 [7-9] vs 9 [9-11], G2: 10 [8-11] vs 11 [10-12]; G3: 11 [10-12] vs 12 [11-13]; G4: 11 [10-13] vs 13 [12-14], all p < 0.01). The ability of both scores to identify patients at higher risk of in-hospital mortality, was similar in different age groups (4C-MS: G1 0.77, G2 0.76, G3 0.68, G4 0.72; COVID-19 MRS: G1 0.67, G2 0.69, G3 0.69, G4 0.72, all p for comparisons between subgroups = NS). Both scores confirmed their good performance in predicting in-hospital mortality in all age groups, despite their different mortality rate.

The role of race and insurance in trauma patients' mortality: A cross-sectional analysis based on a nationwide sample.

Persistent disparities in trauma in-hospital mortality owing to insurance status and race remain a prominent issue within healthcare. This study explores the relationships among insurance status, race, length of stay (LOS) in-hospital mortality outcomes in trauma patients at extreme risk of mortality (EROM) trauma patients. Data was retrieved from the National Inpatient Sample, focusing on high-acuity trauma patients from 2007 to 2020, aged 18-64 years. Patients were identified using specific All Patient Refined Diagnosis Related Groups codes. Emphasis was placed on those with EROM owing to their resource-intensive nature and the potential influence of insurance on outcomes. Patients aged 65 years or older were excluded owing to distinct trauma patterns, as were those diagnosed with burns or non-trauma conditions. The study encompassed 70,381 trauma inpatients with EROM, representing a national estimate of 346,659. Being insured was associated with a 34% decrease in the odds of in-hospital mortality compared to being uninsured. The in-hospital mortality risk associated with insurance status varied over time, with insurance having no impact on in-hospital mortality during hospitalizations of less than 2 days (short LOS). In the overall group, Black patients showed an 8% lower risk of in-hospital mortality compared to White patients, while they experienced a 33% higher risk of in-hospital mortality during short LOS. Insured trauma inpatients demonstrated a significant reduction in the odds of in-hospital mortality compared to their uninsured counterparts, although this advantage was not present in the short LOS group. Black patients experienced lower in-hospital mortality rates compared to White patients, but this trend reversed in the short LOS group. These findings underscore the intricate relationships between insurance status, race, and duration of hospitalization, highlighting the need for interventions to improve patient outcomes.

Reperfusion strategies on the clinical outcomes of ST-elevation myocardial infarction patients over 80 years old in China

Abstract Aims This study aims to explore the efficacy of reperfusion strategies on the clinical outcomes of ST-elevation myocardial infarction (STEMI) patients over 80 years old in China. Methods and results A retrospective cohort study was performed on STEMI patients over 80 years old who underwent reperfusion strategies and no reperfusion between January 2014 and December 2021, based on the Chinese Cardiovascular Association (CCA) Database-Chest Pain Center. This study included a total of 42,699 patients (mean age 84.1 ± 3.6 years, 52.2% male), among whom 19,280 (45.2%) underwent no reperfusion, 20,924 (49.0%) underwent primary percutaneous coronary intervention (PCI), and 2495 (5.8%) underwent thrombolytic therapy. After adjusting for potential confounders, multivariable logistic regression analysis revealed that patients who underwent primary PCI strategy showed a significantly lower risk of in-hospital mortality [odds ratio (OR) = 0.62, 95% confidence interval (CI): 0.57–0.67, P &amp;lt; 0.001] and the composite outcome (OR = 0.83, 95% CI: 0.79–0.87, P &amp;lt; 0.001) compared to those who received no reperfusion. In contrast, patients with thrombolytic therapy exhibited a non-significantly higher risk of in-hospital mortality (OR = 0.99, 95% CI: 0.86–1.14, P = 0.890) and a significantly elevated risk of the composite outcome (OR = 1.15, 95% CI: 1.05–1.27, P = 0.004). During a median follow-up of 6.7 months post-hospital admission, there was a percentage 31.4% of patients died, and patients in the primary PCI group consistently demonstrated a reduced incidence of all-cause mortality (hazard ratio (HR) = 0.58, 95% CI: 0.56–0.61, P &amp;lt; 0.001). Conclusion STEMI patients over 80 years old who underwent the primary PCI strategy are more likely to have favourable clinical outcomes compared to those who received no reperfusion, whereas thrombolytic therapy warrants careful assessment and monitoring.