Evidence mapPaperPMID 39170832Full record

ArticlePatient preference and adherence2024

Developing and Validating a Nomogram for Non-Adherence to Inhaler Therapy Among Elderly Chronic Obstructive Pulmonary Disease Patients Based on the Social Ecological Model.

You-Ran Liu, Yan Wang, Juan Chen, Shan Luo, Xiaomei Ji, Huadong Wang, Li Zhang

Abstract read
In one paragraph

Article in Patient preference and adherence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

You-Ran Liu *School of Nursing, Bengbu Medical University, Bengbu, People's Republic of China.ORCID 0009-0008-4537-3923
Yan Wang *Department of Nursing, Tangshan Vocational & Technical College, Tangshan, People's Republic of China.
Juan ChenDepartment of Acupuncture and Rehabilitation, Hangzhou Hospital of Traditional Chinese Medicine, Hangzhou, People's Republic of China.
Shan LuoDepartment of Nursing, Tangshan Vocational & Technical College, Tangshan, People's Republic of China.
Xiaomei JiSchool of Nursing, Bengbu Medical University, Bengbu, People's Republic of China.
Huadong WangDepartment of Respiratory medicine, The First Affiliated Hospital of Bengbu Medical University, Bengbu, People's Republic of China.
Li ZhangSchool of Nursing, Bengbu Medical University, Bengbu, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to identify the risk predictors of non-adherence to inhaler therapy and construct a nomogram prediction model for use in Chinese elderly patients with chronic obstructive pulmonary disease (COPD). Patients and Methods: A cross-sectional study was conducted with 305 participants recruited from a tertiary care hospital in Anhui, China. Adherence was analyzed using the Test of Adherence to Inhalers. Potential predictive factors were incorporated based on the social ecological model, and data were collected through a questionnaire method. R version 4.3.3 was utilized to perform the least absolute shrinkage and selection operator regression model and multivariable logistic regression analysis to identify risk factors and establish a nomogram prediction model. Results: The results of the multivariable analysis revealed that medication beliefs, illness perception, the COPD Assessment Test score, smoking status, and education level were significant risk factors for non-adherence to inhaler therapy in elderly COPD patients (all P < 0.05). The nomogram prediction model for non-adherence to inhaler therapy in elderly COPD patients demonstrated a good discriminative ability, with an area under the receiver operating characteristic curve of 0.912. The C-index was 0.922 (95% CI: 0.879 to 0.965), and the Brier value was 0.070, indicating good consistency and calibration. Decision curve analysis indicated that the use of the nomogram would be more beneficial in clinical practice when the threshold probability of non-adherence exceeds 17%. Conclusion: This study identified predictive factors regarding non-adherence among elderly patients with COPD and constructed a predictive nomogram. By utilizing the nomogram model healthcare professionals could swiftly calculate and comprehend the non-compliance level of COPD patients, thus guiding the development of personalized interventions in clinical practice.

Indexed as

chronic obstructive pulmonary diseaseinhaler therapynomogramnon-adherencesocial ecological model

Identifiers

PMID39170832
PMCPMC11338172

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.