An analysis of the relationship between chronic obstructive pulmonary disease, smoking and depression in an integrated healthcare system

Riblet, Natalie; Gottlieb, Daniel J.; Hoyt, Jessica E.; Watts, Bradley V.; Shiner, Brian

doi:10.1016/j.genhosppsych.2020.03.007

“…After discharge, 30 d follow-up was conducted, and the patients were divided into the survival group (SG) and death group (DG) according to their clinical outcomes. The patients in SG were scored with the Beck's Depression Inventory (BDI) [ 14 ], which contained 13 items related to depression, each item was rated on a scale of 0-3 points, and the total score of the inventory was 39 points, with ≥5 points indicating depression. The surviving patients were subdivided into the depressed subjects and nondepressed subjects; the levels of inflammatory factors were compared between SG and DG as well as between depressed and nondepressed subjects, so as to analyze the relationship between the levels of inflammatory factors and depression and prognosis of patients.…”

Section: Methodsmentioning

confidence: 99%

Correlation of Serum IL-18, BDNF, and IL-1β with Depression and Prognosis after Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Zhao

¹

,

Dong

²

2022

Computational and Mathematical Methods in Medicine

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Objective. To explore the correlation of serum IL-18, BDNF, and IL-1β with depression and prognosis after acute exacerbation of chronic obstructive pulmonary disease (COPD). Methods. By means of retrospective analysis, the data of 240 patients at the acute exacerbation of COPD treated in our hospital (February 2018-February 2021) were analyzed. All patients received conventional treatment 1 d after admission, patients’ serological indicators were measured before treatment, and after 30 d of follow-up, the patients were divided into the survival group (SG) and death group (DG) according to their clinical outcomes, the Beck’s Depression Inventory (BDI) scores of the surviving patients were investigated, the correlation of IL-18, BDNF, and IL-1β levels with depression was analyzed by R analytics, and the correlation of IL-18, BDNF, and IL-1β levels with prognosis was analyzed by ROC curve analysis. Results. The results of 30 d follow-up showed that 220 patients survived (91.7%) and 20 patients died (8.3%). Among the surviving patients, 95 patients had depression and 125 patients did not have depression; the BDI scores of the depressed subjects and the nondepressed subjects were 10.35 ± 1.25 points and 2.06 ± 0.76 points, respectively; significant differences in IL-18, BDNF, and IL-1β levels between SG and DG were observed ( P < 0.05 ); significant differences in IL-18, BDNF, and IL-1β levels between the depressed subjects and the nondepressed subjects were observed ( 538.43 ± 19.02 vs. 515.32 ± 9.65 , 7.54 ± 0.56 vs. 12.11 ± 2.41 , and 8.70 ± 0.98 vs. 8.12 ± 0.87 ; P < 0.001 ); among the depressed patients, the IL-18 and IL-1β levels were positively correlative with the BDI scores ( r = 0.781 , r = 0.2583 , P < 0.001 , P = 0.012 ), and the BDNF level was negatively correlative with the BDI scores ( r = − 0.3277 , P = 0.001 ) before treatment; according to the ROC analysis, the AUC (95% CI) of IL-18, BDNF, and IL-1β in predicting prognosis was 0.8770 (0.8281-0.9260), 0.7723 (0.6879-0.8567), and 0.7165 (0.6080-0.8250) ( P < 0.05 ), respectively. Conclusion. In regard to the depression in COPD patients after acute exacerbation, IL18 and IL-1β show positive correlation, and BDNF presents negative correlation. All three indicators have predictive value for patient outcome.

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“…Although these factors do not directly cause vascular disease, they affect the development of depression in other ways. COPD causes hypoxia by destroying the lung capillary bed and causing poor airway ventilation, leading to a decrease in neurotransmitter serotonin activity and eventually depression [ 41 , 42 ]. Hypoxia may also cause the global suppression of cerebral metabolism (energy production), leading to depression [ 43 , 44 ].…”

Section: Discussionmentioning

confidence: 99%

Focal points of preanesthesia evaluations for electroconvulsive therapy in patients with depression: a retrospective analysis of clinical characteristics in nonremission

Zou

¹

,

Li

²

,

Chen

³

et al. 2022

BMC Anesthesiol

0

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Background This study explored the patient clinical characteristics that may affect electroconvulsive therapy (ECT) efficacy to enable improved focus during evaluations and preparation for ECT. Methods Patients were enrolled for ECT at the Department of Psychiatry and Anesthesiology of the First Affiliated Hospital of Chongqing Medical University from December 2017 to January 2019. The primary outcome in our study was defined as the development of nonremission. A multivariate logistic analysis was performed to identify the risk factors for nonremission. Results In total, 874 depressed patients were included in the study. After the ECT treatment, 255 cases (29.2%) exhibited nonremission. A multivariate logistic regression analysis of the variables was performed, and the results showed that atherosclerosis (OR 8.072, 95% CI 2.442 to 16.675; P = 0.001), COPD (OR 2.919, 95% CI 1.240 to 6.871; P = 0.014), diabetes (OR 2.202, 95% CI 1.115 to 4.348; P = 0.023) and smoking (OR 1.519, 95% CI 1.015 to 2.273; P = 0.042) were independent risk factors for nonremission. Conclusion In the retrospective analysis, we found that atherosclerosis, diabetes, COPD and smoking may be high-risk factors for nonremission.

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“…Nicotine dependence may serve as a proxy for smoking and health problems that are linked with chronic hypoxia and risk-taking, which in turn are associated with an increased risk of suicide. 36,37 Furthermore, smoking may be a form of self-medication for emotional distress, which in itself is a risk factor for suicide. 38 Nicotine dependence may represent a potentially transdiagnostic suicide prevention factor because it appeared among the top most important predictors of postdischarge suicide above many psychiatric disorders.…”

Section: Discussionmentioning

confidence: 99%

Using machine learning to predict suicide in the 30 days after discharge from psychiatric hospital in Denmark

Jiang

¹

,

Rosellini

²

,

Horváth‐Puhó

³

et al. 2021

Self Cite

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Background Suicide risk is high in the 30 days after discharge from psychiatric hospital, but knowledge of the profiles of high-risk patients remains limited. Aims To examine sex-specific risk profiles for suicide in the 30 days after discharge from psychiatric hospital, using machine learning and Danish registry data. Method We conducted a case–cohort study capturing all suicide cases occurring in the 30 days after psychiatric hospital discharge in Denmark from 1 January 1995 to 31 December 2015 (n = 1205). The comparison subcohort was a 5% random sample of all persons born or residing in Denmark on 1 January 1995, and who had a first psychiatric hospital admission between 1995 and 2015 (n = 24 559). Predictors included diagnoses, surgeries, prescribed medications and demographic information. The outcome was suicide death recorded in the Danish Cause of Death Registry. Results For men, prescriptions for anxiolytics and drugs used in addictive disorders interacted with other characteristics in the risk profiles (e.g. alcohol-related disorders, hypnotics and sedatives) that led to higher risk of postdischarge suicide. In women, there was interaction between recurrent major depression and other characteristics (e.g. poisoning, low income) that led to increased risk of suicide. Random forests identified important suicide predictors: alcohol-related disorders and nicotine dependence in men and poisoning in women. Conclusions Our findings suggest that accurate prediction of suicide during the high-risk period immediately after psychiatric hospital discharge may require a complex evaluation of multiple factors for men and women.

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An analysis of the relationship between chronic obstructive pulmonary disease, smoking and depression in an integrated healthcare system

Cited by 14 publications

References 53 publications

Correlation of Serum IL-18, BDNF, and IL-1β with Depression and Prognosis after Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Correlation of Serum IL-18, BDNF, and IL-1β with Depression and Prognosis after Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Focal points of preanesthesia evaluations for electroconvulsive therapy in patients with depression: a retrospective analysis of clinical characteristics in nonremission

Using machine learning to predict suicide in the 30 days after discharge from psychiatric hospital in Denmark

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