10
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Association between new-onset Parkinson’s disease and suicide risk in South Korea: a nationwide cohort study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Parkinson’s disease (PD) is an increasingly common neurodegenerative disease in an aging society. Whether PD is associated with an increased suicide risk is unclear. Thus, we investigated the effect of new-onset PD on suicide.

          Methods

          Using the National Health Insurance Service Senior Sample Cohort of South Korea, 17,143 incident PD patients and 17,143 risk set controls, matched by propensity score, were selected for follow-up. The incidence rate of suicide and 95% confidence interval (CI) were calculated based on a generalized linear model of the Poisson distribution. Effect sizes were expressed as hazard ratios (HRs) using the Cox proportional hazards model with a robust variance estimator that incorporated clustering within matched pairs.

          Results

          The incidence rate of suicide was 206.7 cases per 100,000 person-years (95% CI, 172.8–246.9) among the PD cohort. Compared to the matched controls, patients with PD were 2.64 times (HR, 2.64; 95% CI, 1.31–5.30) more likely to commit suicide during the first 180 days of follow-up and 2.47 times (HR, 2.47; 95% CI, 1.42–4.28) within the first 365 days of follow-up. During the entire follow-up period, patients with PD were 2.26 times more likely to commit suicide than were their matched controls (HR, 2.26; 95% CI, 1.67–3.06).

          Conclusion

          Our findings indicated an increased risk of suicide in patients with new-onset PD, regardless of the period after diagnosis. Incorporating mental health care with social and environmental interventions into primary care and PD-specialized care can help reduce suicide risk in people with PD, improving suicide prevention, identification, and risk assessment.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12888-022-03990-4.

          Related collections

          Most cited references41

          • Record: found
          • Abstract: found
          • Article: not found

          An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

          The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects. I describe 4 different propensity score methods: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. I describe balance diagnostics for examining whether the propensity score model has been adequately specified. Furthermore, I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data. I describe different causal average treatment effects and their relationship with propensity score analyses.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

            Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms. ICD-10 coding algorithms were developed by "translation" of the ICD-9-CM codes constituting Deyo's (for Charlson comorbidities) and Elixhauser's coding algorithms and by physicians' assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms. Among 56,585 patients in the ICD-9-CM data and 58,805 patients in the ICD-10 data, frequencies of the 17 Charlson comorbidities and the 30 Elixhauser comorbidities remained generally similar across algorithms. The new ICD-10 and enhanced ICD-9-CM coding algorithms either matched or outperformed the original Deyo and Elixhauser ICD-9-CM coding algorithms in predicting in-hospital mortality. The C-statistic was 0.842 for Deyo's ICD-9-CM coding algorithm, 0.860 for the ICD-10 coding algorithm, and 0.859 for the enhanced ICD-9-CM coding algorithm, 0.868 for the original Elixhauser ICD-9-CM coding algorithm, 0.870 for the ICD-10 coding algorithm and 0.878 for the enhanced ICD-9-CM coding algorithm. These newly developed ICD-10 and ICD-9-CM comorbidity coding algorithms produce similar estimates of comorbidity prevalence in administrative data, and may outperform existing ICD-9-CM coding algorithms.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Cohort Profile: The National Health Insurance Service-National Sample Cohort (NHIS-NSC), South Korea.

                Bookmark

                Author and article information

                Contributors
                sukyong@yuhs.ac
                Journal
                BMC Psychiatry
                BMC Psychiatry
                BMC Psychiatry
                BioMed Central (London )
                1471-244X
                17 May 2022
                17 May 2022
                2022
                : 22
                : 341
                Affiliations
                [1 ]GRID grid.15444.30, ISNI 0000 0004 0470 5454, Department of Public Health, Graduate School, , Yonsei University, ; Seoul, Republic of Korea
                [2 ]GRID grid.15444.30, ISNI 0000 0004 0470 5454, Institute of Health Services Research, Yonsei University, ; Seoul, Republic of Korea
                [3 ]GRID grid.15444.30, ISNI 0000 0004 0470 5454, Department of Preventive Medicine, , Yonsei University College of Medicine, ; Seoul, Republic of Korea
                [4 ]GRID grid.15444.30, ISNI 0000 0004 0470 5454, Department of Healthcare Management, Graduate School of Public Health, , Yonsei University, ; 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722 Republic of Korea
                Article
                3990
                10.1186/s12888-022-03990-4
                9115980
                35581575
                c5931d11-4f2a-482c-839f-ebe959e44d2d
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 28 February 2022
                : 12 May 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Clinical Psychology & Psychiatry
                suicide,risk,parkinson’s disease,psychiatric disorder,depression

                Comments

                Comment on this article