Evidence map›Paper›PMID 31312987›Full record

ArticleClinical rheumatology2019

Predictor of depressive disorders in patients with antineutrophil cytoplasmic antibody-associated vasculitis.

Jan-Di Yun, Junghee Ha, Solah Kim, Hyung Ah Park, Juyoung Yoo, Sung Soo Ahn, Seung Min Jung, Jason Jungsik Song, Yong-Beom Park, Sang-Won Lee

Abstract read
PubMed Publisher
In one paragraph

Article in Clinical rheumatology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jan-Di YunDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Junghee HaDepartment of Psychiatry, Yonsei University College of Medicine, Seoul, Republic of Korea.
Solah KimDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Hyung Ah ParkDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Juyoung YooDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Sung Soo AhnDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Seung Min JungDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Jason Jungsik SongDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Yong-Beom ParkDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Sang-Won LeeDivision of Rheumatology, Department of Internal Medicine, Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. sangwonlee@yuhs.ac.ORCID http://orcid.org/0000-0002-8038-3341

Funding

a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health and Welfare, Republic of Korea HI14C1324Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education 2017R1D1A1B03029050
6 · The paper itself

Abstract

We investigated the frequency of depressive disorders and determined the predictors of depressive disorders in Korean patients with antineutrophil cytoplasmic antibody-associated vasculitis. Sixty-one patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) were enrolled in this study. We assessed the Birmingham vasculitis activity score (BVAS), vasculitis damage index (VDI) and the Korean version of the short form 36-item Health Survey (SF-36). SF-36 consists of the mental component score (MCS) and physical component score (PCS). Depression disorder was identified based on the Korean version of the Center for Epidemiologic Studies Depression Scale-Revised (K-CESD-R) ≥ 16. Mood states including depression were assessed by the Korean edition of the Profile of Mood States (K-POMS) subscales. The mean age was 62.2 years (19 men). Twenty-eight AAV patients (45.9%) had depressive disorders based on K-CESD-R ≥ 16. Both SF-36 MCS and SF-36 PCS were negatively correlated with K-CESD-R (r = - 0.687 and r = - 0.594) and K-POMS depression (r = - 0.604 and r = - 0.480), respectively. The optimal cut-offs of SF-36 MCS and SF-36 PCS for depressive disorders based on K-CESD-R ≥ 16 were obtained as 48.07 and 55.63. Patients with SF-36 MCS ≤ 48.07 exhibited a significantly high RR for depressive disorders, compared with those without (RR 42.667). Also, patients with SF-36 PCS ≤ 55.63 showed a significantly high RR depressive disorder, compared with those without (RR 13.619). We demonstrated that SF-36 could help to estimate the current depressive disorders. We also suggest a method to obtain the optimal cut-offs of SF-36 to predict depressive disorders.Key points• Both SF-36 MCS and SF-36 PCS were negatively correlated with K-CESD-R and K-POMS depression.• Patients with SF-36 MCS ≤ 48.07 exhibited a significantly high relative risk (RR) for depressive disorders, compared with those without (RR 42.667).• Patients with SF-36 PCS ≤ 55.63 showed a significantly high RR depressive disorder, compared with those without (RR 13.619).

Indexed as

AgedAnti-Neutrophil Cytoplasmic Antibody-Associated VasculitisCohort StudiesDepressive DisorderFemaleHumansMaleMiddle AgedPsychometricsSeverity of Illness IndexAntineutrophil cytoplasmic antibody–associated vasculitisDepressionPredictorSF-36

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.