scholarly journals A Comparison of the Performance of Out-of-hospital Cardiac Arrest Score and Standard Severity Scores in Predicting Hospital Mortality and Neurological Consequence in Out-of-hospital Cardiac Arrest Patients

2021 ◽  
Author(s):  
Natthaka Sathaporn ◽  
Bodin Khwannimit
Keyword(s):  
Cardiac Arrest ◽  
Hospital Mortality ◽  
Apache Ii ◽  
Secondary Outcome ◽  
Saps 3 ◽  
Saps Ii ◽  
Severity Scores ◽  
Overall Performance ◽  
Hospital Cardiac Arrest ◽  
Better Than

Objective: There is limited data to determine the performance of general and specific severity score in out-of-hospital cardiac arrest (OHCA) patients. Hence, we compared the performance of the OHCA score with Acute Physiology and Chronic Health Evaluation (APACHE) and Simplified Acute Physiology Score (SAPS) to predict outcome in OHCA patients.Material and Methods: A retrospective study was conducted in a mixed intensive care unit of a tertiary hospital. The primary outcome was in-hospital mortality. The secondary outcome was poor neurological outcome.Results: A total of 190 OHCA patients were enrolled. The OHCA score had moderate discrimination with an area under the receiver operating characteristic curve (AUC) 0.77 (95% CI 0.7-0.837) whereas discrimination of APACHE II-IV, SAPS II, and SAPS 3 were good with an AUC more than 0.8. The actual hospital mortality rate was 64.7%. The OHCA score predicted hospital mortality of 95.3±8.4, which significantly overestimated the mortality with standardized mortality ratio 0.68 (95% CI 0.56-0.81). However, all severity scores revealed poor calibration. Additionally, overall performance of APACHE II-IV, SAPS II and SAPS 3 were better than the OHCA score. For secondary outcome, discrimination of the OHCA score was moderate with an AUC 0.790 (95% CI 0.700-0.878) whereas other severity scores demonstrated good discrimination with AUC more than 0.8.Conclusion: APACHE II-IV, SAPS II, and SAPS 3 indicated superior overall performance and demonstrated good discrimination for predicting hospital mortality and unfavorable neurological consequence better than the OHCA score. However, all severity scores attested poor calibration, therefore, specific scores for OHCA patients should be modified.

Predictive Values of Initial Severity Scores at Intensive Care Unit Admission for Patients With Overnight or Prolonged Stay

2021 ◽  
Author(s):  
Koji Hosokawa ◽  
Nobuaki Shime
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Predictive Value ◽  
Apache Ii ◽  
Icu Patients ◽  
Prolonged Stay ◽  
Saps Ii ◽  
Icu Stay ◽  
Severity Scores

Abstract Background: The predictive value of disease severity scores for intensive care unit (ICU) patients is occasionally inaccurate because ICU patients with mild symptoms are also considered. We, thus, aimed to evaluate the accuracy of severity scores in predicting mortality of patients with complicated conditions admitted for > 24 hours. Methods: Overall, 35,353 adult patients using nationwide ICU data were divided into two groups: (1) overnight ICU stay after elective surgery and alive on discharge within 24 hours and (2) death within 24 hours or prolonged stay. The performance and accuracy of Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation (APACHE) II and III, and Simplified Acute Physiology Score (SAPS) II scores in predicting in-hospital mortality were evaluated. Results: In the overnight stay group, the correlation between SOFA and APACHE III scores or SAPS II was low because many had a SOFA score of 0. In the prolonged stay group, the predictive value of SAPS II and APACHE II and III showed high accuracy but that of SOFA was moderate. Conclusions: When overnight ICU stay patients were not included, the high predictive value for in-hospital mortality of SAPS II and APACHE II and III was evident.

scholarly journals Prognostic value of plasma pentraxin 3 levels in patients with septic shock admitted to intensive care

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243849
Author(s):  
S. Perez-San Martin ◽  
B. Suberviola ◽  
M. T. Garcia-Unzueta ◽  
B. A. Lavin ◽  
S. Campos ◽  
...  
Keyword(s):  
Septic Shock ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Prognostic Value ◽  
Positive Association ◽  
Serum Levels ◽  
Apache Ii ◽  
Predictive Capacity ◽  
Saps Ii ◽  
Severity Scores

Objective To evaluate the usefulness of a new marker, pentraxin, as a prognostic marker in septic shock patients. Materials and methods Single-centre prospective observational study that included all consecutive patients 18 years or older who were admitted to the intensive care unit (ICU) with septic shock. Serum levels of procalcitonin (PCT), C-reactive protein (CRP) and pentraxin (PTX3) were measured on ICU admission. Results Seventy-five septic shock patients were included in the study. The best predictors of in-hospital mortality were the severity scores: SAPS II (AUC = 0.81), SOFA (AUC = 0.79) and APACHE II (AUC = 0.73). The ROC curve for PTX3 (ng/mL) yielded an AUC of 0.70, higher than the AUC for PCT (0.43) and CRP (0.48), but lower than lactate (0.79). Adding PTX3 to the logistic model increased the predictive capacity in relation to SAPS II, SOFA and APACHE II for in-hospital mortality (AUC 0.814, 0.795, and 0.741, respectively). In crude regression models, significant associations were found between in-hospital mortality and PTX3. This positive association increased after adjusting for age, sex and immunosuppression: adjusted OR T3 for PTX3 = 7.83, 95% CI 1.35–45.49, linear P trend = 0.024. Conclusion Our results support the prognostic value of a single determination of plasma PTX3 as a predictor of hospital mortality in septic shock patients.

scholarly journals Echocardiographic parameters during prolonged targeted temperature Management in out-of-hospital Cardiac Arrest Survivors to predict neurological outcome – a post-hoc analysis of the TTH48 trial

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Thomas Hvid Jensen ◽  
Peter Juhl-Olsen ◽  
Bent Roni Ranghøj Nielsen ◽  
Johan Heiberg ◽  
Christophe Henri Valdemar Duez ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Neurological Outcome ◽  
Global Longitudinal Strain ◽  
Left Ventricular ◽  
Targeted Temperature Management ◽  
Temperature Management ◽  
Left Ventricular Ejection ◽  
Secondary Outcome ◽  
Ventricular Ejection Fraction ◽  
Hospital Cardiac Arrest

Abstract Background Transthoracic echocardiographic (TTE) indices of myocardial function among survivors of out-of-hospital cardiac arrest (OHCA) have been related to neurological outcome; however, results are inconsistent. We hypothesized that changes in average peak systolic mitral annular velocity (s’) from 24 h (h) to 72 h following start of targeted temperature management (TTM) predict six-month neurological outcome in comatose OHCA survivors. Methods We investigated the association between peak systolic velocity of the mitral plane (s’) and six-month neurological outcome in a population of 99 patients from a randomised controlled trial comparing TTM at 33 ± 1 °C for 24 h (h) (n = 47) vs. 48 h (n = 52) following OHCA (TTH48-trial). TTE was conducted at 24 h, 48 h, and 72 h after reaching target temperature. The primary outcome was 180 days neurological outcome assessed by Cerebral Performance Category score (CPC180) and the primary TTE outcome measure was s’. Secondary outcome measures were left ventricular ejection fraction (LVEF), global longitudinal strain (GLS), e’, E/e’ and tricuspid annular plane systolic excursion (TAPSE). Results Across all three scan time points s’ was not associated with neurological outcome (ORs: 24 h: 1.0 (95%CI: 0.7–1.4, p = 0.98), 48 h: 1.13 (95%CI: 0.9–1.4, p = 0.34), 72 h: 1.04 (95%CI: 0.8–1.4, p = 0.76)). LVEF, GLS, E/e’, and TAPSE recorded on serial TTEs following OHCA were neither associated with nor did they predict CPC180. Estimated median e’ at 48 h following TTM was 5.74 cm/s (95%CI: 5.27–6.22) in patients with good outcome (CPC180 1–2) vs. 4.95 cm/s (95%CI: 4.37–5.54) in patients with poor outcome (CPC180 3–5) (p = 0.04). Conclusions s’ assessed on serial TTEs in comatose survivors of OHCA treated with TTM was not associated with CPC180. Our findings suggest that serial TTEs in the early post-resuscitation phase during TTM do not aid the prognostication of neurological outcome following OHCA. Trial registration NCT02066753. Registered 14 February 2014 – Retrospectively registered,

In-hospital mortality after out-of-hospital cardiac arrest

The Lancet ◽  
1995 ◽  
Vol 346 (8972) ◽  
pp. 417-421 ◽  
Author(s):  
N.R Grubb ◽  
K.A.A Fox ◽  
R.A Elton
Keyword(s):  
Cardiac Arrest ◽  
Hospital Mortality ◽  
Hospital Cardiac Arrest

Abstract 11372: A Risk-Adjustment Model for Patients Presenting to Hospitals with Out-of-Hospital Cardiac Arrest and ST-Elevation Myocardial Infarction

Circulation ◽  
2021 ◽  
Vol 144 (Suppl_2) ◽  
Author(s):  
Andy T Tran ◽  
Anthony Hart ◽  
John Spertus ◽  
Philip Jones ◽  
Bryan McNally ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Hospital Mortality ◽  
Risk Adjustment ◽  
Quality Measures ◽  
Coronary Intervention ◽  
Spontaneous Circulation ◽  
Logistic Regression Models ◽  
Adjustment Model ◽  
Risk Adjustment Model ◽  
Hospital Cardiac Arrest

Background: Given the diversity of patients resuscitated from out-of-hospital cardiac arrest (OHCA) complicated by STEMI, adequate risk adjustment is needed to account for potential differences in case-mix to reflect the quality of percutaneous coronary intervention. Objectives: We sought to build a risk-adjustment model of in-hospital mortality outcomes for patients with OHCA and STEMI requiring emergent angiography. Methods: Within the Cardiac Arrest Registry to Enhance Survival, we included adult patients with OHCA and STEMI who underwent angiography within 2 hours from January 2013 to December 2019. Using pre-hospital patient and arrest characteristics, multivariable logistic regression models were developed for in-hospital mortality. We then described model calibration, discrimination, and variability in patients’ unadjusted and adjusted mortality rates. Results: Of 2,999 hospitalized patients with OHCA and STEMI who underwent emergent angiography (mean age 61.2 ±12.0, 23.1% female, 64.6% white), 996 (33.2%) died. The final risk-adjustment model for mortality included higher age, unwitnessed arrest, non-shockable rhythms, not having sustained return of spontaneous circulation upon hospital arrival, and higher total resuscitation time on scene ( C -statistic, 0.804 with excellent calibration). The risk-adjusted proportion of patients died varied substantially and ranged from 7.8% at the 10 th percentile to 74.5% at the 90 th percentile (Figure). Conclusions: Through leveraging data from a large, multi-site registry of OHCA patients, we identified several key factors for better risk-adjustment for mortality-based quality measures. We found that STEMI patients with OHCA have highly variable mortality risk and should not be considered as a single category in public reporting. These findings can lay the foundation to build quality measures to further optimize care for the patient with OHCA and STEMI.

Abstract 13131: The Priority of Coronary Arteriography and Therapeutic Hypothermia After Return of Spontaneous Circulation in Patients With Out-of-hospital Cardiac Arrest. the Result of Sos-kanto 2012 Study

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Shuichi Hagiwara ◽  
Kiyohiro Oshima ◽  
Masato Murata ◽  
Makoto Aoki ◽  
Kei Hayashida ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Therapeutic Hypothermia ◽  
Statistical Significance ◽  
Coronary Arteriography ◽  
Spontaneous Circulation ◽  
P Value ◽  
Return Of Spontaneous Circulation ◽  
Overall Performance ◽  
The Mean ◽  
Hospital Cardiac Arrest

Aim: To evaluate the priority of coronary angiography (CAG) and therapeutic hypothermia therapy (TH) after return of spontaneous circulation (ROSC) in patients with out-of-hospital cardiac arrest (OHCA). Patients and Methods: SOS-KANTO 2012 study is a prospective, multicenter (69 emergency hospitals) and observational study and includes 16,452 patients with OHCA. Among the cases with ROSC in that study, we intended for patients treated with both CAG and TH within 24 hours after arrival. Those patients were divided into two groups; patients in whom TH was firstly performed (TH group), and the others in whom CAG was firstly done (CAG group). We statistically compared the prognosis between the two groups. SPSS Statistics 22 (IBM, Tokyo, Japan) was used for the statistical analysis. Statistical significance was assumed to be present at a p value of less than 0.05. Result: 233 patients were applied in this study. There were 86 patients in the TH group (M/F: 74/12, mean age; 60.0±15.2 y/o) and 147 in the CAG group (M/F: 126/21, mean age: 63.4±11.1 y/o) respectively, and no significant differences were found in the mean age and M/F ratio between the two groups. The overall performance categories (OPC) one month after ROSC in the both groups were as follows; in the TH group, OPC1: 21 (24.4%), OPC2: 3 (3.5%), OPC3: 7 (8.1%), OPC4: 8 (9.3%), OPC5: 43 (50.0%), unknown: 4 (4.7%), and in the CAG group, OPC1: 38 (25.9%), OPC2: 13 (8.8%), OPC3: 15 (10.2%), OPC4: 18 (12.2%), OPC5: 57 (38.8%), unknown: 6 (4.1%). There were no significant differences in the prognosis one month after ROSC between the two groups. Conclusion: The results which of TH and CAG you give priority to over do not affect the prognosis in patients with OHCA.

scholarly journals Improvement of APACHE II score system for disease severity based on XGBoost algorithm

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yan Luo ◽  
Zhiyu Wang ◽  
Cong Wang
Keyword(s):  
Intensive Care ◽  
Hospital Mortality ◽  
Patient Outcomes ◽  
External Validation ◽  
Apache Ii ◽  
Validation Dataset ◽  
Apache Ii Score ◽  
Severity Scores ◽  
The Impact ◽  
Improve Patient

Abstract Background Prognostication is an essential tool for risk adjustment and decision making in the intensive care units (ICUs). In order to improve patient outcomes, we have been trying to develop a more effective model than Acute Physiology and Chronic Health Evaluation (APACHE) II to measure the severity of the patients in ICUs. The aim of the present study was to provide a mortality prediction model for ICUs patients, and to assess its performance relative to prediction based on the APACHE II scoring system. Methods We used the Medical Information Mart for Intensive Care version III (MIMIC-III) database to build our model. After comparing the APACHE II with 6 typical machine learning (ML) methods, the best performing model was screened for external validation on anther independent dataset. Performance measures were calculated using cross-validation to avoid making biased assessments. The primary outcome was hospital mortality. Finally, we used TreeSHAP algorithm to explain the variable relationships in the extreme gradient boosting algorithm (XGBoost) model. Results We picked out 14 variables with 24,777 cases to form our basic data set. When the variables were the same as those contained in the APACHE II, the accuracy of XGBoost (accuracy: 0.858) was higher than that of APACHE II (accuracy: 0.742) and other algorithms. In addition, it exhibited better calibration properties than other methods, the result in the area under the ROC curve (AUC: 0.76). we then expand the variable set by adding five new variables to improve the performance of our model. The accuracy, precision, recall, F1, and AUC of the XGBoost model increased, and were still higher than other models (0.866, 0.853, 0.870, 0.845, and 0.81, respectively). On the external validation dataset, the AUC was 0.79 and calibration properties were good. Conclusions As compared to conventional severity scores APACHE II, our XGBoost proposal offers improved performance for predicting hospital mortality in ICUs patients. Furthermore, the TreeSHAP can help to enhance the understanding of our model by providing detailed insights into the impact of different features on the disease risk. In sum, our model could help clinicians determine prognosis and improve patient outcomes.

Sign in / Sign up

Export Citation Format

Share Document