Evidence map›Paper›PMID 41133158›Full record

ArticleFrontiers in medicine2025

Effects of multi-disciplinary team nursing model combined with high-fiber dietary intervention on blood glucose level and nutritional status in elderly type 2 diabetes patients: a prospective clinical trial.

Haiyun Wang, Mengping Yan, Hongyin Wang, Lingbo He, Yingzi Zhang

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Haiyun WangDepartment of General Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Mengping YanDepartment of General Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Hongyin WangDepartment of Emergency, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Lingbo HeDepartment of General Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Yingzi ZhangDepartment of Emergency, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study was a prospective clinical trial, aimed to explore the effects of multi-disciplinary team (MDT) nursing model combined with high-fiber dietary intervention on blood glucose level and nutritional status in elderly diabetes patients. Methods: One hundred and sixty-eight elderly type 2 diabetes patients admitted from April 2020 to April 2023 were allocated into intervention group and control group. Patients in the control group accepted routine nursing + basic nutritional therapy. On the basis of the control group, patients in the intervention group adopted MDT nursing + high-fiber dietary intervention. Both groups received an 8-week intervention. The blood glucose indexes, incidence of complications, quality of life, nutritional status, negative emotions, sleep quality along with patient satisfaction were compared in two groups. Results: After 8 weeks of intervention, when comparing with the control group, the fasting blood glucose, 2 h postprandial blood glucose as well as glycosylated hemoglobin in the intervention group were lower ( Conclusion: MDT model in combination with high-fiber dietary intervention can control blood glucose level, promote nutritional status, decrease the incidence of complications along with promote the quality of life in elderly diabetes patients.

Indexed as

blood glucosediabeteshigh-fiber dietary interventionmulti-disciplinary team nursingnutritional status

Identifiers

PMID41133158
PMCPMC12540376

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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.