Evidence map›Paper›PMID 34979949›Full record

ArticleBMC nephrology2022

Thrombocytopenia predicts mortality in Chinese hemodialysis patients- an analysis of the China DOPPS.

Xinju Zhao, Qingyu Niu, Liangying Gan, Fan Fan Hou, Xinling Liang, Zhaohui Ni, Xiaonong Chen, Yuqing Chen, Keith McCullough, Bruce Robinson and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 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

11 authors at 7 institutions in 2 countries.

Xinju Zhao *Department of Nephrology, Peking University People's Hospital, Unit 10C in Ward Building; 11 Xizhimennan Street, Xicheng District, Beijing, 100044, China.
Qingyu Niu *Department of Nephrology, Peking University People's Hospital, Unit 10C in Ward Building; 11 Xizhimennan Street, Xicheng District, Beijing, 100044, China.
Liangying GanDepartment of Nephrology, Peking University People's Hospital, Unit 10C in Ward Building; 11 Xizhimennan Street, Xicheng District, Beijing, 100044, China.
Fan Fan HouDivision of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center of Kidney Disease, State Key Laboratory of Organ Failure Research, 1838 North Guangzhou Avenue, Guangzhou, China.
Xinling LiangDivision of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Zhaohui NiDepartment of Nephrology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Xiaonong ChenDivision of Nephrology, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Yuqing ChenRenal Division, Peking University First Hospital, Beijing, China.
Keith McCulloughArbor Research Collaborative for Health, Ann Arbor, MI, USA.
Bruce RobinsonArbor Research Collaborative for Health, Ann Arbor, MI, USA.
Li ZuoDepartment of Nephrology, Peking University People's Hospital, Unit 10C in Ward Building; 11 Xizhimennan Street, Xicheng District, Beijing, 100044, China. zuoli@bjmu.edu.cn.
Peking University People's Hospital · CNArbor Research Collaborative for Health · USPeking University · CNGuangdong Academy of Medical Sciences · CNNanfang Hospital · CNRenji Hospital · CNRuijin Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHemodialysis (HD) patients have a higher mortality rate compared with general population. Our previous study revealed that platelet counts might be a potential risk factor. The role of platelets in HD patients has rarely been studied. The aim of this study is to examine if there is an association of thrombocytopenia (TP) with elevated risk of all-cause mortality and cardiovascular (CV) death in Chinese HD patients.

methodsData from a prospective cohort study, China Dialysis Outcomes and Practice Patterns Study (DOPPS) 5, were analyzed. Demographic data, comorbidities, platelet counts and other lab data, and death records which extracted from the medical record were analyzed. TP was defined as the platelet count below the lower normal limit (< 100*10

resultsOf 1369 patients, 11.2% (154) had TP at enrollment. The all-cause mortality rates were 26.0% vs. 13.3% (p < 0.001) in patients with and without TP. TP was associated with higher all-cause mortality after adjusted for covariates (HR:1.73,95%CI:1.11,2.71), but was not associated with CV death after fully adjusted (HR:1.71,95%CI:0.88,3.33). Multivariate logistic regression showed that urine output < 200 ml/day, cerebrovascular disease, hepatitis (B or C), and white blood cells were independent impact factors (P < 0.05). Subgroup analysis found that the effect of TP on all-cause mortality was more prominent in patients with diabetes or hypertension, who on dialysis thrice a week, with lower ALB (< 4 g/dl) or higher hemoglobin, and patients without congestive heart failure, cerebrovascular disease, or hepatitis (P < 0.05).

conclusionIn Chinese HD patients, TP is associated with higher risk of all-cause mortality, but not cardiovascular mortality. Platelet counts may be a useful prognostic marker for clinical outcomes among HD patients, though additional study is needed.

Indexed as

Cause of DeathRenal DialysisAgedAsian PeopleCardiovascular DiseasesFemaleHumansKaplan-Meier EstimateKidney Failure, ChronicMaleMiddle AgedPlatelet CountPrognosisProspective StudiesRegression AnalysisThrombocytopeniaCardiovascular deathDOPPSHemodialysisMortalityThrombocytopenia

Identifiers

PMID34979949
PMCPMC8722075
OpenAlexW4206433738

What OpenQuestion holds

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LicenceCC BY
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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.