Using text mining to extract depressive symptoms and to validate the diagnosis of major depressive disorder from electronic health records

Wu, Chia-Fang; Kuo, Cheng‐Deng; Su, Chu-Hsien; Wang, Shi‐Heng; Dai, Hong-Jie

doi:10.1016/j.jad.2019.09.044

“…Patients’ demographic data, disease diagnoses, prescriptions on record, and hospitalizations are recorded in the NHIRD. The diagnostic accuracy of psychiatric disorders has been well documented 12 . The database is available for pharmaco‐epidemiologic research 6 and research into specific diseases, including VTE 13‐17 …”

Section: Methodsmentioning

confidence: 99%

“…disorders has been well documented. 12 The database is available for pharmaco-epidemiologic research 6 and research into specific diseases, including VTE. [13][14][15][16][17] This study used the Longitudinal Health Insurance Database from…”

mentioning

confidence: 99%

Real‐world evidence on the use of benzodiazepine receptor agonists and the risk of venous thromboembolism

Chen

¹

,

Winkelman

²

,

Mao

³

et al. 2020

Journal of Thrombosis and Haemostasis

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Venous thromboembolism (VTE) typically presents as deep vein thrombosis of the lower limbs and can result in pulmonary embolism, a potential cause of mortality. 1 Known risk factors for VTE include advancing age, immobilization, cancer, trauma, pregnancy, and estrogen-related medications. 2 The use of benzodiazepine receptor agonist (BZRA) is increasing in many countries, 3,4 with a 1-year prevalence of 5.2% for adults in the United States 5 and 22.2% in Taiwan. 6 BZRAs produce sedative,

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“…Every NHI member older than 40 years is eligible for biennial cardiovascular health panel screening and cancer screening for free or at a minimal cost depending on income [12]. Prior studies have validated the NHIS-NSC data for some chronic diseases, including stroke and dementia [13][14][15][16]]. Yet, the validation of the International Classi cation of Diseases, 10 th revision (ICD-10) codes for depression diagnosis has not been evaluated [17].…”

Section: Participantsmentioning

confidence: 99%

Additive interaction of mid- to late-life depression and cerebrovascular disease on the risk of dementia: A nationwide population-based cohort study

Jang

¹

,

Kang

²

,

Myung

³

et al. 2021

Preprint

0

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Background: Dementia is a progressive neurocognitive disease with a substantial social burden. No apparent breakthroughs in treatment options have emerged so far; thus, disease prevention is essential for at-risk populations. Depression and cerebrovascular disease (CVD) are independent risk factors for dementia, but no studies have examined their interaction effect on dementia risk. This study aimed to identify the association of depression and CVD with the risk of dementia and evaluate whether dementia risk among patients with comorbid depression and CVD is higher than the sum of the individual risk due to each condition.Methods: A population-based cohort study was conducted to analyze the Korean National Health Insurance Service-National Sample Cohort data of all individuals over 50 years of age. Individuals who had not been diagnosed with dementia at baseline were included and followed up from January 1, 2005 to December 31, 2013. A time-varying Cox proportional hazard regression model adjusted for potential confounding factors was used for the analysis. The interaction between depression and CVD was estimated based on attributable proportion (AP), relative excess risk due to interaction (RERI), synergy index (SI), and multiplicative-scale interaction.Results: A total of 242,237 participants were included in the analytical sample, of which 12,735 (5.3%) developed dementia. Compared to that for participants without depression or CVD, the adjusted hazard ratio for the incidence of dementia for those with depression alone was 2.35 (95% confidence interval [CI]: 2.21-2.49), CVD alone was 3.25 (95% CI: 3.11-3.39), and comorbid depression and CVD was 5.02 (95% CI: 4.66-5.42). The additive interaction between depression and CVD was statistically significant (AP: 0.08, 95% CI: 0.01-0.16; RERI: 0.42, 95% CI: 0.03-0.82; SI: 1.12, 95% CI: 1.01-1.24). The multiplicative interaction was significant too, but effect was negative (0.66, 95% CI: 0.60-0.73).Conclusions: In this population-based nationwide cohort with long-term follow-up, depression and CVD were associated with an increased risk of dementia, and their coexistence additively increased dementia risk more than the sum of the individual risks.

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“…Every NHI member older than 40 years is eligible for biennial cardiovascular health panel screening and cancer screening for free or at a minimal cost depending on income [27]. Prior studies have validated the NHIS-NSC data for some chronic diseases, including stroke and dementia [28][29][30][31]. Yet, the validation of the International Classi cation of Diseases, 10 th revision (ICD-10) codes for depression diagnosis has not been evaluated [32].…”

Section: Participantsmentioning

confidence: 99%

Additive interaction of mid- to late-life depression and cerebrovascular disease on the risk of dementia: A nationwide population-based cohort study

Jang

¹

,

Kang

²

,

Myung

³

et al. 2020

Preprint

0

View full text Add to dashboard Cite

Background: Dementia is a progressive neurocognitive disease with a substantial social burden. No apparent breakthroughs in treatment options have emerged so far; thus, disease prevention is essential for at-risk populations. Depression and cerebrovascular disease (CVD) are independent risk factors for dementia, but no studies have examined their interaction effect on dementia risk. This study aimed to identify the association of depression and CVD with the risk of dementia and evaluate whether dementia risk among patients with comorbid depression and CVD is higher than the sum of the individual risk due to each condition.Methods: A population-based cohort study was conducted to analyze the Korean National Health Insurance Service-National Sample Cohort data of all individuals over 50 years of age. Individuals who had not been diagnosed with dementia at baseline were included and followed up from January 1, 2005 to December 31, 2013. A time-varying Cox proportional hazard regression model adjusted for potential confounding factors was used for the analysis. The interaction between depression and CVD was estimated based on attributable proportion (AP), relative excess risk due to interaction (RERI), synergy index (SI), and multiplicative-scale interaction.Results: A total of 242,237 participants were included in the analytical sample, of which 12,735 (5.3%) developed dementia. Compared to that for participants without depression or CVD, the adjusted hazard ratio for the incidence of dementia for those with depression alone was 2.35 (95% confidence interval [CI]: 2.21-2.49), CVD alone was 3.25 (95% CI: 3.11-3.39), and comorbid depression and CVD was 5.02 (95% CI: 4.66-5.42). The additive interaction between depression and CVD was statistically significant (AP: 0.08, 95% CI: 0.01-0.16; RERI: 0.42, 95% CI: 0.03-0.82; SI: 1.12, 95% CI: 1.01-1.24). The multiplicative interaction was significant too, but effect was negative (0.66, 95% CI: 0.60-0.73).Conclusions: In this population-based nationwide cohort with long-term follow-up, depression and CVD were associated with an increased risk of dementia, and their coexistence additively increased dementia risk more than the sum of the individual risks.

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Using text mining to extract depressive symptoms and to validate the diagnosis of major depressive disorder from electronic health records

Cited by 86 publications

References 21 publications

Real‐world evidence on the use of benzodiazepine receptor agonists and the risk of venous thromboembolism

Real‐world evidence on the use of benzodiazepine receptor agonists and the risk of venous thromboembolism

Additive interaction of mid- to late-life depression and cerebrovascular disease on the risk of dementia: A nationwide population-based cohort study

Additive interaction of mid- to late-life depression and cerebrovascular disease on the risk of dementia: A nationwide population-based cohort study

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