Abstract P394: Association Between Admission Dehydration and In-Hospital Mortality in Patients With Intracerebral Hemorrhage

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Bin Gao ◽  
Hongqiu Gu ◽  
Shimeng Liu ◽  
Qi Zhou ◽  
Kang Kaijiang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Intracerebral Hemorrhage ◽  
Hospital Mortality ◽  
Blood Urea Nitrogen ◽  
Regression Models ◽  
Fluid Management ◽  
Urea Nitrogen ◽  
Logistic Regression Models ◽  
Acute Intracerebral Hemorrhage ◽  
Stroke Center

Background and purpose: Our aim was to investigate the associations between dehydration status at admission and in-hospital mortality in patients with intracerebral hemorrhage. Methods: Data of consecutive patients with intracerebral hemorrhage between August 2015 and July 2019 based on China Stroke Center Alliance (CSCA) were analyzed. The patients were stratified based on the blood urea nitrogen (BUN) to creatinine (CR) ratio (BUN/CR) on admission, into dehydrated (BUN/CR ≥ 15) and non-dehydrated (BUN/CR < 15) groups. Data were analyzed with multi-variate logistic regression models to analyze the risks of death at hospital and baseline dehydration status. Results: A total number of 84043 patients with intracerebral hemorrhage were included in the study. The median age of patients on admission was 63.0 years, and 37.5% of them were women. Based on the baseline BUN/CR, 59153 (70.4%) patients were classified into dehydration group. Patients with admission dehydration (BUN/CR ≥ 15) had 13% lower risks of in-hospital mortality than those without dehydration (BUN/CR < 15, adjusted OR=0.87, 95%CI: [0.78-0.96]). In patients aged <65 years, patients with baseline dehydration (BUN/CR ≥ 15) showed 19% lower risks of in-hospital mortality (adjusted OR=0.81, 95%CI: [0.70-0.94].adjusted p=0.0049) than non-dehydrated patients (BUN/CR<15). Conclusion: Admission dehydration is associated with lower in-hospital mortality in intracerebral hemorrhage,which provides an imaging clue that fluid management could be important for acute intracerebral hemorrhage.

scholarly journals Admission Dehydration Is Associated With Significantly Lower In-Hospital Mortality After Intracerebral Hemorrhage

2021 ◽  
Vol 12 ◽  
Author(s):  
Bin Gao ◽  
Hongqiu Gu ◽  
Wengui Yu ◽  
Shimeng Liu ◽  
Qi Zhou ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Intracerebral Hemorrhage ◽  
Hospital Mortality ◽  
Blood Urea Nitrogen ◽  
Regression Models ◽  
Multivariate Logistic Regression ◽  
Urea Nitrogen ◽  
Logistic Regression Models ◽  
Stroke Center

Background and Purpose: Our aim was to investigate the frequency of dehydration at admission and associations with in-hospital mortality in patients with intracerebral hemorrhage (ICH).Methods: Data of consecutive patients with ICH between August 2015 and July 2019 from the China Stroke Center Alliance (CSCA) registry were analyzed. The patients were stratified based on the blood urea nitrogen (BUN) to creatinine (CR) ratio (BUN/CR) on admission into dehydrated (BUN/CR ≥ 15) or non-dehydrated (BUN/CR &lt; 15) groups. Data were analyzed with multivariate logistic regression models to investigate admission dehydration status and the risks of death at hospital.Results: A total number of 84,043 patients with ICH were included in the study. The median age of patients on admission was 63.0 years, and 37.5% of them were women. Based on the baseline BUN/CR, 59,153 (70.4%) patients were classified into dehydration group. Patients with admission dehydration (BUN/CR ≥ 15) had 13% lower risks of in-hospital mortality than those without dehydration (BUN/CR &lt; 15, adjusted OR = 0.87, 95%CI 0.78–0.96). In patients aged &lt;65 years, admission dehydration was associated with 19% lower risks of in-hospital mortality (adjusted OR = 0.81, 95%CI 0.70–0.94. adjusted p = 0.0049) than non-dehydrated patients.Conclusion: Admission dehydration is associated with significantly lower in-hospital mortality after ICH, in particular, in patients &lt;65 years old.

scholarly journals The association of blood urea nitrogen levels upon emergency admission with mortality in acute exacerbation of chronic obstructive pulmonary disease

2021 ◽  
Vol 18 ◽  
pp. 147997312110600
Author(s):  
Lan Chen ◽  
Lijun Chen ◽  
Han Zheng ◽  
Sunying Wu ◽  
Saibin Wang
Keyword(s):  
Propensity Score ◽  
Hospital Mortality ◽  
Propensity Score Matching ◽  
Blood Urea Nitrogen ◽  
Regression Models ◽  
Chronic Obstructive ◽  
Urea Nitrogen ◽  
Obstructive Pulmonary Disease ◽  
Logistic Regression Models ◽  
Survivor Group

Background and purpose High blood urea nitrogen (BUN) is associated with an elevated risk of mortality in various diseases, such as heart failure and pneumonia. Heart failure and pneumonia are common comorbidities of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). However, data on the relationship of BUN levels with mortality in patients with AECOPD are sparse. The purpose of this study was to evaluate the correlation between BUN level and in-hospital mortality in a cohort of patients with AECOPD who presented at the emergency department (ED). Methods A total of 842 patients with AECOPD were enrolled in the retrospective observational study from January 2018 to September 2020. The outcome was all-cause in-hospital mortality. Receiver operating characteristic (ROC) curve analysis and logistic regression models were performed to evaluate the association of BUN levels with in-hospital mortality in patients with AECOPD. Propensity score matching was used to assemble a cohort of patients with similar baseline characteristics, and logistic regression models were also performed in the propensity score matching cohort. Results During hospitalization, 26 patients (3.09%) died from all causes, 142 patients (16.86%) needed invasive ventilation, and 190 patients (22.57%) were admitted to the ICU. The mean level of blood urea nitrogen was 7.5 ± 4.5 mmol/L. Patients in the hospital non-survivor group had higher BUN levels (13.48 ± 9.62 mmol/L vs. 7.35 ± 4.14 mmol/L, p < 0.001) than those in the survivor group. The area under the curve (AUC) was 0.76 (95% CI 0.73–0.79, p < 0.001), and the optimal BUN level cutoff was 7.63 mmol/L for hospital mortality. As a continuous variable, BUN level was associated with hospital mortality after adjusting respiratory rate, level of consciousness, pH, PCO2, lactic acid, albumin, glucose, CRP, hemoglobin, platelet distribution width, D-dimer, and pro-B-type natriuretic peptide (OR 1.10, 95% CI 1.03–1.17, p=0.005). The OR of hospital mortality was significantly higher in the BUN level ≥7.63 mmol/L group than in the BUN level <7.63 mmol/L group in adjusted model (OR 3.29, 95% CI 1.05–10.29, p=0.041). Similar results were found after multiple imputation and in the propensity score matching cohort. Conclusions Increased BUN level at ED admission is associated with hospital mortality in patients with AECOPD who present at the ED. The level of 7.63 mmol/L can be used as a cutoff value for critical stratification.

scholarly journals Blood Urea Nitrogen and In-Hospital Mortality in Critically Ill Patients with Cardiogenic Shock: Analysis of the MIMIC-III Database

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
En-qian Liu ◽  
Chun-lai Zeng
Keyword(s):  
Logistic Regression ◽  
Hospital Mortality ◽  
Cardiogenic Shock ◽  
Critically Ill ◽  
Blood Urea Nitrogen ◽  
Critically Ill Patients ◽  
Medical Information ◽  
Multivariate Logistic Regression Model ◽  
Standard Deviation Increase ◽  
Urea Nitrogen

The association between blood urea nitrogen (BUN) and prognosis has been the focus of recent research. Therefore, the objective of this study was to investigate the association between BUN and hospital mortality in critically ill patients with cardiogenic shock (CS). This was a retrospective cohort study, in which data were obtained from the Medical Information Mart for Intensive Care III V1.4 database. Data from 697 patients with CS were analyzed. Logistic regression and subgroup analyses were used to assess the association between BUN and hospital mortality in patients with CS. The average age of the 697 participants was 71.14 years, and approximately 42.18% were men. In the multivariate logistic regression model, after adjusting for age, sex, diabetes, cardiac arrhythmias, urine output, simplified acute physiology score II, sequential organ failure assessment, creatinine, anion gap, and heart rate, high BUN demonstrated strong associations with increased in-hospital mortality (per standard deviation increase: odds ratio [OR] 1.47, 95% confidence interval [CI] 1.13–1.92). A similar result was observed in BUN tertile groups (BUN 23–37 mg/dL versus 6–22 mg/dL: OR [95% CI], 1.42 [0.86–2.34]; BUN 38–165 mg/dL versus 6–22 mg/dL: OR [95% CI], 1.99 [1.10–3.62]; P trend 0.0272). Subgroup analysis did not reveal any significant interactions among various subgroups, and higher BUN was associated with adverse clinical outcomes in patients with CS.

Abstract P122: The Impact of Center Certification Status on Acute Stroke Care Within a Multi-Hospital System in Western United States

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Radoslav I Raychev ◽  
CrystalAnn Moreno ◽  
Leslie Corless ◽  
Jason W Tarpley ◽  
John F Zurasky ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Clinical Outcome ◽  
Regression Models ◽  
Process Of Care ◽  
Chi Square ◽  
Hospital System ◽  
Logistic Regression Models ◽  
Stroke Center ◽  
The Impact ◽  
Iv Tpa

Introduction: We aimed to investigate the impact of certification status on process of care metrics and clinical outcome in a large multi-center hospital system. Methods: We analyzed data obtained from the Providence Stroke Registry between January 2016 and December 2019. Key process of care metrics and clinical outcome were compared among patients with a discharge diagnosis of stroke and stratified based on site certification: comprehensive stroke center (CSC), thrombectomy-capable stroke center (TSC), primary stroke center (PSC) and no certification (NC). Donner’s adjusted chi-square tests were used to compare proportions for each metric grouped by certification. Generalized linear mixed effects logistic regression models were used to adjust for mode of patient arrival, age, sex, admit NIHSS, and medical history. Results: Data included 45,278 patients. Results from the analyses are summarized in the table. Donner’s adjusted chi-square analyses showed significant differences for metrics across certification groups. Results from the logistic regression models indicated significant differences in IV TPA and EVT treatment, as well as IV TPA treatment times across certification groups. There were no significant differences between TSC and CSC. Conclusions: Patients presenting with acute ischemic stroke at NC and PSC were significantly less likely to receive IV TPA or EVT with significantly less efficient IV tPA treatment times as compared to CSC. However, CSC and TSC sites performed similarly.

In-Hospital Mortality and Trends Associated with Splenectomy in Patients with Immune-Mediated Thrombocytopenia (ITP).

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 1398-1398
Author(s):  
Samantha M. Jaglowski ◽  
John C. Byrd ◽  
Jeffrey A. Jones
Keyword(s):  
Logistic Regression ◽  
Hospital Mortality ◽  
Mortality Risk ◽  
Medical Management ◽  
Regression Models ◽  
Multivariate Logistic Regression ◽  
Logistic Regression Models ◽  
Risk Of Death ◽  
Teaching Status ◽  
Observation Period

Abstract Abstract 1398 Poster Board I-420 Background: Splenectomy remains a standard treatment for ITP patients not responding to medical management, but anecdotal reports suggest that use of the procedure is in decline. We studied patterns of use and outcome of splenectomy performed for ITP at the population level. Methods: Using data from the Nationwide Inpatient Sample and ICD-9 diagnosis and procedure codes, we identified 39,543 splenectomies among hospital admissions including a diagnosis of ITP (ICD-9 287.3) from 1993-2005. Admissions were characterized by patient and hospital facility characteristics. Laparascopic procedures were identified by published procedure coding algorithms. Factors influencing in-hospital mortality for 2005 were further evaluated using multivariate logistic regression models. Results: Annual estimates for incidence of splenectomy are displayed in Figure 1. Between 1993 and 2005, there was a decrease in the total number of splenectomies performed for ITP, with the most significant drop occurring from 1997 to 2000, concurrent with the FDA approval of rituximab. Over the same period, there has been an increase in the proportion of splenectomies performed laparoscopically from 3.4% to 18.6%. Patient gender, age, presence of comorbid malignancy, and Charlson score were not significantly associated with type of splenectomy procedure. Among facility factors, only hospital teaching status was a statistically significant predictor of laparoscopic splenectomy use, early but not later in the observation period. On an annual basis, in-hospital mortality did not vary significantly over the observation period, with risks ranging from 1.5% (95% CI 0.83-2.86%) in 1993 to 4% (95% CI 2.8%-5.7%) in 1997. Annual mortality risk between open and laparoscopic procedures likewise did not significantly differ. However, over the total 13-year observation period there was a >60% increased risk of death with an open versus laparoscopic procedure (OR 1.669, p<0.0001). In 2005, 2869 splenectomy procedures were performed. Multivariate logistic regression models for in-hospital mortality that year found that presence of a malignancy (OR 9.65, p=0.003) significantly increased mortality risk. Charlson comorbidity approached statistical significance (0 v. ≥1, OR 6.83, p=0.087). Hospital bed-size (OR 0.87, p=0.73), location (rural v. urban, OR 3.80, p=0.127), and teaching status (OR 0.39, p=0.203) were not significantly associated with outcome. Conclusions: While the overall mortality risk from splenectomy in ITP is low, it is influenced by the presence of malignancy and other comorbid conditions. Further studies designed to evaluate newer medical management strategies (e.g. rituximab, thrombopoeitin mimetics, etc.) versus surgical intervention in these higher-risk populations are warranted. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Primary admission and secondary transfer of trauma patients to Dutch level I and level II trauma centers: predictors and outcomes

2021 ◽  
Author(s):  
Claire R. L. van den Driessche ◽  
Charlie A. Sewalt ◽  
Jan C. van Ditshuizen ◽  
Lisa Stocker ◽  
Michiel H. J. Verhofstad ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Hospital Mortality ◽  
Trauma Center ◽  
Regression Models ◽  
Trauma Patients ◽  
Trauma Centers ◽  
Logistic Regression Models ◽  
Level Ii ◽  
Secondary Transfer ◽  
Level I

Abstract Purpose The importance and impact of determining which trauma patients need to be transferred between hospitals, especially considering prehospital triage systems, is evident. The objective of this study was to investigate the association between mortality and primary admission and secondary transfer of patients to level I and II trauma centers, and to identify predictors of primary and secondary admission to a designated level I trauma center. Methods Data from the Dutch Trauma Registry South West (DTR SW) was obtained. Patients ≥ 18 years who were admitted to a level I or level II trauma center were included. Patients with isolated burn injuries were excluded. In-hospital mortality was compared between patients that were primarily admitted to a level I trauma center, patients that were transferred to a level I trauma center, and patients that were primarily admitted to level II trauma centers. Logistic regression models were used to adjust for potential confounders. A subgroup analysis was done including major trauma (MT) patients (ISS > 15). Predictors determining whether patients were primarily admitted to level I or level II trauma centers or transferred to a level I trauma center were identified using logistic regression models. Results A total of 17,035 patients were included. Patients admitted primarily to a level I center, did not differ significantly in mortality from patients admitted primarily to level II trauma centers (Odds Ratio (OR): 0.73; 95% confidence interval (CI) 0.51–1.06) and patients transferred to level I centers (OR: 0.99; 95%CI 0.57–1.71). Subgroup analyses confirmed these findings for MT patients. Adjusted logistic regression analyses showed that age (OR: 0.96; 95%CI 0.94–0.97), GCS (OR: 0.81; 95%CI 0.77–0.86), AIS head (OR: 2.30; 95%CI 2.07–2.55), AIS neck (OR: 1.74; 95%CI 1.27–2.45) and AIS spine (OR: 3.22; 95%CI 2.87–3.61) are associated with increased odds of transfers to a level I trauma center. Conclusions This retrospective study showed no differences in in-hospital mortality between general trauma patients admitted primarily and secondarily to level I trauma centers. The most prominent predictors regarding transfer of trauma patients were age and neurotrauma. These findings could have practical implications regarding the triage protocols currently used.

In-hospital mortality after traumatic brain injury surgery: a nationwide population-based comparison of mortality predictors used in artificial neural network and logistic regression models

2013 ◽  
Vol 118 (4) ◽  
pp. 746-752 ◽  
Author(s):  
Hon-Yi Shi ◽  
Shiuh-Lin Hwang ◽  
King-Teh Lee ◽  
Chih-Lung Lin
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Hospital Mortality ◽  
Regression Models ◽  
Logistic Regression Model ◽  
Global Sensitivity Analysis ◽  
Ann Model ◽  
Logistic Regression Models ◽  
Global Sensitivity

Object Most reports compare artificial neural network (ANN) models and logistic regression models in only a single data set, and the essential issue of internal validity (reproducibility) of the models has not been adequately addressed. This study proposes to validate the use of the ANN model for predicting in-hospital mortality after traumatic brain injury (TBI) surgery and to compare the predictive accuracy of ANN with that of the logistic regression model. Methods The authors of this study retrospectively analyzed 16,956 patients with TBI nationwide who were surgically treated in Taiwan between 1998 and 2009. For every 1000 pairs of ANN and logistic regression models, the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow statistics, and accuracy rate were calculated and compared using paired t-tests. A global sensitivity analysis was also performed to assess the relative importance of input parameters in the ANN model and to rank the variables in order of importance. Results The ANN model outperformed the logistic regression model in terms of accuracy in 95.15% of cases, in terms of Hosmer-Lemeshow statistics in 43.68% of cases, and in terms of the AUC in 89.14% of cases. The global sensitivity analysis of in-hospital mortality also showed that the most influential (sensitive) parameters in the ANN model were surgeon volume followed by hospital volume, Charlson comorbidity index score, length of stay, sex, and age. Conclusions This work supports the continued use of ANNs for predictive modeling of neurosurgery outcomes. However, further studies are needed to confirm the clinical efficacy of the proposed model.

scholarly journals Early immunosuppression was associated with poor prognosis in elderly patients with sepsis: secondary analysis of the ETASS study

2020 ◽  
Author(s):  
Fei Pei ◽  
Guanrong Zhang ◽  
Lixin Zhou ◽  
Jiyun Liu ◽  
Gang Ma ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Elderly Patients ◽  
Hospital Mortality ◽  
Poor Prognosis ◽  
Regression Models ◽  
Immune Status ◽  
The Elderly ◽  
Logistic Regression Models ◽  
Definition Of

Abstract Background: Although immunosuppression has been investigated in adult septic patients, early immune status remains unclear. In this study, we aimed to assess early immune status in adult patients with sepsis stratified by age and its relevance to hospital mortality. Methods: From post hoc analysis of a multicenter, randomized controlled trial, 273 patients whose levels of monocyte human leukocyte antigen-DR (mHLA-DR) were obtained within 48 hours after onset of sepsis were enrolled. All patients were divided into elderly (≥60yrs) group and non-elderly (<60yrs) group. Early immune status was evaluated by the percentage of mHLA-DR in total monocytes within 48 hours after onset of sepsis and it was classified as immunosuppression (mHLA-DR≤30%) or non-immunosuppression (>30%). Changes in immune status were assessed by the value change in mHLA-DR on day 3 compared with the first measurement. Three logistic regression models were conducted to test the associations between early immunosuppression and hospital mortality. We also did a sensitivity analysis to find out if the definition of early immune status (24 vs. 48 hours after onset of sepsis) affects the outcomes. Results: Of the 181 elderly and 92 non-elderly septic patients, 71 (39.2%) elderly and 25 (27.2%) non-elderly died in hospital. The percentage of early immunosuppression in the elderly was twice of that of the non-elderly patients (32% vs. 16%, p=0.006). Immunosuppressed elderly had higher hospital mortality than the non-immunosuppressed elderly (53.4% vs. 32.5%, p=0.009), but there was no significant difference in mortality between immunosuppresed non-elderly patients and non-immunosuppressed non-elderly patients (33.5% vs. 26.0%, p=0.541). In all of the three logistic regression models, we found that early immunosuppression was independently associated with increased hospital mortality in elderly, but not in non-elderly patients. Sensitivity analysis further confirmed the definition of early immune status did not affect the outcomes. In addition, immune status improvement on day 3 was associated with reduced hospital mortality in both elderly and non-elderly patients. Conclusion: In adult patients with sepsis, the elderly were more susceptible to early immunosuppression after onset of sepsis. Early immunosuppression was independently associated with poor prognosis in elderly patients. Trial registration: ClinicalTrials.gov NCT00711620 , 9 July 2008, https://clinicaltrials.gov/ct2/show/NCT00711620

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