Evidence map›Paper›PMID 35559352›Full record

ArticleFrontiers in medicine2022

Development and Validation of a Prediction Model for the Cure of Peritoneal Dialysis-Associated Peritonitis: A Multicenter Observational Study.

Lingfei Meng, Liming Yang, Xueyan Zhu, Xiaoxuan Zhang, Xinyang Li, Siyu Cheng, Shizheng Guo, Xiaohua Zhuang, Hongbin Zou, Wenpeng Cui

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Lingfei MengDepartment of Nephrology, The Second Hospital of Jilin University, Changchun, China.
Liming YangDepartment of Nephrology, The First Hospital of Jilin University-The Eastern Division, Changchun, China.
Xueyan ZhuDepartment of Nephrology, Jilin Central Hospital, Jilin, China.
Xiaoxuan ZhangDepartment of Nephrology, Jilin FAW General Hospital, Changchun, China.
Xinyang LiDepartment of Nephrology, The Second Hospital of Jilin University, Changchun, China.
Siyu ChengDepartment of Nephrology, The Second Hospital of Jilin University, Changchun, China.
Shizheng GuoDepartment of Nephrology, The Second Hospital of Jilin University, Changchun, China.
Xiaohua ZhuangDepartment of Nephrology, The Second Hospital of Jilin University, Changchun, China.
Hongbin ZouDepartment of Nephrology, The Second Hospital of Jilin University, Changchun, China.
Wenpeng CuiDepartment of Nephrology, The Second Hospital of Jilin University, Changchun, China.
Second Affiliated Hospital of Jilin University · CNJilin City Central Hospital · CNJilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Peritoneal dialysis (PD)-associated peritonitis (PDAP) is a severe complication of PD. It is an important issue about whether it can be cured. At present, there is no available prediction model for peritonitis cure. Therefore, this study aimed to develop and validate a prediction model for peritonitis cure in patients with PDAP. Methods: Patients with PD who developed PDAP from four dialysis centers in Northeast China were followed up. According to the region of PD, data were divided into training and validation datasets. Initially, a nomogram for peritonitis cure was established based on the training dataset. Later, the nomogram performance was assessed by discrimination (C-statistic), calibration, and decision curves. Results: Totally, 1,011 episodes of peritonitis were included in the final analysis containing 765 in the training dataset and 246 in the validation dataset. During the follow-up period, peritonitis cure was reported in 615 cases from the training dataset and 198 from the validation dataset. Predictors incorporated in the final nomogram included PD duration, serum albumin, antibiotics prior to admission, white cell count in peritoneal dialysate on day 5 (/μl) ≥ 100/μl, and type of causative organisms. The C-statistic values were 0.756 (95% CI: 0.713-0.799) in the training dataset and 0.756 (95% CI: 0.681-0.831) in the validation dataset. The nomogram exhibited favorable performance in terms of calibration in both the training and validation datasets. Conclusion: This study develops a practical and convenient nomogram for the prediction of peritonitis cure in patients with PDAP, which assists in clinical decision-making.

Indexed as

clinical decision rulesESRD – end stage renal diseasenomogramperitoneal dialysisperitoneal dialysis-associated peritonitis

Identifiers

PMID35559352
PMCPMC9086557
OpenAlexW4224930760

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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.