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Screening for Depressive Disorder in Elderly Patients with Chronic Physical Diseases Using the Patient Health Questionnaire-9

OBJECTIVE: We aimed to identify depressive symptom profiles that indicated the presence of depressive disorder and present optimal cut-off sub-scores for depressive symptom profiles for detecting depressive disorder in elderly subjects with chronic physical diseases including diabetes, chronic obstr...

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Detalles Bibliográficos
Autores principales: Park, Seon-Cheol, Lee, Hwa-Young, Lee, Dong-Woo, Hahn, Sang-Woo, Park, Sang-Ho, Kim, Yeo Ju, Choi, Jae Sung, Lee, Ho-Sung, Lee, Soyoung Irene, Na, Kyoung-Sae, Jung, Sung Won, Shim, Se-Hoon, Kim, Ki Won, Paik, Jong-Woo, Kwon, Young-Joon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Neuropsychiatric Association 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5440433/
https://www.ncbi.nlm.nih.gov/pubmed/28539949
http://dx.doi.org/10.4306/pi.2017.14.3.306
Descripción
Sumario:OBJECTIVE: We aimed to identify depressive symptom profiles that indicated the presence of depressive disorder and present optimal cut-off sub-scores for depressive symptom profiles for detecting depressive disorder in elderly subjects with chronic physical diseases including diabetes, chronic obstructive pulmonary disease/asthma, and coronary artery disease, using the Patient Health Questionnaire-9 (PHQ-9). METHODS: Two hundred and thirty-one elderly patients with chronic physical diseases were recruited consecutively from a university-affiliated general hospital in South Korea. RESULTS: Greater severities of all 9 depressive symptoms in the PHQ-9 were presented in those with depressive disorder rather than those without depressive disorder. A binary logistic regression modeling presented that little interest [adjusted odds ratio (aOR)=4.648, p<0.001], reduced/increased sleep (aOR=3.269, p<0.001), psychomotor retardation/agitation (aOR=2.243, p=0.004), and concentration problem (aOR=16.116, p<0.001) were independently associated with increased likelihood of having depressive disorder. Receiver operating characteristics (ROC) curve analysis presented that the optimal cut-off value of score on the items for little interest, reduced/increased sleep, psychomotor retardation/agitation and concentration problem (PHQ-9) for detecting depressive disorder was 4 with 61.9% of sensitivity and 91.5% of specificity [area under curve (AUC)=0.937, p<0.001]. CONCLUSION: Our findings suggested that the diagnostic weighting of little interest, reduced/increased sleep, psychomotor retardation/agitation, and concentration problem is needed to detect depressive disorder among the elderly patients with chronic physical diseases.