Evidence map›Paper›PMID 38867251›Full record

ArticleBMC medical informatics and decision making2024

Impact of mobile application and outpatient follow-up on renal endpoints and physiological indices in patients with chronic kidney disease: a retrospective cohort study in Southwest China.

Yu Shi, Shi Pu, Hongmei Peng, Jing Zhang, Yang Li, Xia Huang, Caiping Song, Yu Luo

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Observational
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

8 authors.

Yu Shi *Department of Nephrology, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, P.R. China.ORCID http://orcid.org/0000-0002-2983-5613
Shi Pu *Department of Nephrology, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, P.R. China.
Hongmei PengDepartment of Nephrology, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, P.R. China.
Jing ZhangThinmed Medical Technology (Chongqing) Co.,LTD, Chongqing, 401121, P.R. China.
Yang LiDepartment of Nephrology, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, P.R. China.
Xia HuangDepartment of Nephrology, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, P.R. China.
Caiping SongPresident Office, The Second Affiliated Hospital of Army Medical University (Third Military Medical University), Chongqing, 400037, P.R. China. scp1974@163.com.
Yu LuoSchool of Nursing, Army Medical University, Third Military Medical University, No. 30 Gaotanyan Street, Shapingba District, Chongqing, 400038, P.R. China. luoyuhlgl@tmmu.edu.cn.ORCID http://orcid.org/0000-0002-3566-3766

Funding

Chongqing Municipal Science-Technology Bureau and Health Commission jointly funded the project 2022MSXM026, 2022
6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) is a significant public health concern, and patient self-management is an effective approach to manage the condition. Mobile applications have been used as tools to assist in improving patient self-management, but their effectiveness in long-term outpatient follow-up management of patients with CKD remains to be validated. This study aimed to investigate whether using a mobile application combined with traditional outpatient follow-up can improve health outcomes of patients with CKD .

methodsThis retrospective cohort study recruited CKD patients with stage 1-5 who were not receiving renal replacement therapy from a CKD management center. Two groups were established: the APP + outpatient follow-up group and the traditional outpatient follow-up group. Baseline data was collected from January 2015 to December 2019, followed by a three-year long-term follow-up until December 2022. Laboratory data, all-cause mortality, and renal replacement treatment were then collected and compared between the two groups.

results5326 patients were included in the study, including 2492 in the APP + outpatient group and 2834 in the traditional outpatient group. After IPTW virtualization matching, the final matched the APP + outpatient group consisted of 2489 cases (IQR, 33-55) and 2850 (IQR, 33-55) in the traditional outpatient group. By the end of the study, it was observed that the laboratory data of Phosphorus, Sodium, Triglyceride, Hemoglobin showed significant improvements, Furthermore the APP + outpatient group demonstrated superior results compared to the traditional outpatient group (P < .05). And it was observed that there were 34 deaths (1.4%) in the APP + outpatient group and 46 deaths (1.6%) in the traditional outpatient group(P = .49). After matching for renal replacement therapy outcomes, the two groups were found to be comparable (95% CI [0.72-1.08], P = .23), with no significant difference. However, it was noted that the traditional outpatient group had a lower incidence of using temporary catheters during initial hemodialysis (95% CI [8.4-29.8%], P < .001).

conclusionThe development and application of an app combined with outpatient follow-up management can improve patient health outcomes. However, to ensure optimal preparation for kidney replacement therapy, patients in CKD stages 4-5 may require more frequent traditional outpatient follow-ups, and further develop an information-based decision-making support tool for renal replacement therapy.

Indexed as

Mobile ApplicationsRenal Insufficiency, ChronicAdultAgedChinaFemaleFollow-Up StudiesHumansMaleMiddle AgedOutpatientsRetrospective StudiesTelemedicineChronic kidney diseaseMobile appOutpatient follow-upRemote follow-upRetrospective cohort study

Identifiers

PMID38867251
PMCPMC11167892

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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.