scholarly journals Associations of On-arrival Vital Signs with 24-hour In-hospital Mortality in Adult Trauma Patients Admitted to Four Public University Hospitals in Urban India: A Prospective Multi-Centre Cohort Study

Injury ◽  
2021 ◽  
Author(s):  
Bhakti Sarang ◽  
Prashant Bhandarkar ◽  
Nakul Raykar ◽  
Gerard M O Reilly ◽  
Kapil Dev Soni ◽  
...  
Keyword(s):  
Cohort Study ◽  
Hospital Mortality ◽  
Vital Signs ◽  
Public University ◽  
Trauma Patients ◽  
University Hospitals ◽  
Urban India

Association Between AND‐ASPEN Malnutrition Criteria and Hospital Mortality in Critically Ill Trauma Patients: A Prospective Cohort Study

2020 ◽  
Vol 44 (7) ◽  
pp. 1347-1354 ◽  
Author(s):  
Guilherme Duprat Ceniccola ◽  
Aline Bassetto Okamura ◽  
Jeane da Silva Sepúlveda Neta ◽  
Fernanda Cintra Lima ◽  
Andressa Cristina Santos de Deus ◽  
...  
Keyword(s):  
Cohort Study ◽  
Hospital Mortality ◽  
Critically Ill ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Trauma Patients

scholarly journals Predictors of Mortality and Prehospital Monitoring Limitations in Blunt Trauma Patients

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Matej Strnad ◽  
Vesna Borovnik Lesjak ◽  
Vitka Vujanović ◽  
Tine Pelcl ◽  
Miljenko Križmarić
Keyword(s):  
Hospital Mortality ◽  
Regression Model ◽  
Blunt Trauma ◽  
Injury Severity ◽  
Vital Signs ◽  
Study Groups ◽  
Multivariate Logistic Regression Model ◽  
Hospital Death ◽  
Trauma Patients ◽  
Arterial Blood

This study aimed at determining predictors of in-hospital mortality and prehospital monitoring limitations in severely injured intubated blunt trauma patients. We retrospectively reviewed patients’ charts. Prehospital vital signs, Injury Severity Score (ISS), initial Glasgow Coma Scale (GCS), Revised Trauma Score (RTS), arterial blood gases, and lactate were compared in two study groups: survivors (n=40) and nonsurvivors (n=30). There were no significant differences in prehospital vital signs between compared groups. Nonsurvivors were older (P=0.006), with lower initial GCS (P<0.001) and higher ISS (P<0.001), along with higher lactate (P<0.001) and larger base deficit (BD;P=0.006), whereas RTS (P=0.001) was lower in nonsurvivors. For predicting mortality, area under the curve (AUC) was calculated: for lactate 0.82 (P<0.001), for ISS 0.82 (P<0.001), and for BD 0.69 (P=0.006). Lactate level of 3.4 mmol/L or more was 82% sensitive and 75% specific for predicting in-hospital death. In a multivariate logistic regression model, ISS (P=0.037), GCS (P=0.033), and age (P=0.002) were found to be independent predictors of in-hospital mortality. The AUC for regression model was 0.93 (P<0.001). Increased levels of lactate and BD on admission indicate more severe occult hypoperfusion in nonsurvivors whereas vital signs did not differ between the groups.

Patient-Level and Hospital-Level Risk Factors for In-Hospital Mortality in Patients Ventilated for More Than 24 Hours: Results of a Nationwide Cohort Study

2020 ◽  
pp. 088506662094218
Author(s):  
Olaf Schoffer ◽  
Martin Roessler ◽  
Felix Walther ◽  
Maria Eberlein-Gonska ◽  
Peter C. Scriba ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Relative Risk ◽  
Hospital Mortality ◽  
Study Patient ◽  
Hospital Death ◽  
Hospital Level ◽  
University Hospitals ◽  
Emergency Case ◽  
Patient Level

Background: Prolonged ventilation is associated with a high risk of death. This study investigated both patient-level and hospital-level risk factors for in-hospital mortality in patients ventilated for more than 24 hours. Methods: The analyses were conducted in the framework of a German national multicenter retrospective cohort study. Patient and hospital characteristics were examined using descriptive statistics. Risk factors of in-hospital mortality were analyzed using multilevel robust Poisson regressions for binary outcomes. Potential effect modifications were examined by stratified analyses. Results: The sample includes 95 672 cases of patients ventilated >24 hours in 163 hospitals covering the period 2016 to 2017. According to the results of multilevel Poisson regressions, main patient-level risk factors for in-hospital mortality were age (per year relative risk [RR] = 1.021, 95% CI = 1.020-1.023), stroke (RR = 1.459; 95% CI = 1.361-1.563), emergency case admission (RR = 1.273, 95% CI = 1.156-1.403), and transfer from another hospital (RR = 1.169, 95% CI = 1.084-1.261). The individual risk of in-hospital death was positively associated with hospital size (RR of hospitals with 600-799 beds vs <100 beds = 1.412, 95% CI = 1.095-1.820) and negatively related to cumulated ventilation patient time (per 1000 days RR = 0.995, 95% CI = 0.993-0.996). University hospital status was identified as an effect modifier, particularly with regard to the patients’ admission reasons. The RR of in-hospital death in patients admitted after transfer from another hospital was higher in university hospitals (RR = 1.456, 95% CI = 1.298-1.634) compared to nonuniversity hospitals (RR = 1.077, 95% CI = 1.019-1.139). Likewise, patients admitted as emergency case had a higher relative risk in university hospitals (RR = 1.619, 95% CI = 1.359-1.929) than in nonuniversity hospitals (RR = 1.141, 95% CI = 1.080-1.205). Conclusion: By providing evidence on multiple patient-level and hospital-level risk factors for in-hospital mortality in patients ventilated for more than 24 hours, this large multicenter study has main implications for quality assessment of clinical care and the adequate specification of risk adjustment models. The revealed effect modifications indicate the relevance of stratified analyses.

Sign in / Sign up

Export Citation Format

Share Document