scholarly journals Derivation and Validation of Clinical Prediction Models for Rapid Risk Stratification for Time-Sensitive Management for Acute Heart Failure

2020 ◽  
Vol 9 (11) ◽  
pp. 3394
Author(s):  
Yasuyuki Shiraishi ◽  
Shun Kohsaka ◽  
Takayuki Abe ◽  
Toshiyuki Nagai ◽  
Ayumi Goda ◽  
...  
Keyword(s):  
Heart Failure ◽  
Risk Stratification ◽  
Hospital Mortality ◽  
Acute Heart Failure ◽  
Mortality Risk ◽  
Mortality Rates ◽  
Validation Dataset ◽  
Stepwise Logistic Regression ◽  
Early Presentation ◽  
C Statistic

Early and rapid risk stratification of patients with acute heart failure (AHF) is crucial for appropriate patient triage and outcome improvements. We aimed to develop an easy-to-use, in-hospital mortality risk prediction tool based on data collected from AHF patients at their initial presentation. Consecutive patients’ data pertaining to 2006–2017 were extracted from the West Tokyo Heart Failure (WET-HF) and National Cerebral and Cardiovascular Center Acute Decompensated Heart Failure (NaDEF) registries (n = 4351). Risk model development involved stepwise logistic regression analysis and prospective validation using data pertaining to 2014–2015 in the Registry Focused on Very Early Presentation and Treatment in Emergency Department of Acute Heart Failure Syndrome (REALITY-AHF) (n = 1682). The final model included data describing six in-hospital mortality risk predictors, namely, age, systolic blood pressure, blood urea nitrogen, serum sodium, albumin, and natriuretic peptide (SOB-ASAP score), available at the time of initial triage. The model showed excellent discrimination (c-statistic = 0.82) and good agreement between predicted and observed mortality rates. The model enabled the stratification of the mortality rates across sixths (from 14.5% to <1%). When assigned a point for each associated factor, the integer score’s discrimination was similar (c-statistic = 0.82) with good calibration across the patients with various risk profiles. The models’ performance was retained in the independent validation dataset. Promptly determining in-hospital mortality risks is achievable in the first few hours of presentation; they correlate strongly with mortality among AHF patients, potentially facilitating clinical decision-making.

scholarly journals Risk stratification scores for patients with acute heart failure in the Emergency Department: A systematic review

2020 ◽  
Vol 9 (5) ◽  
pp. 375-398
Author(s):  
Òscar Miró ◽  
Xavier Rossello ◽  
Elke Platz ◽  
Josep Masip ◽  
Danielle M Gualandro ◽  
...  
Keyword(s):  
Heart Failure ◽  
Systematic Review ◽  
Emergency Department ◽  
Risk Stratification ◽  
Acute Heart Failure ◽  
Mortality Risk ◽  
Heart Failure Patients ◽  
Hospitalised Patients ◽  
Risk Grade ◽  
Estimation Of Risk

Aims This study aimed to systematically identify and summarise all risk scores evaluated in the emergency department setting to stratify acute heart failure patients. Methods and results A systematic review of PubMed and Web of Science was conducted including all multicentre studies reporting the use of risk predictive models in emergency department acute heart failure patients. Exclusion criteria were: (a) non-original articles; (b) prognostic models without predictive purposes; and (c) risk models without consecutive patient inclusion or exclusively tested in patients admitted to a hospital ward. We identified 28 studies reporting findings on 19 scores: 13 were originally derived in the emergency department (eight exclusively using acute heart failure patients), and six in emergency department and hospitalised patients. The outcome most frequently predicted was 30-day mortality. The performance of the scores tended to be higher for outcomes occurring closer to the index acute heart failure event. The eight scores developed using acute heart failure patients only in the emergency department contained between 4–13 predictors (age, oxygen saturation and creatinine/urea included in six scores). Five scores (Emergency Heart Failure Mortality Risk Grade, Emergency Heart Failure Mortality Risk Grade 30 Day mortality ST depression, Epidemiology of Acute Heart Failure in Emergency department 3 Day, Acute Heart Failure Risk Score, and Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure) have been externally validated in the same country, and two (Emergency Heart Failure Mortality Risk Grade and Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure) further internationally validated. The c-statistic for Emergency Heart Failure Mortality Risk Grade to predict seven-day mortality was between 0.74–0.81 and for Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure to predict 30-day mortality was 0.80–0.84. Conclusions There are several scales for risk stratification of emergency department acute heart failure patients. Two of them are accurate, have been adequately validated and may be useful in clinical decision-making in the emergency department i.e. about whether to admit or discharge.

scholarly journals Prospective Validation of the Emergency Heart Failure Mortality Risk Grade for Acute Heart Failure

Circulation ◽  
2019 ◽  
Vol 139 (9) ◽  
pp. 1146-1156 ◽  
Author(s):  
Douglas S. Lee ◽  
Jacques S. Lee ◽  
Michael J. Schull ◽  
Bjug Borgundvaag ◽  
Marcia L. Edmonds ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Heart Failure ◽  
Mortality Risk ◽  
Risk Grade

scholarly journals Is oxygen therapy beneficial for normoxemic patients with acute heart failure? A propensity score matched study

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yue Yu ◽  
Ren-Qi Yao ◽  
Yu-Feng Zhang ◽  
Su-Yu Wang ◽  
Wang Xi ◽  
...  
Keyword(s):  
Heart Failure ◽  
Linear Regression ◽  
Propensity Score ◽  
Hospital Mortality ◽  
Acute Heart Failure ◽  
Oxygen Therapy ◽  
Ambient Air ◽  
Supplemental Oxygen ◽  
Research Database ◽  
Icu Mortality

Abstract Background The clinical efficiency of routine oxygen therapy is uncertain in patients with acute heart failure (AHF) who do not have hypoxemia. The aim of this study was to investigate the association between oxygen therapy and clinical outcomes in normoxemic patients hospitalized with AHF using real-world data. Methods Normoxemic patients diagnosed with AHF on ICU admission from the electronic ICU (eICU) Collaborative Research Database were included in the current study, in which the study population was divided into the oxygen therapy group and the ambient-air group. Propensity score matching (PSM) was applied to create a balanced covariate distribution between patients receiving supplemental oxygen and those exposed to ambient air. Linear regression and logistic regression models were performed to assess the associations between oxygen therapy and length of stay (LOS), and all-cause in-hospital as well as ICU mortality rates, respectively. A series of sensitivity and subgroup analyses were conducted to further validate the robustness of our findings. Results A total of 2922 normoxemic patients with AHF were finally included in the analysis. Overall, 42.1% (1230/2922) patients were exposed to oxygen therapy, and 57.9% (1692/2922) patients did not receive oxygen therapy (defined as the ambient-air group). After PSM analysis, 1122 pairs of patients were matched: each patient receiving oxygen therapy was matched with a patient without receiving supplemental oxygen. The multivariable logistic model showed that there was no significant interaction between the ambient air and oxygen group for all-cause in-hospital mortality [odds ratio (OR) 1.30; 95% confidence interval (CI) 0.92–1.82; P = 0.138] or ICU mortality (OR 1.39; 95% CI 0.83–2.32; P = 0.206) in the post-PSM cohorts. In addition, linear regression analysis revealed that oxygen therapy was associated with prolonged ICU LOS (OR 1.11; 95% CI 1.06–1.15; P <  0.001) and hospital LOS (OR 1.06; 95% CI 1.01–1.10; P = 0.009) after PSM. Furthermore, the absence of an effect of supplemental oxygen on mortality was consistent in all subgroups. Conclusion Routine use of supplemental oxygen in AHF patients without hypoxemia was not found to reduce all-cause in-hospital mortality or ICU mortality.

scholarly journals Prediction of short-term mortality in acute heart failure patients using minimal electronic health record data

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ashwath Radhachandran ◽  
Anurag Garikipati ◽  
Nicole S. Zelin ◽  
Emily Pellegrini ◽  
Sina Ghandian ◽  
...  
Keyword(s):  
Heart Failure ◽  
Logistic Regression ◽  
Decision Tree ◽  
Risk Stratification ◽  
Acute Heart Failure ◽  
Model Performance ◽  
Machine Learning Techniques ◽  
Electronic Health Record Data ◽  
Test Set ◽  
Patient Disposition

Abstract Background Acute heart failure (AHF) is associated with significant morbidity and mortality. Effective patient risk stratification is essential to guiding hospitalization decisions and the clinical management of AHF. Clinical decision support systems can be used to improve predictions of mortality made in emergency care settings for the purpose of AHF risk stratification. In this study, several models for the prediction of seven-day mortality among AHF patients were developed by applying machine learning techniques to retrospective patient data from 236,275 total emergency department (ED) encounters, 1881 of which were considered positive for AHF and were used for model training and testing. The models used varying subsets of age, sex, vital signs, and laboratory values. Model performance was compared to the Emergency Heart Failure Mortality Risk Grade (EHMRG) model, a commonly used system for prediction of seven-day mortality in the ED with similar (or, in some cases, more extensive) inputs. Model performance was assessed in terms of area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. Results When trained and tested on a large academic dataset, the best-performing model and EHMRG demonstrated test set AUROCs of 0.84 and 0.78, respectively, for prediction of seven-day mortality. Given only measurements of respiratory rate, temperature, mean arterial pressure, and FiO2, one model produced a test set AUROC of 0.83. Neither a logistic regression comparator nor a simple decision tree outperformed EHMRG. Conclusions A model using only the measurements of four clinical variables outperforms EHMRG in the prediction of seven-day mortality in AHF. With these inputs, the model could not be replaced by logistic regression or reduced to a simple decision tree without significant performance loss. In ED settings, this minimal-input risk stratification tool may assist clinicians in making critical decisions about patient disposition by providing early and accurate insights into individual patient’s risk profiles.

scholarly journals Determinants of In-Hospital Mortality in Elderly Patients Aged 80 Years or above with Acute Heart Failure: A Retrospective Cohort Study at a Single Rural Hospital

2021 ◽  
Vol 10 (7) ◽  
pp. 1468
Author(s):  
Yusuke Watanabe ◽  
Kazuko Tajiri ◽  
Hiroyuki Nagata ◽  
Masayuki Kojima
Keyword(s):  
Heart Failure ◽  
Regression Analysis ◽  
Elderly Patients ◽  
Hospital Mortality ◽  
Acute Heart Failure ◽  
Stepwise Regression ◽  
Stepwise Regression Analysis ◽  
Antibiotic Administration ◽  
Very Elderly ◽  
Survivor Group

Heart failure is one of the leading causes of mortality worldwide. Several predictive risk scores and factors associated with in-hospital mortality have been reported for acute heart failure. However, only a few studies have examined the predictors in elderly patients. This study investigated determinants of in-hospital mortality in elderly patients with acute heart failure, aged 80 years or above, by evaluating the serum sodium, blood urea nitrogen, age and serum albumin, systolic blood pressure and natriuretic peptide levels (SOB-ASAP) score. We reviewed the medical records of 106 consecutive patients retrospectively and classified them into the survivor group (n = 83) and the non-survivor group (n = 23) based on the in-hospital mortality. Patient characteristics at admission and during hospitalization were compared between the two groups. Multivariate stepwise regression analysis was used to evaluate the in-hospital mortality. The SOB-ASAP score was significantly better in the survivor group than in the non-survivor group. Multivariate stepwise regression analysis revealed that a poor SOB-ASAP score, oral phosphodiesterase 3 inhibitor use, and requirement of early intravenous antibiotic administration were associated with in-hospital mortality in very elderly patients with acute heart failure. Severe clinical status might predict outcomes in very elderly patients.

scholarly journals The Effect of Frailty on 30‐day Mortality Risk in Older Patients With Acute Heart Failure Attended in the Emergency Department

2017 ◽  
Vol 24 (3) ◽  
pp. 298-307 ◽  
Author(s):  
Francisco Javier Martín‐Sánchez ◽  
Esther Rodríguez‐Adrada ◽  
Christian Mueller ◽  
María Teresa Vidán ◽  
Michael Christ ◽  
...  
Keyword(s):  
Heart Failure ◽  
Emergency Department ◽  
Acute Heart Failure ◽  
Mortality Risk ◽  
Older Patients
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