Evidence map›Paper›PMID 26473916›Full record

ArticleNutrients2015

Association of Body Mass Index and Body Mass Index Change with Mortality in Incident Peritoneal Dialysis Patients.

Liping Xiong, Shirong Cao, Fenghua Xu, Qian Zhou, Li Fan, Qingdong Xu, Xueqing Yu, Haiping Mao

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
1.4field-weighted citation impact, top 20% 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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Advanced wasting in peritoneal dialysis patients.World journal of nephrology · 2017
    Article
  12. Review
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 at 2 institutions in 1 country.

Liping XiongDepartment of Nephrology, The First Affiliated Hospital of Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health of China, Guangdong Provincial Key Laboratory of Nephrology, Guangzhou 510080, China. xiongliping2000@126.com.
Shirong CaoDepartment of Nephrology, The First Affiliated Hospital of Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health of China, Guangdong Provincial Key Laboratory of Nephrology, Guangzhou 510080, China. bcone@163.com.
Fenghua XuEpidemiology Research Unit and Translational Medicine Research Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China. xufenghua0411@126.com.
Qian ZhouEpidemiology Research Unit and Translational Medicine Research Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China. zhouqian2017@163.com.
Li FanDepartment of Nephrology, The First Affiliated Hospital of Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health of China, Guangdong Provincial Key Laboratory of Nephrology, Guangzhou 510080, China. lfan6262@gmail.com.
Qingdong XuDepartment of Nephrology, The First Affiliated Hospital of Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health of China, Guangdong Provincial Key Laboratory of Nephrology, Guangzhou 510080, China. xqd82@163.com.
Xueqing YuDepartment of Nephrology, The First Affiliated Hospital of Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health of China, Guangdong Provincial Key Laboratory of Nephrology, Guangzhou 510080, China. yuxq@mail.sysu.edu.cn.
Haiping MaoDepartment of Nephrology, The First Affiliated Hospital of Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health of China, Guangdong Provincial Key Laboratory of Nephrology, Guangzhou 510080, China. haipingmao@126.com.
Sun Yat-sen University · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although high body mass index (BMI) appears to confer a survival advantage in hemodialysis patients, the association of BMI with mortality in continuous ambulatory peritoneal dialysis (CAPD) patients is uncertain. We enrolled incident CAPD patients and BMI was categorized according to World Health Organization classification for Asian population. BMI at baseline and one year after the initiation of peritoneal dialysis (PD) treatment was assessed to calculate the BMI change (∆BMI). Patients were split into four categories according quartiles of ∆BMI. Kaplan-Meier method and Cox regression proportional hazard analysis were performed to assess the association of BMI on outcomes. A total of 1263 CAPD patients were included, with a mean age of 47.8 ± 15.0 years, a mean BMI of 21.58 ± 3.13 kg/m². During a median follow-up of 25.3 months, obesity was associated with increased risk for cardiovascular diseases (CVD) death (adjusted hazard ratio (AHR) 2.01; 95% CI 1.14, 3.54), but not all-cause mortality. Additionally, patients with more BMI decline (>0.80%) during the first year after CAPD initiation had an elevated risk for both all-cause (AHR: 2.21, 95% CI 1.23-3.95) and CVD mortality (AHR 2.31, 95% CI 1.11, 4.84), which was independent of baseline BMI values.

Indexed as

Body Mass IndexAdultCardiovascular DiseasesChinaDiabetes ComplicationsHumansKaplan-Meier EstimateMiddle AgedObesityPeritoneal Dialysis, Continuous AmbulatoryProportional Hazards ModelsRetrospective Studiesbody mass indexbody mass index changecontinuous ambulatory peritoneal dialysismortality

Identifiers

PMID26473916
PMCPMC4632425
OpenAlexW2121398312

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.