Psychosocial stress and quality of life in patients with type 2 cardiorenal syndrome

Bivol, Elena; Grib, L.

doi:10.31688/abmu.2019.54.1.20

Cited by 2 publications

(2 citation statements)

References 16 publications

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“…Although QOL in patients with CRAS was not evaluated, significant alterations in psychological state due to depression, anxiety, and decreased vitality and daily activities were reported in patients with type II CRS compared with patients with HF and no kidney impairment. 64…”

Section: Epidemiology and Clinical Consequences Of Crasmentioning

confidence: 99%

Anemia of cardiorenal syndrome

McCullough

2021

Kidney International Supplements

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Cardiorenal syndrome includes a spectrum of disorders of the kidneys and heart in which loss of function in one organ contributes to reduced function in the other organ. Cardiorenal syndrome is frequently complicated by comorbid anemia, which leads to reciprocal and progressive cardiac and renal deterioration. The triad of heart failure, chronic kidney disease (CKD), and anemia is termed cardiorenal anemia syndrome (CRAS). There are currently no evidence-based recommendations for managing patients with CRAS; however, the treatment of these patients is multifactorial. Not only must the anemia be controlled, but heart failure and kidney injury must be addressed, in addition to other comorbidities. Intravenous iron and erythropoiesis-stimulating agents are the mainstays of treatment for anemia of CKD, addressing both iron and erythropoiesis deficiencies. Since erythropoiesisstimulating agent therapy can be associated with adverse outcomes at higher doses in patients with CKD and is not used in routine practice in patients with heart failure, treatment options for managing anemia in patients with CRAS are limited. Several new therapies, particularly the hypoxia-inducible factor-prolyl hydroxylase inhibitors, are currently under clinical development. The hypoxiainducible factor-prolyl hydroxylase inhibitors have shown promising results for treating anemia of CKD in clinical trials and may confer benefits in patients with CRAS, potentially addressing some of the limitations of erythropoiesis-stimulating agents. Updated clinical practice guidelines for the screening and management of anemia in cardiorenal syndrome, in light of potential new therapies and clinical evidence, would improve the clinical outcomes of patients with this complex syndrome.

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Section: Epidemiology and Clinical Consequences Of Crasmentioning

confidence: 99%

Anemia of cardiorenal syndrome

McCullough

2021

Kidney International Supplements

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“…The interaction of these changeable measures forcefully increases the hazard of HF with negative outcomes. In the UK, around £980 million per year is consumed on the administration of HF and the World Bank assessed that it cost globally $108 billion/per annum 7 . HF is assumed to be an ailment of senior persons.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the Outcome of Pakistani Heart Failure Patients by Various Supervised Machine Learning Methods

Saeed¹,

Faheem²,

Saleem³

et al. 2022

PJMHS

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Aim: To foresee the outcome of heart failure(HF) in Pakistani patients with potential predictors and through various machine learning (ML) methods. Study design:The secondary data of Pakistani patients is taken from the UCI repository in which a cross-sectional, analytical study was planned. Place and duration: This data was collected in April-December, 2015 at the Institute of Cardiology and Allied hospital Faisalabad-Pakistan. Methodology: The data set consisted of299 patients distributed among male (194) and female patients (105). Ages, serum sodium (SS), serum creatinine (SC), gender, smoking, high blood pressure (HBP), ejection fraction (EF), anemia, platelets, Creatinine Phosphokinase (CPK), and diabetes were considered as the potential predictors for predicting the outcome of HF.The data set was analyzed with the help of various machine learning (ML) predictive models including Logistic regression (LR), K-nearest neighbor (KNN), and Decision trees (DT). Results: The ages of the patients were within 60.833±11.894 years. Out of 299 patients, 129 were anemic, 105 had high blood pressure (HBP), and 96 had a smoking history. A statistical model was estimated by applying LR which assisted us in identifying the significant predictors. The sensitivity of the LRwas observed to be 92.1%, whereas 85.6% of the outcome of HF patients was correctly predicted by this model (LR) and DT achieved89.6% prediction accuracy. Conclusion:Since HF is a substantial reason for deaths in Pakistan. Therefore, the identification of its potential risk factors and its accurate prediction by some modern tools are highly demanded. This study applied ML tools for the said task and concluded that among all the fitted ML models, DT predicted the correct outcome for HF patients proficiently. Keywords: Heart failure, machine learning, logistic regression, k-nearest neighbor, decision trees

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Psychosocial stress and quality of life in patients with type 2 cardiorenal syndrome

Cited by 2 publications

References 16 publications

Anemia of cardiorenal syndrome

Anemia of cardiorenal syndrome

Prediction of the Outcome of Pakistani Heart Failure Patients by Various Supervised Machine Learning Methods

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