Evidence map›Paper›PMID 38658648›Full record

ArticleScientific reports2024

Mobile monitoring system detects the disease activity pattern and shows the association with clinical outcomes in patients with newly diagnosed Crohn's disease.

Yoo Jin Lee, Sang Gyu Kwak, Eun Soo Kim, Sung Kook Kim, Hyun Seok Lee, Yun Jin Chung, Byung Ik Jang, Kyeong Ok Kim, Jeongseok Kim, Hyeong Ho Jo and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 5 institutions in 1 country.

Yoo Jin Lee *Department of Internal Medicine, Keimyung University School of Medicine, Daegu, South Korea.
Sang Gyu Kwak *Department of Medical Statistics, Catholic University of Daegu School of Medicine, Daegu, South Korea.
Eun Soo KimDepartment of Internal Medicine, School of Medicine, Kyungpook National University, 130 Dongdeuk-ro, Jung-gu, Daegu, South Korea. dandy813@knu.ac.kr.
Sung Kook KimDepartment of Internal Medicine, School of Medicine, Kyungpook National University, 130 Dongdeuk-ro, Jung-gu, Daegu, South Korea.
Hyun Seok LeeDepartment of Internal Medicine, School of Medicine, Kyungpook National University, 130 Dongdeuk-ro, Jung-gu, Daegu, South Korea.
Yun Jin ChungDepartment of Internal Medicine, School of Medicine, Kyungpook National University, 130 Dongdeuk-ro, Jung-gu, Daegu, South Korea.
Byung Ik JangDepartment of Internal Medicine, Yeungnam University College of Medicine, 317‑1 Daemyung 5 Dong, Daegu, 705-703, South Korea. jbi@med.yu.ac.kr.
Kyeong Ok KimDepartment of Internal Medicine, Yeungnam University College of Medicine, 317‑1 Daemyung 5 Dong, Daegu, 705-703, South Korea.
Jeongseok KimDepartment of Internal Medicine, Keimyung University School of Medicine, Daegu, South Korea.
Hyeong Ho JoDepartment of Internal Medicine, Catholic University of Daegu School of Medicine, Daegu, South Korea.
Eun Young KimDepartment of Internal Medicine, Catholic University of Daegu School of Medicine, Daegu, South Korea.
Kyungpook National University · KRDaegu Catholic University · KRKeimyung University · KRYeungnam University · KRYeungnam University Medical Center · KR

Funding

National Research Foundation of Korea 2021R1A5A2021614
6 · The paper itself

Abstract

We aimed to determine whether Crohn's disease (CD) activity patterns assessed via a web-based symptom diary can help predict clinical outcomes in patients with newly diagnosed CD. Patients diagnosed with CD within the preceding 3 months were prospectively enrolled at four tertiary centers. All patients recorded their symptoms on a website using a smartphone at least once a week. The index outcomes were disease-related admission and surgery during follow-up. The disease activity from enrollment to outcome or last follow-up was reviewed for pattern analysis. Cox regression analysis was used to identify the predictors of disease outcomes. A total of 102 patients were enrolled. During a median follow-up period of 42 months, 25 (24.5%) and 6 (5.9%) patients required admission and surgery, respectively. Poor activity pattern was an independent predictor of disease-related hospitalization (adjusted hazard ratio [aHR], 3.96; 95% confidence interval [CI] 1.5-10.45; p = 0.005). A poor activity pattern (aHR, 19.48; 95% CI 1.86-203.95; p = 0.013) and female sex (aHR, 11.28; 95% CI 1.49-85.01; p = 0.018) were found to be independent predictors of bowel resection. CD disease activity patterns monitored through the mobile monitoring system may help predict clinical outcomes, such as disease-related hospitalization and surgery, in patients with newly diagnosed CD.

Indexed as

Crohn DiseaseAdolescentAdultFemaleFollow-Up StudiesHospitalizationHumansMaleMiddle AgedMobile ApplicationsProspective StudiesSmartphoneTelemedicineYoung Adult

Identifiers

PMID38658648
PMCPMC11043071
OpenAlexW4395076948

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.