Depression and the risk of hospitalization in type 2 diabetes patients: A nested case-control study accounting for non-persistence to antidiabetic treatment

Tardif, Isabelle; Guénette, Line; Zongo, Arsène; Demers, Éric; Lunghi, Carlotta

doi:10.1016/j.diabet.2022.101334

Cited by 3 publications

(1 citation statement)

References 48 publications

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“…Educators, armed with a thorough understanding of the main components of MHL and depression literacy, can provide more targeted, coherent, and useful education, ultimately leading to transformative changes in the values and mindsets of patients. Depression is also associated with an increased risk of hospitalization (for any reason) in patients with diabetes ( 77 ). Therefore, nurses and practitioners should not neglect to take the mental history of patients with diabetes into account in addition to initial clinical evaluations.…”

Section: Discussionmentioning

confidence: 99%

Depression literacy, mental health literacy, and their relationship with psychological status and quality of life in patients with type 2 diabetes mellitus

Jafari,

Moshki,

Naddafi

et al. 2024

Front. Public Health

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BackgroundThis study was conducted to measure depression literacy (D-Lit) and mental health literacy (MHL) and to investigate their relationship with psychological status and quality of life among Iranian patients with type 2 diabetes mellitus (T2DM).MethodsThis cross-sectional study was conducted in 2021 among 400 patients with T2DM in Iran. Samples were selected using proportional stratified sampling. Data collection tools comprised a demographic questionnaire, measures of MHL and D-Lit, the diabetes quality of life (DQOL) scale, and the DASS-21. After confirming the normality of the data using the Kolmogorov-Smirnov test, parametric statistical tests (such as one-way ANOVA, independent samples t-test, and Chi-Square) were used to investigate the relationship between the variables using SPSS v22 software. The results of continuous quantitative data are reported in the form of means and standard deviations, and qualitative data are reported in the form of absolute and relative frequencies.ResultsIn this study, 10.25% of the participants (n = 41) had severe depression, while 36.75% (n = 147) experienced severe anxiety. The mean (standard deviation) of MHL was 80.92 (9.16) from 130 points. Of the participants, only 1.7% (n = 7) did not answer any questions correctly on the D-lit scale, and only 5.8% (n = 23) were able to answer 15 questions or more correctly on the D-lit. MHL had a significant negative correlation with depression (r = −0.236), anxiety (r = −0.243), and stress (r = −0.155) (P < 0.001). There was a positive and significant correlation between MHL and D-Lit (r = 0.186) (P < 0.001). D-Lit had a significant negative correlation with depression (r = −0.192), anxiety (r = −0.238), and stress (r = −0.156) (P < 0.001). There was a positive and significant correlation between the ability to recognize disorders (r = 0.163), knowledge of self-treatment (r = 0.154), and DQOL (P < 0.001). Depression (r = −0.251), anxiety (r = −0.257), and stress (r = −0.203) had a significant negative correlation with DQOL (P < 0.001).ConclusionMHL and D-Lit levels were found to be inadequate in patients with T2DM. These low levels of MHL and D-Lit among patients with T2DM were associated with higher levels of anxiety, depression, and stress, as well as a lower quality of life. Therefore, designing and implementing preventive programs to improve the mental health of patients with T2DM can help prevent mental disorders and ultimately improve their quality of life.

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Section: Discussionmentioning

confidence: 99%

Depression literacy, mental health literacy, and their relationship with psychological status and quality of life in patients with type 2 diabetes mellitus

Jafari,

Moshki,

Naddafi

et al. 2024

Front. Public Health

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Applying contrastive pre-training for depression and anxiety risk prediction in type 2 diabetes patients based on heterogeneous electronic health records: a primary healthcare case study

Feng,

Wu,

et al. 2023

Journal of the American Medical Informatics Association

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Objective Due to heterogeneity and limited medical data in primary healthcare services (PHS), assessing the psychological risk of type 2 diabetes mellitus (T2DM) patients in PHS is difficult. Using unsupervised contrastive pre-training, we proposed a deep learning framework named depression and anxiety prediction (DAP) to predict depression and anxiety in T2DM patients. Materials and Methods The DAP model consists of two sub-models. Firstly, the pre-trained model of DAP used unlabeled discharge records of 85 085 T2DM patients from the First Affiliated Hospital of Nanjing Medical University for unsupervised contrastive learning on heterogeneous electronic health records (EHRs). Secondly, the fine-tuned model of DAP used case–control cohorts (17 491 patients) selected from 149 596 T2DM patients’ EHRs in the Nanjing Health Information Platform (NHIP). The DAP model was validated in 1028 patients from PHS in NHIP. Evaluation included receiver operating characteristic area under the curve (ROC-AUC) and precision-recall area under the curve (PR-AUC), and decision curve analysis (DCA). Results The pre-training step allowed the DAP model to converge at a faster rate. The fine-tuned DAP model significantly outperformed the baseline models (logistic regression, extreme gradient boosting, and random forest) with ROC-AUC of 0.91±0.028 and PR-AUC of 0.80±0.067 in 10-fold internal validation, and with ROC-AUC of 0.75 ± 0.045 and PR-AUC of 0.47 ± 0.081 in external validation. The DCA indicate the clinical potential of the DAP model. Conclusion The DAP model effectively predicted post-discharge depression and anxiety in T2DM patients from PHS, reducing data fragmentation and limitations. This study highlights the DAP model’s potential for early detection and intervention in depression and anxiety, improving outcomes for diabetes patients.

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Prevalence of comorbid depression and associated factors among hospitalized patients with type 2 diabetes mellitus in Hunan, China

et al. 2023

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Background Depression and diabetes are major health challenges, with heavy economic social burden, and comorbid depression in diabetes could lead to a wide range of poor health outcomes. Although many descriptive studies have highlighted the prevalence of comorbid depression and its associated factors, the situation in Hunan, China, remains unclear. Therefore, this study aimed to identify the prevalence of comorbid depression and associated factors among hospitalized type 2 diabetes mellitus (T2DM) patients in Hunan, China. Methods This cross-sectional study involved 496 patients with T2DM who were referred to the endocrinology inpatient department of Xiangya Hospital affiliated to Central South University, Hunan. Participants’ data on socio-demographic status, lifestyle factors, T2DM-related characteristics, and social support were collected. Depression was evaluated using the Hospital Anxiety and Depression Scale-depression subscale. All statistical analyses were conducted using the R software version 4.2.1. Results The prevalence of comorbid depression among hospitalized T2DM patients in Hunan was 27.22% (95% Confidence Interval [CI]: 23.3–31.1%). Individuals with depression differed significantly from those without depression in age, educational level, per capita monthly household income, current work status, current smoking status, current drinking status, regular physical activity, duration of diabetes, hypertension, chronic kidney disease, stroke, fatty liver, diabetic nephropathy, diabetic retinopathy, insulin use, HbA1c, and social support. A multivariable logistic regression model showed that insulin users (adjusted OR = 1.86, 95% CI: 1.02–3.42) had a higher risk of depression, while those with regular physical activity (adjusted OR = 0.48, 95% CI: 0.30–0.77) or greater social support (adjusted OR = 0.20, 95% CI: 0.11–0.34) had a lower risk of depression. The area under the curve of the receiver operator characteristic based on this model was 0.741 with a sensitivity of 0.785 and specificity of 0.615. Conclusions Depression was moderately prevalent among hospitalized T2DM patients in Hunan, China. Insulin treatment strategies, regular physical activity, and social support were significantly independently associated with depression, and the multivariable model based on these three factors demonstrated good predictivity, which could be applied in clinical practice.

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Depression and the risk of hospitalization in type 2 diabetes patients: A nested case-control study accounting for non-persistence to antidiabetic treatment

Cited by 3 publications

References 48 publications

Depression literacy, mental health literacy, and their relationship with psychological status and quality of life in patients with type 2 diabetes mellitus

Depression literacy, mental health literacy, and their relationship with psychological status and quality of life in patients with type 2 diabetes mellitus

Applying contrastive pre-training for depression and anxiety risk prediction in type 2 diabetes patients based on heterogeneous electronic health records: a primary healthcare case study

Prevalence of comorbid depression and associated factors among hospitalized patients with type 2 diabetes mellitus in Hunan, China

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