scholarly journals A Prediction Model to Identify Individuals at High Risk for Developing Heart Failure Using Administrative Data and Medical Records

2017 ◽  
Vol 23 (8) ◽  
pp. S77 ◽  
Author(s):  
David Steenhard ◽  
Yun Wei ◽  
Yanting Dong ◽  
George Andrews ◽  
Vipin Gopal
Keyword(s):  
Heart Failure ◽  
High Risk ◽  
Prediction Model ◽  
Administrative Data ◽  
Medical Records ◽  
Developing Heart

scholarly journals In-hospital and short-term predictors of mortality in patients with intermediate-high risk pulmonary embolism

2020 ◽  
Vol 12 (4) ◽  
pp. 321-327
Author(s):  
Gulay Gök ◽  
Mehmet Karadağ ◽  
Tufan Çinar ◽  
Zekeriya Nurkalem ◽  
Dursun Duman
Keyword(s):  
Heart Failure ◽  
Congestive Heart Failure ◽  
Pulmonary Embolism ◽  
High Risk ◽  
Hospital Mortality ◽  
Medical Records ◽  
Pulmonary Angiography ◽  
Albumin Level ◽  
Short Term ◽  
Acute Pe

Introduction: The aim of this study was to evaluate the in-hospital and short-term predictive factors of mortality in intermediate-high risk acute pulmonary embolism (PE) patients with right ventricle (RV)dysfunction and myocardial injury. Methods: In this retrospective study, the medical records of 187 patients with a diagnosis of intermediate high risk acute PE were evaluated. A contrast-enhanced multi-detector pulmonary angiography was used to confirm diagnosis in all cases. All-cause mortality was determined by obtaining both in hospital and 30 days follow-up data of patients from medical records. Results: During the in-hospital stay (9.5±4.72 days), 7 patients died, resulting in an acute PE related in-hospital mortality of 3.2%. Admission heart rate (HR), (Odds ratio (OR), 1.028 95% Confidence interval (CI), 0.002-1.121; P = 0.048) and blood urea nitrogen (BUN) (OR, 1.028 95% CI, 0.002-1.016; P = 0.044) were found to be independent predictors for in-hospital mortality in a multi variate logistic regression analysis. In total, 32 patients (20.9%) died during 30 days follow-up.The presence of congestive heart failure (OR, 0.015, 95%CI, 0.001-0.211; P = 0.002) and dementia (OR, 0.029, 95%CI,0.002-0.516; P = 0.016) as well as low albumin level (OR, 0.049 95%CI, 0.006-0.383; P = 0.049) were associated with 30 days mortality. Conclusion: HR and BUN were independent predictors of in-hospital mortality and the presence of congestive heart failure, dementia, and low albumin levels were associated with higher 30 days mortality.

Abstract 18870: Adjudicated versus “Administrative” Heart Failure With Preserved Ejection Fraction

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Andreas P Kalogeropoulos ◽  
Akash Patel ◽  
Song Li ◽  
Gregory Burkman ◽  
Lampros Papadimitriou ◽  
...  
Keyword(s):  
Heart Failure ◽  
Ejection Fraction ◽  
Administrative Data ◽  
Medical Records ◽  
Patient Characteristics ◽  
Preserved Ejection Fraction ◽  
Icd Codes ◽  
And Gender ◽  
Special Causes

Introduction: The proportion of heart failure (HF) with preserved ejection fraction (HFpEF) is reported to be as high as 40%-60% based on administrative data, but these estimates have not been clinically validated. Methods: We evaluated 1752 consecutive patients who received outpatient care during the first quarter of 2012 for an encounter ICD-9 code of 402.X1, 404.X1, 404.X3, or 428.XX. Medical records were reviewed for HF symptoms, signs, and treatment; last reported ejection fraction (EF); all previous EF documentations; and special causes of HF (congenital heart disease or specific cardiomyopathies). We classified confirmed HF cases not due to special causes into 3 mutually exclusive categories: (1) HFpEF: current EF >40% without any previous EF ≤40%; (2) HF with recovered EF (HFrecEF): current EF >40% but previous EF ≤40%; and (3) HF with reduced EF (HFrEF): current EF ≤40%. Results: HF was confirmed in 1652 cases (94.3%). Among these, 321 had HFpEF (19.4%; 95%CI 17.6-21.4); 268 had HFrecEF (16.2%; 95%CI 14.5-18.1); and 992 had HFrEF (60.0%; 95%CI 57.7-62.4); the remaining 71 cases (4.3%) had HF due to special causes. In comparison, the proportion of HFpEF on the basis of ICD codes and last EF without further adjudication would have been 39.0%. Patient characteristics are summarized in Table 1. After 2 years of follow up, age- and gender- adjusted mortality was 10.2% in HFrEF, 8.6% in HFpEF, and 4.4% in HFrecEF patients (stratified log-rank P=0.005), Fig. 1 . Conclusions: The proportion of clinically verified HFpEF is considerably lower compared to estimates from administrative data. Many patients with preserved EF actually represent HFrecEF, which has a more favorable prognosis.

scholarly journals A Prediction Model for Metachronous Peritoneal Carcinomatosis in Patients with Stage T4 Colon Cancer after Curative Resection

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2808
Author(s):  
Tzong-Yun Tsai ◽  
Jeng-Fu You ◽  
Yu-Jen Hsu ◽  
Jing-Rong Jhuang ◽  
Yih-Jong Chern ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Prediction Model ◽  
Prediction Error ◽  
Area Under The Curve ◽  
Low Risk ◽  
Brier Score ◽  
Individual Risk ◽  
T4 Colon Cancer ◽  
Testing Set

(1) Background: The aim of this study was to develop a prediction model for assessing individual mPC risk in patients with pT4 colon cancer. Methods: A total of 2003 patients with pT4 colon cancer undergoing R0 resection were categorized into the training or testing set. Based on the training set, 2044 Cox prediction models were developed. Next, models with the maximal C-index and minimal prediction error were selected. The final model was then validated based on the testing set using a time-dependent area under the curve and Brier score, and a scoring system was developed. Patients were stratified into the high- or low-risk group by their risk score, with the cut-off points determined by a classification and regression tree (CART). (2) Results: The five candidate predictors were tumor location, preoperative carcinoembryonic antigen value, histologic type, T stage and nodal stage. Based on the CART, patients were categorized into the low-risk or high-risk groups. The model has high predictive accuracy (prediction error ≤5%) and good discrimination ability (area under the curve >0.7). (3) Conclusions: The prediction model quantifies individual risk and is feasible for selecting patients with pT4 colon cancer who are at high risk of developing mPC.

External validation of a heart failure risk prediction model in a remote monitoring cohort submitted to cardiac resynchronization therapy

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
I Cardoso ◽  
M Coutinho ◽  
G Portugal ◽  
A Valentim ◽  
A.S Delgado ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
High Risk ◽  
Remote Monitoring ◽  
Hospital Admissions ◽  
External Validation ◽  
Left Ventricular Ejection ◽  
National Database ◽  
Failure Risk

Abstract Background Patients (P) submitted to cardiac ressynchronization therapy (CRT) are at high risk of heart failure (HF) events during follow-up. Continuous analysis of various physiological parameters, as reported by remote monitoring (RM), can contribute to point out incident HF admissions. Tailored evaluation, including multi-parameter modelling, may further increase the accuracy of such algorithms. Purpose Independent external validation of a commercially available algorithm (“Heart Failure Risk Status” HFRS, Medtronic, MN USA) in a cohort submitted to CRT implantation in a tertiary center. Methods Consecutive P submitted to CRT implantation between January 2013 and September 2019 who had regular RM transmissions were included. The HFRS algorithm includes OptiVol (Medtronic Plc., MN, USA), patient activity, night heart rate (NHR), heart rate variability (HRV), percentage of CRT pacing, atrial tachycardia/atrial fibrillation (AT/AF) burden, ventricular rate during AT/AF (VRAF), and detected arrhythmia episodes/therapy delivered. P were classified as low, medium or high risk. Hospital admissions were systematically assessed by use of a national database (“Plataforma de Dados de Saúde”). Accuracy of the HFRS algorithm was evaluated by random effects logistic regression for the outcome of unplanned hospital admission for HF in the 30 days following each transmission episode. Results 1108 transmissions of 35 CRT P, corresponding to 94 patient-years were assessed. Mean follow-up was 2.7 yrs. At implant, age was 67.6±9.8 yrs, left ventricular ejection fraction 28±7.8%, BNP 156.6±292.8 and NYHA class >II in 46% of the P. Hospital admissions for HF were observed within 30 days in 9 transmissions. Stepwise increase in HFRS was significantly associated with higher risk of HF admission (odds ratio 12.7, CI 3.2–51.5). HFRS had good discrimination for HF events with receiving-operator curve AUC 0.812. Conclusions HFRS was significantly associated with incident HF admissions in a high-risk cohort. Prospective use of this algorithm may help guide HF therapy in CRT recipients. Funding Acknowledgement Type of funding source: None

scholarly journals Predictors of diuresis response to levosimendan administration in patients with acute heart failure

2021 ◽  
Vol 10 (Supplement_1) ◽  
Author(s):  
J Plonka ◽  
J Bugajski ◽  
M Plonka ◽  
A Tycinska ◽  
M Gierlotka
Keyword(s):  
Heart Failure ◽  
High Risk ◽  
Acute Heart Failure ◽  
Clinical Status ◽  
Older Age ◽  
Analysis Model ◽  
Heart Failure Patients ◽  
Positive Effects ◽  
Pulmonary Hemodynamic ◽  
Recent Acute Myocardial Infarction

Abstract Funding Acknowledgements Type of funding sources: None. Levosimendan, a calcium sensitizer and potassium channel-opener, is appreciated  for its effects on systemic and pulmonary hemodynamic and for the relief of symptoms in acute heart failure (AHF). Positive effects of levosimendan on renal function have been also described. The aim of the present analysis was to assess the predictors of the diuresis response to levosimendan administration in high risk acute heart failure patients. Methods. We analysed 34 consecutive patients admitted with high risk AHF to one centre and treated in intensive cardiac care unit. Levosimendan was administered on top of other treatment as a 24-hour infusion of 12.5 mg total dose except for 7 patients (1 patient - terminated earlier due to intolerance, 5 patients – 48h infusion, 1 patient - 72h infusion). Decision of levosimendan administration was based on clinical status and left to attending physician. Diuresis and diuretic dosage before (24 hours) and after levosimendan infusion (48 hours) were taken into account for the present study. Results. The AHF was primary of cardiac origin in all patients. In 6 (18%) it was due to recent acute myocardial infarction. In-hospital mortality was 24%. Median length of hospitalization was 26 days (range 6 to 107 days). Mean age of the patients was 66 ± 12 years, 25 (74%) were men. Mean INTERMACS score was 3.4 ± 1.4 with wet-cold clinical profile present in 13 (38%) of patients. Mean left ventricle ejection fraction (LVEF) was 27 ± 13%, mean NTproBNP was 17176 ± 12464 pg/ml, and mean eGFR 48 ± 22 ml/min/1.73m2. At the time of levosimendan administration patients had background treatment with catecholamines (mean number per patient 1.4 ± 1.1, range 0-3) and with diuretics (mean dosage of furosemide 167 ± 102 mg/24h, range 20-500). 48-hours diuresis after levosimendan administration varies from 950 to 11300 ml (mean 4307 ± 2418 ml). It was significantly lower in patients with cold-wet profile (2646 ± 1335 vs. 5335 ± 2381 ml in other clinical profiles, p = 0.0002). Additionally, 48-hour diuresis was negatively correlated with age (r=-0.46, p = 0.0062) and the number of background catecholamines (r=-0.47, p = 0.0047), and not significantly with the furosemide dosage (r=-0.28, p = 0.10) – figure. No association with diuresis was found for LVEF, NTproBNP, and eGFR. In multiple regression analysis (model R2 = 0.63, p = 0.0085) both older age (p = 0.026) and cold-wet profile (p = 0.0074) were significant predictors of poor diuresis after levosimendan administration. Conclusion. Older age and cold-wet profile were significant predictors of poor diuresis response to levosimendan administration in high risk acute heart failure patients. Although concomitant catecholamines and high diuretic dosage use cloud also be markers of non-responders to levosimendan in terms of diuresis. Abstract Figure

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