Dataset Information

External Validation of the ELAN-HF Score, Predicting 6-Month All-Cause Mortality in Patients Hospitalized for Acute Decompensated Heart Failure.

ABSTRACT: Background Our aim was to calibrate and externally revalidate the ELAN-HF (European Collaboration on Acute Decompensated Heart Failure) score, to confirm and improve on a previous external validation of the risk score. Methods and Results The ELAN-HF score predicts 6-month all-cause mortality in patients hospitalized for acute decompensated heart failure using absolute and percentage change of NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels in addition to clinical variables. For the external validation, we used the PRIMA II (Can NT-proBNP-Guided Therapy During Hospital Admission for Acute Decompensated Heart Failure Reduce Mortality and Readmissions?) trial. For both data sets, observed versus predicted mortality was compared for the 4 risk categories; and the mean predicted mortality was plotted against the observed mortality with calculation of a correlation coefficient and SEE. The model discriminant ability was determined by comparing the C-statistics for both data sets. The predicted versus actual 6-month mortality values in the derivation cohort were 3.7% versus 3.6% for the low-risk category, 9.4% versus 9.2% for the intermediate-risk category, 24.2% versus 23.5% for the high-risk category, and 54.2% versus 51.1% for the very-high-risk category. The correlation between predicted and observed mortality by deciles was 0.92, with an SEE of ±4%. In the validation cohort, predicted versus actual 6-month mortality values were 3.0% versus 2.2% for the low-risk category, 9.4% versus 8.2% for the intermediate-risk category, 25.0% versus 22.9% for the high-risk category, and 56.8% versus 53.6% for the very-high-risk category. The correlation between predicted and actual mortality by quintiles was 0.99, with an SEE of ±2%. There was no significant difference in C-statistic between the derivation cohort (0.78; 95% CI, 0.74-0.82) and the validation cohort (0.77; 95% CI, 0.69-0.84; P=0.693). Conclusions Our study confirms that the ELAN-HF score predicts accurately 6-month mortality in patients hospitalized for acute decompensated heart failure with the use of easily obtained characteristics.

SUBMITTER: Salah K

PROVIDER: S-EPMC6662127 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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External Validation of the ELAN-HF Score, Predicting 6-Month All-Cause Mortality in Patients Hospitalized for Acute Decompensated Heart Failure.

Salah Khibar K Stienen Susan S Moons Andreas H M AHM Bakx Adrianus L M ALM van Pol Petra E PE Kortz R A Mikael RAM Ferreira João Pedro JP Marques Irene I Schroeder-Tanka Jutta M JM Keijer Jan T JT Bayes-Genis Antoni A Pinto Yigal M YM Tijssen Jan G JG Kok Wouter E WE

Journal of the American Heart Association 20190712 14

Background Our aim was to calibrate and externally revalidate the ELAN-HF (European Collaboration on Acute Decompensated Heart Failure) score, to confirm and improve on a previous external validation of the risk score. Methods and Results The ELAN-HF score predicts 6-month all-cause mortality in patients hospitalized for acute decompensated heart failure using absolute and percentage change of NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels in addition to clinical variables. For the ...[more]

PMID: 31296084

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Project description:The ADA (Age-D-dimer-Albumin) score was developed to identify hospitalized patients at an increased risk for thrombosis in the coronavirus infectious disease-19 (COVID-19) setting. The study aimed to validate the ADA score for predicting thrombosis in a non-COVID-19 medically ill population from the APEX trial. The APEX trial was a multinational, randomized trial that evaluated the efficacy and safety of betrixaban vs. enoxaparin among acutely ill hospitalized patients at risk for venous thromboembolism. The study endpoints included the composite of arterial or venous thrombosis and its components. Metrics of model calibration and discrimination were computed for assessing the performance of the ADA score as compared to the IMPROVE score, a well-validated VTE risk assessment model. Among 7,119 medical inpatients, 209 (2.9%) had a thrombosis event up to 77 days of follow-up. The ADA score demonstrated good calibration for both arterial and venous thrombosis, whereas the IMPROVE score had adequate calibration for venous thrombosis (p > 0.05 from the Hosmer-Lemeshow test). For discriminating arterial and venous thrombosis, there was no significant difference between the ADA vs. IMPROVE score (c statistic = 0.620 [95% CI: 0.582 to 0.657] vs. 0.590 [95% CI: 0.556 to 0.624]; ∆ c statistic = 0.030 [95% CI: -0.022 to 0.081]; p = 0.255). Similarly, for discriminating arterial thrombosis, there was no significant difference between the ADA vs. IMPROVE score (c statistic = 0.582 [95% CI: 0.534 to 0.629] vs. 0.609 [95% CI: 0.564 to 0.653]; ∆ c statistic = -0.027 [95% CI: -0.091 to 0.036]; p = 0.397). For discriminating venous thrombosis, the ADA score was modestly superior to the IMPROVE score (c statistic = 0.664 [95% CI: 0.607 to 0.722] vs. 0.573 [95% CI: 0.521 to 0.624]; ∆ c statistic = 0.091 [95% CI: 0.011 to 0.172]; p = 0.026). The ADA score had a higher sensitivity (0.579 [95% CI: 0.512 to 0.646]; vs. 0.440 [95% CI: 0.373 to 0.507]) but lower specificity (0.625 [95% CI: 0.614 to 0.637] vs. 0.747 [95% CI: 0.737 to 0.758]) than the IMPROVE score for predicting thrombosis. Among acutely ill hospitalized medical patients enrolled in the APEX trial, the ADA score demonstrated good calibration but suboptimal discrimination for predicting thrombosis. The findings support the use of either the ADA or IMPROVE score for thrombosis risk assessment. The applicability of the ADA score to non-COVID-19 populations warrants further research.Clinical Trial Registration: http://www.clinicaltrials.gov . Unique identifier: NCT01583218.

Project description:BackgroundWith higher adoption of electronic health records at health-care centers, electronic search algorithms (computable phenotype) for identifying acute decompensated heart failure (ADHF) among hospitalized patients can be an invaluable tool to enhance data abstraction accuracy and efficacy in order to improve clinical research accrual and patient centered outcomes. We aimed to derive and validate a computable phenotype for ADHF in hospitalized patients.MethodsWe screened 256, 443 eligible (age > 18 years and with prior research authorization) individuals who were admitted to Mayo Clinic Hospital in Rochester, MN, from January 1, 2006, through December 31, 2014. Using a randomly selected derivation cohort of 938 patients, several iterations of a free-text electronic search were developed and refined. The computable phenotype was subsequently validated in an independent cohort 100 patients. The sensitivity and specificity of the computable phenotype were compared to the gold standard (expert review of charts) and International Classification of Diseases-9 (ICD-9) codes for Acute Heart Failure.ResultsIn the derivation cohort, the computable phenotype achieved a sensitivity of 97.5%, and specificity of 100%, whereas ICD-9 codes for Acute Heart Failure achieved a sensitivity of 47.5% and specificity of 96.7%. When all Heart Failure codes (ICD-9) were used, sensitivity and specificity were 97.5 and 86.6%, respectively. In the validation cohort, the sensitivity and specificity of the computable phenotype were 100 and 98.5%. The sensitivity and specificity for the ICD-9 codes (Acute Heart Failure) were 42 and 98.5%. Upon use of all Heart Failure codes (ICD-9), sensitivity and specificity were 96.8 and 91.3%.ConclusionsOur results suggest that using computable phenotype to ascertain ADHF from the clinical notes contained within the electronic medical record are feasible and reliable. Our computable phenotype outperformed ICD-9 codes for the detection of ADHF.

Project description:BackgroundThe CARDOT scores have been developed for prediction of respiratory complications after thoracic surgery. This study aimed to externally validate the CARDOT score and assess the predictive value of preoperative neutrophil-to-lymphocyte ratio (NLR) for postoperative respiratory complication.MethodsA retrospective cohort study of consecutive thoracic surgical patients at a single tertiary hospital in northern Thailand was conducted. The development and validation datasets were collected between 2006 and 2012 and from 2015 to 2021, respectively. Six prespecified predictive factors were identified, and formed a predictive score, the CARDOT score (chronic obstructive pulmonary disease, American Society of Anesthesiologists physical status, right-sided operation, duration of surgery, preoperative oxygen saturation on room air, thoracotomy), was calculated. The performance of the CARDOT score was evaluated in terms of discrimination by using the area under the receiver operating characteristic (AuROC) curve and calibration.ResultsThere were 1086 and 1645 patients included in the development and validation datasets. The incidence of respiratory complications was 15.7% (171 of 1086) and 22.5% (370 of 1645) in the development and validation datasets, respectively. The CARDOT score had good discriminative ability for both the development and validation datasets (AuROC 0.789 (95% CI 0.753-0.827) and 0.758 (95% CI 0.730-0.787), respectively). The CARDOT score showed good calibration in both datasets. A high NLR (≥ 4.5) significantly increased the risk of respiratory complications after thoracic surgery (P < 0.001). The AuROC curve of the validation cohort increased to 0.775 (95% CI 0.750-0.800) when the score was combined with a high NLR. The AuROC of the CARDOT score with the NLR showed significantly greater discrimination power than that of the CARDOT score alone (P = 0.008).ConclusionsThe CARDOT score showed a good discriminative performance in the external validation dataset. An addition of a high NLR significantly increases the predictive performance of CARDOT score. The utility of this score is valuable in settings with limited access to preoperative pulmonary function testing.

Project description:ObjectivesPulmonary complications remain a frequent cause of morbidity in patients undergoing oesophagectomy. Risk screening tools assist in patient stratification. Ferguson proposed a risk score system to predict major pulmonary complications after oesophagectomy. Our objective was to externally validate this risk score system.MethodsWe analysed our institutional database for patients undergoing oesophagectomy for cancer from August 2009 to December 2012. We analysed patients who had complete documentation of variables used in the Ferguson risk score calculation: forced expiratory volume in the 1 s, diffusion capacity of the lung for carbon monoxide, performance status and age. One hundred and thirty-six patients qualified for analysis in the validation study. Outcome variables measured included major pulmonary complications, defined as need for reintubation for respiratory failure and pneumonia. The risk score was then calculated for each individual based on the model. Incidence of major pulmonary events was assessed in the five risk class groupings to assess the discriminative ability of the Ferguson score.ResultsMajor pulmonary complications occurred in 35% of patients (47/136). Overall mortality was 6% (8/136). Patients were grouped into five risk categories according to their Ferguson pulmonary risk score: 0-2, 8 patients (6%); 3-4, 24 patients (18%); 5-6, 49 patients (36%); 29 patients (21%); 9-14, 26 patients (19%). The incidence of major pulmonary complications in these categories was 0, 17, 20, 41 and 77%, respectively. The accuracy of the risk score system for predicting major pulmonary complications was 76% (P < 0.0001).ConclusionsThis pulmonary risk scoring system is a reliable instrument to be used during the preoperative phase to differentiate patients who may be at higher risk for pulmonary complications after oesophagectomy. These data can assist in patient selection, and in patient education/informed consent and can guide postoperative management.

Dataset Information

External Validation of the ELAN-HF Score, Predicting 6-Month All-Cause Mortality in Patients Hospitalized for Acute Decompensated Heart Failure.

Publications

External Validation of the ELAN-HF Score, Predicting 6-Month All-Cause Mortality in Patients Hospitalized for Acute Decompensated Heart Failure.

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