A nomogram based on a patient-reported outcomes measure: predicting the risk of readmission for patients with chronic heart failure

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Abstract

Background

Health-related quality of life, as evaluated by a patient-reported outcomes measure (PROM), is an important prognostic marker in patients with chronic heart failure. This study aimed to use PROM to establish an effective readmission nomogram for chronic heart failure.

Methods

Using a PROM as a measurement tool, we conducted a readmission nomogram for chronic heart failure on a prospective observational study comprising of 454 patients with chronic heart failure hospitalized between May 2017 to January 2020. A Concordance index and calibration curve were used to evaluate the discriminative ability and predictive accuracy of the nomogram. A bootstrap resampling method was used for internal validation of results.

Results

The median follow-up period in the study was 372 days. After a final COX regression analysis, the gender, income, health care, appetite-sleep, anxiety, depression, paranoia, support, and independence were identified and included in the nomogram. The nomogram showed moderate discrimination, with a concordance index of 0.737 (95% CI 0.673–0.800). The calibration curves for the probability of readmission for patients with chronic heart failure showed high consistency between the probability, as predicted, and the actual probability.

Conclusions

This model offers a platform to assess the risk of readmission for different populations with CHF and can assist clinicians with personalized treatment recommendations.

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Most cited references 27

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Type D personality, mental distress, social support and health-related quality of life in coronary artery disease patients with heart failure: a longitudinal observational study

Margarita Staniute, Julija Brozaitiene, Julius Burkauskas … (2015)

Background The relationship between Type D personality and health related quality of life (HRQoL) in coronary artery disease patients is becoming more established, however, the factors that may explain this association remain unclear. The objective of the study was to examine the mediating effects of mental distress and social support on the relationship between the Type D personality and HRQoL in CAD patients with heart failure. Methods A total of 855 CAD patients with heart failure were assessed on Type D personality, mental distress, perceived social support and HRQoL with the following self-administered questionnaires: the Type D personality scale - 14, the Hospital Anxiety and Depression scale, the Multidimensional Scale of Perceived Social Support and the Minnesota Living with Heart Failure Questionnaire. Results The prevalence of Type D personality within the study population was 33.5%. Type D personality, anxiety symptoms, depressive symptoms and social support were all found to be determinants of decreased HRQoL (p’s < 0.001), once age, gender, NYHA functional class and acute myocardial infarction were adjusted for. Anxiety, depressive symptoms and social support were found to mediate the relationship between Type D personality and HRQoL. Type D personality exerted a stable effect on HRQoL over 24 months follow-up period. Conclusions Type D personality has an independent significant effect on the HRQoL in CAD patients with heart failure, and this relation is mediated by anxiety and depressive symptoms, social support.

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Patient reported outcome measures: a model-based classification system for research and clinical practice.

Jordi Alonso, J. Valderas (2008)

The umbrella term Patient Reported Outcomes (PRO) has been successfully proposed for instruments measuring perceived health outcomes, but its relationship to current conceptual models remains to be established. Our aim was to develop a classification system for PRO measures based on a valid conceptual model. We reviewed models and classification schemes of health outcomes and integrated them in a common conceptual framework, based on the models by Wilson and Cleary and the International Classification of Functioning (ICF). We developed a cross-classification system based on the minimum common set of consistent concepts identified in previous classifications, and specified categories based on the WHO International Classifications (ICD-10, and ICF). We exemplified the use of the classification system with selected PRO instruments. We identified three guiding concepts: (1) construct (the measurement object); (2) population (based on age, gender, condition, and culture); and (3) measurement model (dimensionality, metric, and adaptability). The application of the system to selected PRO measures demonstrated the feasibility of its use, and showed that most of them actually assess more than one construct. This classification system of PRO measures, based on a valid integrated conceptual model, should allow the classification of most currently used instruments and may facilitate a more adequate selection and application of these instruments.

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Health status assessment methods for adults: past accomplishments and future challenges.

C McHorney (1998)

Over the past 30 years, health status assessment methods for adults have proliferated. Numerous generic, disease-specific, and preference-based measures now exist that tap diverse aspects of functioning, well-being, symptom states, and subjective perceptions of health. The evolution of the state of the art in adult health status assessment is reviewed. Applications of these tools in health services research, health policy, and clinical practice are discussed. Recommendations are offered for selecting among the armamentaria of tools. Conceptual and methodological challenges that confront instrument users and developers alike are identified and discussed.

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Author and article information

Contributors

Qinghua Han: syhqh@sohu.com

Yanbo Zhang:

ORCID: http://orcid.org/0000-0002-9461-4163

sxmuzyb@126.com

Journal

Journal ID (nlm-ta): Health Qual Life Outcomes

Journal ID (iso-abbrev): Health Qual Life Outcomes

Title: Health and Quality of Life Outcomes

Publisher: BioMed Central (London )

ISSN (Electronic): 1477-7525

Publication date (Electronic): 27 August 2020

Publication date PMC-release: 27 August 2020

Publication date Collection: 2020

Volume: 18

Electronic Location Identifier: 290

Affiliations

[1 ]GRID grid.263452.4, ISNI 0000 0004 1798 4018, Department of Health Statistics, School of Public Health, , Shanxi Medical University, ; 56 South XinJian Road, Taiyuan, 030001 Shanxi Province China

[2 ]Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, 56 South XinJian Road, Taiyuan, 030001 Shanxi Province China

[3 ]GRID grid.263452.4, ISNI 0000 0004 1798 4018, Department of Cardiology, , The 1st Hospital of Shanxi Medical University, ; 85 South Jiefang Road, Taiyuan, 030001 Shanxi Province China

Author information

Yanbo Zhang http://orcid.org/0000-0002-9461-4163

Article

Publisher ID: 1534

DOI: 10.1186/s12955-020-01534-6

PMC ID: 7450976

PubMed ID: 32854729

SO-VID: ee80015b-cd01-4baf-8586-46a26b6a9468

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 1 April 2020

Date accepted : 11 August 2020

Funding

Funded by: the National Nature Science Foundation of China

Award ID: 81872714

Award Recipient : Yanbo Zhang

Funded by: the Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment

Award ID: 201805D111006

Award Recipient : Yanbo Zhang

Funded by: the General Program for Young Scholar of Shanxi Province

Award ID: 201801D221423

Award Recipient : Jing Tian

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ScienceOpen disciplines: Health & Social care

Keywords: patient-reported outcomes measure,chronic heart failure,readmission,nomogram

Data availability:

ScienceOpen disciplines: Health & Social care

Keywords: patient-reported outcomes measure, chronic heart failure, readmission, nomogram

A nomogram based on a patient-reported outcomes measure: predicting the risk of readmission for patients with chronic heart failure

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Abstract

Background

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Conclusions

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Most cited references 27

Type D personality, mental distress, social support and health-related quality of life in coronary artery disease patients with heart failure: a longitudinal observational study

Patient reported outcome measures: a model-based classification system for research and clinical practice.

Health status assessment methods for adults: past accomplishments and future challenges.

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