Prognostic Significance of Diastolic Dysfunction With Multiple Comorbidities in Heart Failure Patients

Mann, Baldeep Kaur; Bhandohal, Janpreet; Mushiyev, Savi

doi:10.7759/cureus.8297

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…Binning was done before modelling according to the normal reference ranges and clinically significant cut‐off values, given values from 0‐3 with missing tests given a value of 0. We adopted as cut off values white blood count (WBC) >12 × 10 9 /L, 11 mean corpuscular volume (MCV) ≥100 fL, 12 haemoglobin <12 g/dL, and a cut‐off of <10 g/dL for clinically relevant anaemia, 13 platelet counts <150, and <100 × 10 9 /L was considered clinically significant thromobopenia 14 . We also added platelet counts (10 9 /L) of <300, 300‐399 and 400 or more after finding that it was significantly associated with readmissions both on univariate and multivariate analysis in 2015‐6.…”

Section: Methodsmentioning

confidence: 99%

A simple index predicting 30‐day readmissions in acutely hospitalized patients

Froom

Shimoni

Benbassat

2020

Evaluation Clinical Practice

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Background There are various models attempting to predict 30‐day readmissions of acutely admitted internal medicine patients. However, it is uncertain how to create a parsimonious index that has equivalent predictive ability and can be extrapolated to other settings. Methods We developed a regression equation to predict 30‐day readmissions from all acute hospitalizations in internal medicine departments in a regional hospital in 2015‐2016 and validated the model in 2019. The independent (predictor) variables were age, past hospitalizations, admission laboratory test results, length of stay in hospital and discharge diagnoses. We compared the predictive value of a logistic regression model and index that included discharge diagnoses and admission laboratory test results with one that included only age, past hospitalizations, and hospital length of stay. Results Readmission rates were associated with age, time since last hospitalization, number of previous hospitalizations, and length of stay, as well as with a diagnosis of chronic obstructive lung disease and congestive heart failure and several laboratory data. Logistic regressions of the independent variables for 30‐day readmission rates were similar in 2015‐2016 and 2019. An index was derived from number of previous admissions to hospitals, time since last admission, age, and length of stay. In 2019, for every unit of the index, the odds of readmission increased by 1.33 (95% CI‐ 1.30‐1.37), and ranged from 2.1% to 37.1%. Addition of discharge diagnoses and laboratory variables did not significantly improve the risk differentiation of the index. The c‐statistic for the final parsimonious model was 0.704. Conclusions An index derived from the number of previous hospital admissions, days since last admission, age, and length of stay in days differentiated between the risks of readmission within 30 days without the need for discharge diagnosis and laboratory variables.

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Section: Methodsmentioning

confidence: 99%

A simple index predicting 30‐day readmissions in acutely hospitalized patients

Froom

Shimoni

Benbassat

2020

Evaluation Clinical Practice

View full text Add to dashboard Cite

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“…The variables were binned according to clinically relevant cutoff values: WBC (>12 × 10 9 /L), 17 hemoglobin (<12 g/dL) for females, and (<13 g/dL) for males, and (<10 g/dL) for anemia, 18 platelet counts (<150 × 10 9 /L) and (<100 × 10 9 /L) for clinically significant thrombocytopenia. 19 The remaining CBC parameters were binned according to the best cutoff values that predicted mortality differences in the 2018 exploratory analysis and validated in 2019.…”

Section: Independent Variablesmentioning

confidence: 99%

Parameters of the complete blood count predict in hospital mortality

Shimoni

Froom

Benbassat

2021

Int J Lab Hematology

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Mortality rates are used to evaluate the quality of hospital care after adjusting for disease severity, age, comorbidity, and laboratory data that include complete blood counts (CBC). Previous studies have focused on selected CBC parameters only and have variously found that white blood counts (WBC), [1][2][3][4][5] proportion of neutrophils, 4 red cell counts (RBC), 3,4 red cell distribution widths (RDW), [6][7][8][9][10][11][12][13] mean corpuscular hemoglobin concentrations (MCHC), 1 platelet counts, 1,2,14 mean platelet volumes (MPV), 1,5,6 and neutrophil-lymphocyte ratios (NLR) 3,5,8,15,16 predict short-term mortality. We know of no attempts to identify the predictive value of all CBC parameters, with and without those provided by some modern analyzers, such as the proportion of large unstained cells (LUC), hypochromic cells, and macrocytes. The following study attempts to explore the value of each CBC parameter in predicting

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Prognostic Significance of Diastolic Dysfunction With Multiple Comorbidities in Heart Failure Patients

Cited by 2 publications

References 26 publications

A simple index predicting 30‐day readmissions in acutely hospitalized patients

A simple index predicting 30‐day readmissions in acutely hospitalized patients

Parameters of the complete blood count predict in hospital mortality

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