Evidence map›Paper›PMID 24967900›Full record

ArticlePloS one2014

Distribution of serum total protein in elderly Chinese.

Chang-Rong Tian, Li Qian, Xiao-Zhu Shen, Jia-Jing Li, Jiang-Tao Wen

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Biomarkers of ageing of humans and non-human primates.Nature reviews. Molecular cell biology · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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.

Chang-Rong TianDepartment of Geriatrics, The Second People's Hospital of Lianyungang, Xinpu, China.
Li QianDepartment of Microbiology Laboratory, The Second People's Hospital of Lianyungang, Xinpu, China.
Xiao-Zhu ShenDepartment of Geriatrics, The Second People's Hospital of Lianyungang, Xinpu, China.
Jia-Jing LiDepartment of Electronic and Information Engineering Center, The Second People's Hospital of Lianyungang, Xinpu, China.
Jiang-Tao WenDepartment of Clinical Science Experiment Center, The Second People's Hospital of Lianyungang, Xinpu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The serum total protein levels of the elderly possibly decrease gradually with aging. However, serum total protein levels are not suitable as a uniform reference standard for the elderly at different ages and genders. Thus, we investigated the total serum protein distribution in different gender and age groups of 11,453 elderly individuals aged ≥60 years and without liver or renal disease from Lianyungang, Jiangsu, China. The total protein levels (TPL) of these individuals exhibited normal distribution (Z = 1.206, P = 0.109), whereas the reference range (95% CI) was 54.1 g/L to 82.3 g/L. TPL was higher in females than in males for those aged between 60 and 75 years, whereas no significant difference was observed for those aged between 80 and 95 years. TPL was negatively correlated with age in males (r = -0.1342, P<0.05), females (r = -0.304, P<0.05), and the total group (r = -0.2136, P<0.05). TPL also decreased with aging and showed a faster rate in women than in men. These results indicated that an appropriate range of serum total protein based on age and gender differences should be used for clinical applications.

Indexed as

Asian PeopleBlood ProteinsAgedAged, 80 and overAge FactorsAgingChinaFemaleHumansMaleMiddle AgedPopulation SurveillanceReference ValuesSex FactorsBlood Proteins

Identifiers

PMID24967900
PMCPMC4072719

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.