In-hospital Death In Patients Research Articles

Impact of nursing policy on securing intensive care unit nurse staffing and in-hospital mortality

ObjectiveThis study aimed to evaluate changes in intensive care unit nurse staffing after the introduction of the government’s nursing policy, and the relationship between ICU nurse staffing levels and in-hospital mortality. DesignA retrospective cohort study. SettingThis study used data from the Health Insurance Review and Assessment Service and included all patients admitted to adult ICUs at general and tertiary hospitals in Korea from 2016 to 2020. MethodsThe primary variables of interest in this study were the level and overall trend change in the outcome variables after introducing the nursing policy; the nurse-to-bed ratio in the ICUs was evaluated. The secondary variable of interest was the relationship between nurse staffing levels and in-hospital mortality. Interrupted time-series analysis and generalized estimating equation models were used to evaluate the primary and secondary variables of interest. ResultsAfter the nursing policy was introduced, the nursing grades in the ICUs increased, especially in tertiary hospitals. The change at the time of the introduction of each policy was not statistically significant; however, after the introduction, the number of hospital beds per nurse decreased. In-hospital deaths of patients in ICUs increased as the number of beds per nurse increased (odds ratio [OR]: 1.17, 95 % confidence interval [CI]: 1.12–1.21) and decreased as the number of experienced nurses increased (OR: 0.97, 95 % CI: 0.96–0.98). ConclusionsThe introduction of a nursing policy centered on financial support for medical institutions led to an increase in nurse hiring, leading to improved nursing grades. However, the results of introducing these policies differed by medical institution and region, and disparities between medical institutions appear to have widened further. Implications for Clinical PracticeExperienced nurses are important for better outcomes for patients admitted to ICUs, and continuous policy efforts are needed to secure and maintain sufficient nurses.

Use of Neutrophil-to-Lymphocyte Ratio to Predict In-Hospital Mortality in Patients Admitted with Acute Decompensation of Atrial Fibrillation.

Background/Objectives: The prevalence of atrial fibrillation (AF) has been on the rise over the last 20 years. It is considered to be the most common cardiac arrhythmia and is associated with significant morbidity and mortality. The need for in-hospital management of patients having AF is increasing. Acute decompensation of cardiac rhythm is an indication for hospital admission. In the existing literature, several studies on different pathologies have observed that the risk of death was greater for patients with an increased neutrophil-to-lymphocyte ratio (NLR) and suggested that the NLR can be a useful biomarker to predict in-hospital mortality. This study aims to evaluate the link between the neutrophil-to-lymphocyte ratio at admission and death among the patients admitted to the medical ward for the acute manifestation of AF, and to gain a better understanding of how we can predict in-hospital all-cause death based on the NLR for these patients. Methods: A single-center retrospective study in an academic medical clinic was conducted. We analyzed if the NLR at in-hospital admission can be related to in-hospital mortality among the patients admitted for AF at the Medical Ward of Municipal Emergency University Hospital Timisoara between 2015 and 2016. After identifying a total of 1111 patients, we divided them into two groups: in-hospital death patients and surviving patients. We analyzed the NLR in both groups to determine if it is related to in-hospital mortality or not. One patient was excluded because of missing data. Results: Our analysis showed that patients who died during in-hospital admission had a significantly higher NLR compared to those who survived (p < 0.0001, 95% CI (1.54 to 3.48)). The NLR was found to be an independent predictor of in-hospital death among patients with AF, even for the patients with no raised level of blood leukocytes (p < 0.0001, 95% CI (0.6174 to 3.0440)). Additionally, there was a significant correlation between the NLR and the risk of in-hospital death for patients admitted with decompensated AF (p < 0.0001), with an area under the ROC curve of 0.745. Other factors can increase the risk of death for these patients (such as the personal history of stroke, HAS-BLED score, and age). Conclusions: The NLR is a useful biomarker to predict in-hospital mortality in patients with AF and can predict the risk of death with a sensitivity of 72.8% and a specificity of 70.4%. Further studies are needed to determine the clinical utility of the NLR in risk stratification and management of patients with AF.

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.

Prediction of risk of in-hospital death in patients with chronic heart failure complicated by lung infections using interpretable machine learning

To predict the risk of in-hospital death in patients with chronic heart failure (CHF) complicated by lung infections using interpretable machine learning. The clinical data of 1415 patients diagnosed with CHF complicated by lung infections were obtained from the MIMIC-IV database. According to the pathogen type, the patients were categorized into bacterial pneumonia and non-bacterial pneumonia groups, and their risks of in-hospital death were compared using Kaplan-Meier survival curves. Univariate analysis and LASSO regression were used to select the features for constructing LR, AdaBoost, XGBoost, and LightGBM models, and their performance was compared in terms of accuracy, precision, F1 value, and AUC. External validation of the models was performed using the data from eICU-CRD database. SHAP algorithm was applied for interpretive analysis of XGBoost model. Among the 4 constructed models, the XGBoost model showed the highest accuracy and F1 value for predicting the risk of in-hospital death in CHF patients with lung infections in the training set. In the external test set, the XGBoost model had an AUC of 0.691 (95% CI: 0.654-0.720) in bacterial pneumonia group and an AUC of 0.725 (95% CI: 0.577-0.782) in non-bacterial pneumonia group, and showed better predictive ability and stability than the other models. The overall performance of the XGBoost model is superior to the other 3 models for predicting the risk of in-hospital death in CHF patients with lung infections. The SHAP algorithm provides a clear interpretation of the model to facilitate decision-making in clinical settings.

Comparison of Endovascular Therapy and Open Surgical Revascularization in Patients With Acute Superior Mesenteric Artery Occlusion: A Large-Scale Analysis Based on the JROAD-DPC Database.

Acute mesenteric ischemia is rare, and few large-scale trials have evaluated endovascular therapy (EVT) and open surgical revascularization (OS). This study aimed to assess clinical outcomes after EVT or OS for acute superior mesenteric artery occlusion and identify predictors of mortality and bowel resection. Data from the Japanese Registry of All Cardiac and Vascular Diseases-Diagnosis Procedure Combination (JROAD-DPC) database from April 2012 to March 2020 were retrospectively analyzed. Overall, 746 patients with acute superior mesenteric artery occlusion who underwent revascularization were classified into 2 groups: EVT (n=475) or OS (n=271). The primary clinical outcome was in-hospital mortality. The secondary outcomes were bowel resection, bleeding complications (transfusion or endoscopic hemostasis), major adverse cardiovascular events, hospitalization duration, and cost. The in-hospital death or bowel resection rate was ≈30%. In-hospital mortality (22.5% versus 21.4%, P=0.72), bowel resection (8.2% versus 8.5%, P=0.90), and major adverse cardiovascular events (11.6% versus 9.2%, P=0.32) were comparable between the EVT and OS groups. Hospitalization duration in the EVT group was 6 days shorter than that in the OS group, and total hospitalization cost was 0.88 million yen lower. Interaction analyses revealed that EVT and OS had no significant difference in terms of in-hospital death in patients with thromboembolic and atherothrombotic characteristics. Advanced age, decreased activities of daily living, chronic kidney disease, and oldmyocardial infarction were significant predictive factors for in-hospital mortality. Diabetes was a predictor of bowel resection after revascularization. EVT was comparable to OS in terms of clinical outcomes in patients with acute superior mesenteric artery occlusion. Some predictive factors for mortality or bowel resection were obtained. URL: www.umin.ac.jp/ctr/; Unique Identifier: UMIN000045240.

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

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. 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. 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). 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.

Pulmonary artery elastance as a predictor of hospital mortality in heart failure cardiogenic shock.

The initial bundle of cares strongly affects haemodynamics and outcomes in acute decompensated heart failure cardiogenic shock (ADHF-CS). We sought to characterize whether 24h haemodynamic profiling provides superior prognostic information as compared with admission assessment and which haemodynamic parameters best predict in-hospital death. All patients with ADHF-CS and with available admission and 24h invasive haemodynamic assessment from two academic institutions were considered for this study. The primary endpoint was in-hospital death. Regression analyses were run to identify relevant predictors of study outcome. We included 127 ADHF-CS patients [65 (inter-quartile range 52-72) years, 25.2% female]. Overall, in-hospital mortality occurred in 26.8%. Non-survivors were older, with greater CS severity. Among admission variables, age [odds ratio (OR)=1.06; 95% confidence interval (CI): 1.02-1.11; Padj=0.005] and CPIRAP (OR=0.62 for 0.1 increment; 95% CI: 0.39-0.95; Padj=0.034) were found significantly associated with in-hospital death. Among 24h haemodynamic univariate predictors of in-hospital death, pulmonary elastance (PaE) was the strongest (area under the curve of 0.77; 95% CI: 0.68-0.86). PaE (OR=5.98; 95% CI: 2.29-17.48; Padj<0.001), pulmonary artery pulsatility index (PAPi, OR=0.77; 95% CI: 0.62-0.92; Padj=0.013) and age (OR=1.06; 95% CI: 1.02-1.11; Padj=0.010) were independently associated with in-hospital death. Best cut-off for PaE was 0.85mmHg/mL and for PAPi was 2.95; cohort phenotyping based on these PaE and PAPi thresholds further increased in-hospital death risk stratification; patients with 24h high PaE and low PAPi exhibited the highest in-hospital mortality (56.2%). Pulmonary artery elastance has been found to be the most powerful 24h haemodynamic predictor of in-hospital death in patients with ADHF-CS. Age, 24h PaE, and PAPi are independently associated with hospital mortality. PaE captures right ventriclar (RV) afterload mismatch and PAPi provides a metric of RV adaptation, thus their combination generates four distinct haemodynamic phenotypes, enhancing in-hospital death risk stratification.

Association between the neutrophil-to-lymphocyte ratio and in-hospital mortality in patients with chronic kidney disease and coronary artery disease in the intensive care unit

BackgroundThe objective of this study was to investigate the correlation between neutrophil-to-lymphocyte ratios (NLR) and the risk of in-hospital death in patients admitted to the intensive care unit (ICU) with both chronic kidney disease (CKD) and coronary artery disease (CAD).MethodsData from the MIMIC-IV database, which includes a vast collection of more than 50,000 ICU admissions occurring between 2008 and 2019, was utilized in the study and eICU-CRD was conducted for external verification. The Boruta algorithm was employed for feature selection. Univariable and multivariable logistic regression analyses and multivariate restricted cubic spline regression were employed to scrutinize the association between NLR and in-hospital mortality. The receiver operating characteristic (ROC) curves were conducted to estimate the predictive ability of NLR.ResultsAfter carefully applying criteria to include and exclude participants, a total of 2254 patients with CKD and CAD were included in the research. The findings showed a median NLR of 7.3 (4.4, 12.1). The outcomes of multivariable logistic regression demonstrated that NLR significantly elevated the risk of in-hospital mortality (OR 2.122, 95% confidence interval [CI] 1.542–2.921, P < 0.001) after accounting for all relevant factors. Further insights from subgroup analyses unveiled that age and Sequential Organ Failure Assessment (SOFA) scores displayed an interactive effect in the correlation between NLR and in-hospital deaths. The NLR combined with traditional cardiovascular risk factors showed relatively great predictive value for in-hospital mortality (AUC 0.750).ConclusionThe findings of this research indicate that the NLR can be used as an indicator for predicting the likelihood of death during a patient’s stay in the intensive care unit, particularly for individuals with both CAD and CKD. The results indicate that NLR may serve as a valuable tool for assessing and managing risks in this group at high risk. Further investigation is required to authenticate these findings and investigate the mechanisms that underlie the correlation between NLR and mortality in individuals with CAD and CKD.

Analysis of in-hospital deaths in patients with critical limb ischemia necessitating invasive treatments: based on a Japanese nationwide database.

Critical limb ischemia (CLI) is associated with systemic cardiovascular and non-cardiovascular diseases. Treatments primarily targeting limb-related outcomes may not improve overall life prognosis. We aimed to describe in-hospital mortality and the underlying etiologies in Japanese patients with CLI. We analyzed the Diagnosis Procedure Combination (DPC) database from approximately 1200 Japanese acute-care hospitals between April 2018 and March 2020. The definition of patients with CLI was based on the diagnostic codes listed as the most resource-intensive diagnosis and information regarding invasive procedures (endovascular treatment, bypass, or amputation). The DPC database provides information on whether in-hospital death was caused by the most resource-intensive diagnosis. Among 15,228 distinct patients with CLI, we identified 18,970 records, including 5,378 amputations. In-hospital death occurred in 1238 (6.5%) patients. Among them, 811 (65.5%) were due to causes unrelated to CLI. In patients who underwent amputation (n = 5378), causes unrelated to CLI accounted for 70.0% of in-hospital deaths, whereas among patients who did not undergo amputation (n = 13,592), this proportion was 60.1%. When compared to patients who died due to causes related to CLI, the prevalence of male patients was higher (62.6% vs 52.7%, p = 0.001), and amputation was more frequently performed (58.0% vs 47.1%, p < 0.001) in those who died due to causes unrelated to CLI. The majority of in-hospital deaths among patients with CLI necessitating endovascular treatment, bypass, or amputation were attributable to factors unrelated to the primary condition of CLI. Managing systemic cardiovascular and non-cardiovascular diseases beyond the affected limb is crucial to improve the prognosis of these patients.

The prognostic impact of insulin resistance surrogates in patients with acute myocardial infarction with and without type 2 diabetes.

Cardiovascular disease is the major cause of morbidity and mortality, particularly in type 2 diabetes mellitus (T2DM). Novel markers of insulin resistance and progression of atherosclerosis include the triglycerides and glucose index (TyG index), the triglycerides and body mass index (Tyg-BMI) and the metabolic score for insulin resistance (METS-IR). Establishing independent risk factors for in-hospital death and major adverse cardiac and cerebrovascular events (MACCE) in patients with myocardial infarction (MI) remains critical. The aim of the study was to assess the risk of in-hospital death and MACCE within 12months after ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) in patients with and without T2DM based on TyG index, Tyg-BMI and METS-IR. Retrospective analysis included 1706 patients with STEMI and NSTEMI hospitalized between 2013 and 2021. We analyzed prognostic value of TyG index, Tyg-BMI and METS-IR for in-hospital death and MACCE as its components (death from any cause, MI, stroke, revascularization) within 12months after STEMI or NSTEMI in patients with and without T2DM. Of 1706 patients, 58 in-hospital deaths were reported (29 patients [4.3%] in the group with T2DM and 29 patients [2.8%] in the group without T2DM; p = 0.1). MACCE occurred in 18.9% of the total study population (25.8% in the group with T2DM and 14.4% in the group without T2DM; p < 0.001). TyG index, Tyg-BMI and METS-IR were significantly higher in the group of patients with T2DM compared to those without T2DM (p < 0.001). Long-term MACCE were more prevalent in patients with T2DM (p < 0.001). The area under the ROC curve (AUC-ROC) for the prediction of in-hospital death and the TyG index was 0.69 (p < 0.001). The ROC curve for predicting in-hospital death based on METS-IR was 0.682 (p < 0.001). The AUC-ROC values for MACCE prediction based on the TyG index and METS-IR were 0.582 (p < 0.001) and 0.57 (p < 0.001), respectively. TyG index was an independent risk factor for in-hospital death in patients with STEMI or NSTEMI. TyG index, TyG-BMI and METS-IR were not independent risk factors for MACCE at 12month follow-up. TyG index and METS-IR have low predictive value in predicting MACCE within 12months after STEMI and NSTEMI.

High-density lipoprotein cholesterol to apolipoprotein A-1 ratio is an important indicator predicting in-hospital death in patients with acute coronary syndrome.

Dyslipidemia plays a pivotal role in the pathogenesis of acute coronary syndrome (ACS). This study aims to investigate the value of two indices associated with lipid metabolism, low-density lipoprotein cholesterol to apolipoprotein B ratio (LBR) and high-density lipoprotein cholesterol to apolipoprotein A-1 ratio (HAR), to predict in-hospital death in patients with ACS. This single-center, retrospective, observational study included 3,366 consecutive ACS patients in Zhongda Hospital, Southeast University from July 2013 to January 2018. The clinical and laboratory data were extracted, and the in-hospital death and hospitalization days were also recorded. All patients were equally divided into four groups according to quartiles of HAR: Q1 (HAR < 1.0283), Q2 (1.0283 ≤ HAR < 1.0860), Q3 (1.0860 ≤ HAR < 1.1798), and Q4 (HAR ≥ 1.1798). Overall, HAR was positively associated with the counts of neutrophils and monocytes, whereas negatively correlated to lymphocyte counts. HAR was negatively correlated to left ventricular ejection fraction (LVEF). Compared to other three groups, in-hospital mortality (vs. Q1, Q2, and Q3, p < 0.001) and hospitalization length (vs. Q1, Q2, and Q3, p < 0.001) were significantly higher in the Q4 group. When grouped by LBR, however, there was no significant difference in LVEF, in-hospital mortality, and hospitalization length among groups. After adjusting potential impact from age, systolic blood pressure, creatine, lactate dehydrogenase, albumin, glucose, and uric acid, multivariate analysis indicated that HAR was an independent factor predicting in-hospital death among ACS patients. HAR had good predictive value for patients' in-hospital death after the occurrence of acute coronary events, but LBR was not related to in-hospital adverse events.

The course of the pulmonary embolism in patients with oncological diseases

The aim – to identify factors associated with in-hospital mortality among patients with acute pulmonary embolism (PE) and oncological diseases. Materials and methods. A retrospective analysis of 647 medical records of patients with acute PE treated at one center from January 1, 2018, to January 1, 2020, was conducted. Among them, 115 patients had verified oncological diseases. PE diagnosis in all patients was confirmed by computed tomography and/or autopsy results. Alongside laboratory studies, patients underwent ultrasound examination. Results and discussion. A comparative assessment of clinical and anamnestic parameters in patients with PE, depending on the presence of oncological diseases, was conducted. The analysis revealed that patients with PE associated with oncological process were on average 5 years older, with higher proportion of elderly patients, and less frequently had anamnestic episodes of venous thrombosis (13.9 % vs. 24.6 %), but predictably more often had additional risk factors, such as blood transfusions, central venous catheters, and laparoscopic interventions. According to the results of the multifactorial regression analysis, factors independently influencing the risk of in-hospital death in patients with acute PE and oncological diseases included decrease of blood pressure, saturation, an increase of the pulmonary artery pressure, leukocytosis and presence of atrial fibrillation. The ROC analysis results allowed determining threshold values of parametric indicators associated with the risk of death during the hospital period in a patient with PE and oncological diseases, i.e. blood pressure ≤ 105 mm Hg, SpO2 ≤ 87 %, pulmonary artery pressure &gt; 48 mm Hg, and leukocyte count &gt; 9.8  109/l. Conclusion. The risk factors of in-hospital death in patients with PE associated with oncological disease are atrial fibrillation, increased pulmonary artery pressure, leukocyte count, low blood pressure and saturation.

Effect of fasting plasma glucose level in severe fever and thrombocytopenia syndrome patients without diabetes.

Hyperglycemia is correlated with worse in-hospital outcomes in acute infectious diseases such as coronavirus disease 2019 (COVID-19) and severe fever with thrombocytopenia syndrome (SFTS). This study assessed the relationship between fasting plasma glucose (FPG) levels and in-hospital mortality, disease type, and secondary infections among individuals with SFTS without preexisting diabetes. The clinical data and laboratory results upon admission of 560 patients with SFTS without preexisting diabetes meeting the inclusion criteria at Wuhan Union Hospital were collected. FPG levels in surviving patients with SFTS subjects were significantly lower than those in patients with SFTS who had died (P<0.0001). In multivariate Cox regression, high FPG level (≥11.1 mmol/L) was a risk factor independently associated with the in-hospital death of patients with SFTS without preexisting diabetes. Similarly, the FPG levels in general patients with SFTS were significantly lower than those in patients with severe SFTS (P<0.0001). Multivariate logistic regression identified high FPG level (7.0-11.1 mmol/L) as a risk factor independently associated with SFTS severity. While FPG levels were comparable between patients with SFTS with and without secondary infection (P = 0.5521), logistic regression analysis revealed that high FPG levels were not a risk factor for secondary infection in patients with SFTS without preexisting diabetes. High FPG level on admission was an independent predictor of in-hospital death and severe disease in individuals with SFTS without preexisting diabetes. FPG screening upon admission and glycemic control are effective methods for improving the prognosis of patients with SFTS.

A new nomogram to predict in-hospital mortality in patients with acute decompensated chronic heart failure and diabetes after 48 Hours of Intensive Care Unit

BackgroundThe study set out to develop an accurate and clinically valuable prognostic nomogram to assess the risk of in-hospital death in patients with acute decompensated chronic heart failure (ADCHF) and diabetes.MethodsWe extracted clinical data of patients diagnosed with ADCHF and diabetes from the Medical Information Mart for Intensive Care III database. Risk variables were selected utilizing least absolute shrinkage and selection operator regression analysis, and were included in multivariate logistic regression and presented in nomogram. bootstrap was used for internal validation. The discriminative power and predictive accuracy of the nomogram were estimated using the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis (DCA).ResultsAmong 867 patients with ADCHF and diabetes, In-hospital death occurred in 81 (9.3%) patients. Age, heart rate, systolic blood pressure, red blood cell distribution width, shock, β-blockers, angiotensin converting enzyme inhibitors or angiotensin receptor blockers, assisted ventilation, and blood urea nitrogen were brought into the nomogram model. The calibration curves suggested that the nomogram was well calibrated. The AUC of the nomogram was 0.873 (95% CI: 0.834–0.911), which was higher that of the Simplified Acute Physiology Score II [0.761 (95% CI: 0.711–0.810)] and sequential organ failure assessment score [0.699 (95% CI: 0.642–0.756)], and Guidelines-Heart Failure score [0.782 (95% CI: 0.731–0.835)], indicating that the nomogram had better ability to predict in-hospital mortality. In addition, the internally validated C-index was 0.857 (95% CI: 0.825–0.891), which again verified the validity of this model.ConclusionsThis study constructed a simple and accurate nomogram for predicting in-hospital mortality in patients with ADCHF and diabetes, especially in those who admitted to the intensive care unit for more than 48 hours, which contributed clinicians to assess the risk and individualize the treatment of patients, thereby reducing in-hospital mortality.

Association between blood urea nitrogen to serum albumin ratio and in-hospital mortality in critical patients with diabetic ketoacidosis: a retrospective analysis of the eICU database.

This study aimed to investigate the association between blood urea nitrogen to serum albumin ratio (BAR) and the risk of in-hospital mortality in patients with diabetic ketoacidosis. A total of 3,962 diabetic ketoacidosis patients from the eICU Collaborative Research Database were included in this analysis. The primary outcome was in-hospital death. Over a median length of hospital stay of 3.1 days, 86 in-hospital deaths were identified. One unit increase in LnBAR was positively associated with the risk of in-hospital death (hazard ratio [HR], 1.82 [95% CI, 1.42-2.34]). Furthermore, a nonlinear, consistently increasing correlation between elevated BAR and in-hospital mortality was observed (P for trend =0.005 after multiple-adjusted). When BAR was categorized into quartiles, the higher risk of in-hospital death (multiple-adjusted HR, 1.99 [95% CI, (1.1-3.6)]) was found in participants in quartiles 3 to 4 (BAR≥6.28) compared with those in quartiles 1 to 2 (BAR<6.28). In the subgroup analysis, the LnBAR-hospital death association was significantly stronger in participants without kidney insufficiency (yes versus no, P-interaction=0.023). There was a significant and positive association between BAR and the risk of in-hospital death in patients with diabetic ketoacidosis. Notably, the strength of this association was intensified among those without kidney insufficiency.

Efficacy of venoarterial extracorporeal membrane oxygenation with and without intra-aortic balloon pump in adult cardiogenic shock.

Intra-aortic balloon pump (IABP) is sometimes coupled with Venoarterial extracorporeal membrane oxygenation (VA-ECMO) to treat patients with cardiogenic shock. In this study, we attempted to evaluate the association of the IABP approach on survival and vascular complication rates in adults with cardiogenic shock undergoing VA-ECMO. We performed a systematic search of original studies on VA-ECMO with and without IABP in PubMed, EMBASE, and the Cochrane Library. A total of 42 studies with 8,759 patients were included. The pooled in-hospital deaths of patients on VA-ECMO with and without IABP were 2,962/4,807 (61.61%) versus 2,666/3,952 (67.45%). VA-ECMO with IABP presents lower in-hospital mortality (risk ratio, 0.88; 95% CI, 0.86-0.91; P < 0.00001). In addition, IABP was associated with lower in-hospital mortality of patients with postcardiotomy cardiogenic shock and ischaemic heart disease. (risk ratio, 0.93; 95% CI, 0.87-0.98; P = 0.01; risk ratio, 0.85; 95% CI, 0.82-0.89; P < 0.00001). There was no significant difference in in-hospital morbidity in neurological, gastrointestinal, limb-related, bleeding, and infection complications between patients on VA-ECMO with and without IABP. In these observational studies, concomitant use of IABP and VA-ECMO in adult patients with cardiogenic shock was associated with reduced in-hospital mortality. PROSPERO [CRD42017069259].

Risk analysis of gastrointestinal bleeding in patients with acute ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention

Objective: Of all spontaneous bleeding complications in patients with acute ST-elevation myocardial infarction (STEMI), upper gastrointestinal bleeding (UGIB) is the most common and of specific interest, because it can be prevented by several prophylactic measures. The purpose of this study was to investigate the in-hospital incidence, associated outcomes, and predictors of UGIB after STEMI. Methods: In this retrospective study, we analyzed the records of 2 791 patients with acute STEMI admitted to Beijing Anzhen Hospital Affiliated to Capital Medical University between January 2018 and January 2022. The patients were divided into the UGIB group (n=61) and non-UGIB group (n=2 730) according to the presence or absence of upper gastrointestinal hemorrhage, respectively. Baseline clinical conditions, coronary lesions, in-hospital deaths, and in-hospital adverse events were compared between the two groups. Logistic regression analysis was also performed for risk factors that could lead to UGIB. Results: The in-hospital incidence of UGIB after STEMI was 2.2% (61/2 791). Hospital stay was significantly longer in the UGIB group [8(6, 12) days vs. 5 (4, 7) days, Z=3.28, P<0.001] and in-hospital mortality was significantly higher in the UGIB group than in the non-UGIB group (9.8% vs. 0.8%, χ2=0.63, P=0.001). Patients with UGIB were significantly older than those without UGIB (63±11 years vs. 58±11 years, t=-3.75, P<0.001). The serum creatinine level of UGIB patients was significantly higher than that of non-UGIB patients [(80(62, 98) mmol/L vs. 73(64, 84) mmol/L, Z=1.68, P=0.007], the red blood cell count of UGIB patients was significantly lower than that of non-UGIB patients [4.1(3.8, 4.6)×1012/L vs. 4.6(4.2, 4.9)×1012/L, Z=2.61,P<0.001], and the hemoglobin concentration of UGIB patients was significantly lower than that of non-UGIB patients [129(109, 141) g/L vs. 141(130, 152) g/L, Z=2.52,P<0.001]. Brain natriuretic peptide levels were significantly higher in UGIB patients than in non-UGIB patients [331(165, 644) ng/L vs. 181(89, 333) ng/L, Z=2.42,P<0.001]. Logistic regression analysis showed that age (OR=1.045, 95%CI 1.009-1.082, P=0.013); hemoglobin (OR=1.594, 95%CI 1.150-2.210, P=0.005); hematocrit (OR=0.181, 95%CI 0.060-0.546, P=0.002); and mean hemoglobin concentration (OR=0.845, 95%CI 0.752-0.951, P=0.005) were independent risk factors for UGIB in patients with STEMI. Logistic regression analysis of risk factors for in-hospital death revealed that concurrent UGIB was an independent risk factor for in-hospital death in patients with STEMI (OR=2.954, 95%CI 0.635-13.751, P=0.024). Conclusions: The incidence of in-hospital UGIB in STEMI patients was 2.2%, and the in-hospital mortality rate of STEMI complicated with UGIB increased to 9.8%. Concurrent UGIB was an independent risk factor for in-hospital death in patients with STEMI. The most important predictors of in-hospital UGIB in patients with STEMI were age, hemoglobin, hematocrit, and mean hemoglobin concentration.

Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures

BackgroundThe incidence of nonhip femoral fractures is gradually increasing, but few studies have explored the risk factors for in-hospital death in patients with nonhip femoral fractures in the ICU or developed mortality prediction models. Therefore, we chose to study this specific patient group, hoping to help clinicians improve the prognosis of patients.MethodsThis is a retrospective study based on the data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Least absolute shrinkage and selection operator (LASSO) regression was used to screen risk factors. The receiver operating characteristic (ROC) curve was drawn, and the areas under the curve (AUC), net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. The consistency between the actual probability and the predicted probability was assessed by the calibration curve and Hosmer–Lemeshow goodness of fit test (HL test). Decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit.ResultsThe LASSO regression analysis showed that heart rate, temperature, red blood cell distribution width, blood urea nitrogen, Glasgow Coma Scale (GCS), Simplified Acute Physiology Score II (SAPSII), Charlson comorbidity index and cerebrovascular disease were independent risk factors for in-hospital death in patients with nonhip femoral fractures. The AUC, IDI and NRI of our model in the training set and validation set were better than those of the GCS and SAPSII scoring systems. The calibration curve and HL test results showed that our model prediction results were in good agreement with the actual results (P = 0.833 for the HL test of the training set and P = 0.767 for the HL test of the validation set). DCA showed that our model had a better clinical net benefit than the GCS and SAPSII scoring systems.ConclusionIn this study, the independent risk factors for in-hospital death in patients with nonhip femoral fractures were determined, and a prediction model was constructed. The results of this study may help to improve the clinical prognosis of patients with nonhip femoral fractures.

Abstract 12495: Modes of In-Hospital Death in Patients With Cardiogenic Shock (CS): An Analysis From the Critical Care Cardiology Trials Network (CCCTN)

Introduction: Mortality from cardiogenic shock (CS), a syndrome of multi-organ system dysfunction, remains high. However, data regarding how patients with CS expire are limited and may have implications for designing clinical trials, identifying therapeutic strategies, and improving outcomes. Aim: We sought to describe primary modes of in-hospital death among patients admitted with CS to cardiac intensive care units (CICUs). Methods: CCCTN is a multi-national research network of advanced CICUs coordinated by the TIMI Study Group (Boston, MA). Using standardized definitions, site investigators classified the direct mode of in-hospital death for patients with CS. Categories included 8 possible modes of cardiovascular (CV) and non-CV death ( Fig ). Subgroups defined by cardiac arrest prior to CICU admission and use of mechanical circulatory support (MCS) were explored. Results: Among 1098 CS cases captured from 10/2021-09/2022, 358 (32.6%) died during the index hospitalization with a median time to death of 4.3 (Q1-Q3, 1.1-10.9) days from CICU admission. Among the deaths, 50%, 41%, and 9% occurred in the context of HF-CS, AMI-CS, and secondary CS, respectively. Overall, mode of death was CV in 82% of cases ( Fig A ). Refractory CS was the dominant mode of death (66%), followed by arrhythmia (13%), anoxic brain injury (6%), and respiratory failure (5%; Fig A ). Compared to patients without preceding cardiac arrest, those with cardiac arrest prior to CICU admission were more likely to die from anoxic brain injury (10% vs. 1%; p&lt;0.01; Fig B ). Compared to patients managed without MCS, those with MCS were more likely to die from refractory shock (p&lt;0.01), either cardiogenic (74% vs. 61%) or non-cardiogenic (6% vs. 3%; Fig C ). Conclusions: Most in-hospital deaths in patients with CS are related to direct CV causes, particularly refractory CS. However, there is potentially important heterogeneity in mode of death across subgroups defined by preceding cardiac arrest and use of MCS.

Prediction models for in-hospital deaths of patients with COVID-19 using electronic healthcare data

Objective Many models for predicting various disease prognoses have achieved high performance without laboratory test results. However, whether laboratory test results can improve performance remains unclear. This study aimed to investigate whether laboratory test results improve the model performance for coronavirus disease 2019 (COVID-19). Methods Prediction models were developed using data from the electronic healthcare record database in Japan. Patients aged ≥18 years hospitalized for COVID-19 after February 11, 2020, were included. Their age, sex, comorbidities, laboratory test results, and number of days from February 11, 2020, were collected. We developed a logistic regression, XGBOOST, random forest, and neural network analysis and compared the performance with and without laboratory test results. The performance of predicting in-hospital death was evaluated using the area under the curve (AUC). Results Data from 8,288 hospitalized patients (females, 46.5%) were analyzed. The median patient age was 71 years. A total of 6,630 patients were included in the training dataset, and 312 (4.7%) died. In the logistic regression model, the area under the curve was 0.88 (95% confidence interval [CI] = 0.83–0.93) and 0.75 (95% CI = 0.68–0.81) with and without laboratory test results, respectively. The performance was not fundamentally different between the model types, and the laboratory test results improved the performance in all cases. The variables useful for prediction were blood urea nitrogen, albumin, and lactate dehydrogenase. Conclusions Laboratory test results, such as blood urea nitrogen, albumin, and lactate dehydrogenase levels, along with background information, helped estimate the prognosis of patients hospitalized for COVID-19.