TY - JOUR
T1 - Prognostic value of a brief loneliness questionnaire for patients with coronary heart disease
T2 - Proposal for a prediction model
AU - Blakoe, Mitti
AU - Christensen, Anne Vinggaard
AU - Palm, Pernille
AU - Højskov, Ida Elisabeth
AU - Thrysoee, Lars
AU - Thorup, Charlotte Brun
AU - Borregaard, Britt
AU - Mols, Rikke Elmose
AU - Rasmussen, Trine Bernholdt
AU - Berg, Selina Kikkenborg
N1 - Publisher Copyright:
© 2021 John Wiley & Sons Ltd
PY - 2022/6
Y1 - 2022/6
N2 - Background: In patients with coronary heart disease (CHD), loneliness is associated with increased risk of morbidity and mortality. No predictive tool is available to detect patients who are influenced by loneliness to a degree that impacts mortality. Aim: To: (i) propose a prediction model that detects patients influenced by loneliness to a degree that increases one-year all-cause mortality, (ii) evaluate model classification performance of the prediction model, and (iii) investigate potential questionnaire response errors. Method: A cohort of patients with CHD (n = 7169) responded to a national cross-sectional survey, including two questions on loneliness. Information on cohabitation and follow-up information on one-year all-cause mortality were obtained from national registers. Prediction model development was based on the prognostic values of item responses in the questionnaire on loneliness and of cohabitation, evaluated with Cox-proportional Hazards Ratio (HR). Item responses which significantly predicted one-year mortality were included in the high-risk loneliness (HiRL) prediction model. Sensitivity, specificity and likelihood ratio were calculated to evaluate model classification performance. Sources of response errors were evaluated using verbal probing technique in an additional cohort (n = 7). The TRIPOD checklist has been used to ensure transparent reporting. Results: Two item responses significantly predicted one-year mortality HR = 2.24 (95%CI = 1.24–4.03) and HR = 2.65 (95%CI = 1.32–5.32) and were thus included in the model. Model classification performance showed a likelihood ratio of 1.89. Response error was evaluated as low. Conclusion: Based on the prognostic value in a loneliness questionnaire, a prediction model suitable to screen patients with CHD for high-risk loneliness was suggested. Relevance to clinical practice: The HiRL prediction model is a short and easy-to-use screening tool that offers clinical staff to identify patients with CHD who are influenced by loneliness to a degree that impacts mortality. However, further evaluation of model performance and questionnaire validation is recommended before integrating the model into clinical practice.
AB - Background: In patients with coronary heart disease (CHD), loneliness is associated with increased risk of morbidity and mortality. No predictive tool is available to detect patients who are influenced by loneliness to a degree that impacts mortality. Aim: To: (i) propose a prediction model that detects patients influenced by loneliness to a degree that increases one-year all-cause mortality, (ii) evaluate model classification performance of the prediction model, and (iii) investigate potential questionnaire response errors. Method: A cohort of patients with CHD (n = 7169) responded to a national cross-sectional survey, including two questions on loneliness. Information on cohabitation and follow-up information on one-year all-cause mortality were obtained from national registers. Prediction model development was based on the prognostic values of item responses in the questionnaire on loneliness and of cohabitation, evaluated with Cox-proportional Hazards Ratio (HR). Item responses which significantly predicted one-year mortality were included in the high-risk loneliness (HiRL) prediction model. Sensitivity, specificity and likelihood ratio were calculated to evaluate model classification performance. Sources of response errors were evaluated using verbal probing technique in an additional cohort (n = 7). The TRIPOD checklist has been used to ensure transparent reporting. Results: Two item responses significantly predicted one-year mortality HR = 2.24 (95%CI = 1.24–4.03) and HR = 2.65 (95%CI = 1.32–5.32) and were thus included in the model. Model classification performance showed a likelihood ratio of 1.89. Response error was evaluated as low. Conclusion: Based on the prognostic value in a loneliness questionnaire, a prediction model suitable to screen patients with CHD for high-risk loneliness was suggested. Relevance to clinical practice: The HiRL prediction model is a short and easy-to-use screening tool that offers clinical staff to identify patients with CHD who are influenced by loneliness to a degree that impacts mortality. However, further evaluation of model performance and questionnaire validation is recommended before integrating the model into clinical practice.
KW - coronary heart disease
KW - loneliness
KW - prognostic research
KW - prognostic tool
KW - screening
KW - social support
UR - http://www.scopus.com/inward/record.url?scp=85114111722&partnerID=8YFLogxK
U2 - 10.1111/jocn.16023
DO - 10.1111/jocn.16023
M3 - Journal article
AN - SCOPUS:85114111722
SN - 0962-1067
VL - 31
SP - 1686
EP - 1696
JO - Journal of Clinical Nursing
JF - Journal of Clinical Nursing
IS - 11-12
ER -