Evidence map›Paper›PMID 40679174›Full record

ArticleJournal of clinical laboratory analysis2025

The Application of Six Sigma to Assess the Analytical Performance of Plasma Proteins and Design a Risk-Based Statistical Quality Control Strategy: A Multicenter Study.

Ming Hu, Jiaping Wang, Huan Yang, Sugang Zang, Tingting Gao, Jian Zeng, Fumeng Yang

Abstract readMulticenter Study
In one paragraph

Article in Journal of clinical laboratory analysis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Ming HuDepartment of Laboratory Medicine, People's Hospital of Donghai County, Lianyungang, People's Republic of China.ORCID https://orcid.org/0000-0002-2312-4263
Jiaping WangDepartment of Laboratory Medicine, People's Hospital of Donghai County, Lianyungang, People's Republic of China.
Huan YangDepartment of Laboratory Medicine, The Second Affiliated Hospital of Suzhou University, Suzhou, People's Republic of China.ORCID https://orcid.org/0000-0002-3106-490X
Sugang ZangDepartment of Laboratory Medicine, Suqian City People's Hospital, Suqian, People's Republic of China.
Tingting GaoDepartment of Laboratory Medicine, Traditional Chinese Medicine Hospital of Fuxin, Fuxin, People's Republic of China.
Jian ZengDepartment of Laboratory Medicine, Traditional Chinese Medicine Hospital of Lianyungang, Lianyungang, People's Republic of China.
Fumeng YangDepartment of Laboratory Medicine, Affiliated Lianyungang Clinical College of Nantong University, Lianyungang, People's Republic of China.ORCID https://orcid.org/0000-0002-2636-7340

Funding

Kangda College of Nanjing Medical University Research and Development Fund KD2023KYJJ150Lianyungang City Science and Technology Bureau Key Research and Development Project on Social Development SF2322Research Project of Lianyungang Health Commission 202221
6 · The paper itself

Abstract

backgroundThis study applied the six sigma model to evaluate plasma protein testing performance in six laboratories, with customized quality control programs and targeted improvements introduced where necessary.

methodsInternal quality control (IQC) and external quality assessment (EQA) data for plasma proteins were gathered from six laboratories. Sigma values for each analyte were determined based on the coefficient of variation (CV), bias, and total allowable error (TEa). Using six sigma performance verification charts, we calibrated analyte performance and, guided by Westgard sigma rules, batch length, and quality goal index (QGI), developed laboratory-specific quality control schemes and improvement plans.

resultsDespite standardized platforms and reagents, sigma values showed significant inter-laboratory variation, with some differences also observed within labs at varying analyte concentrations. For projects with sigma < 6, tailored quality control measures were implemented, leading to marked performance improvements.

conclusionThe six sigma model provides an objective framework for evaluating plasma protein test performance and enhancing quality. It enables quantitative assessment of laboratory management and supports the development and implementation of customized, risk-based statistical quality control (SQC) strategies and improvement measures across multiple laboratory systems.

Indexed as

Blood ProteinsHumansLaboratoriesLaboratories, ClinicalQuality ControlBlood Proteinsplasma proteinquality controlquality goal indexsix sigma

Identifiers

PMID40679174
PMCPMC12378367

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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.