Evidence map›Paper›PMID 39610846›Full record

ArticleFrontiers in endocrinology2024

Non-diabetic elderly populations: SIRI as a risk factor and PIV as a protective factor against bone abnormalities.

Manli Yan, Ping Gong, Xiang Li, Haoyue Huang, Hua Wei

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. 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.

Manli Yan *Second Clinical Medical College, Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
Ping Gong *Second Clinical Medical College, Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
Xiang Li *Department of Orthopedic, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Haoyue HuangDepartment of Endocrinology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Hua WeiDepartment of Endocrinology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The prevalence of osteoporosis and its resultant healthcare challenges are escalating, posing significant burdens on public health systems. Studies have introduced immunoinflammatory indices, which are recognized for effectively reflecting the systemic immunoinflammatory status. Despite their potential, the exploration of these indices in the context of osteoporosis remains limited. The study sought to explore the relationship between immune inflammation-related indices and osteoporosis in non-diabetic elderly populations. Methods: The clinical data of 438 non-diabetic elderly subjects were retrospectively analyzed and all statistical analyses were performed using SPSS 27.0. Results: Differences were observed between the osteoporosis group and the normal bone density group in terms of age, neutrophil, lymphocyte, monocyte, hemoglobin, and platelet. A review of prior studies revealed a close association between osteoporosis and chronic inflammation. Immunological indices such as Platelet to Lymphocyte Ratio (PLR), Neutrophil to Lymphocyte Ratio (NLR), Monocyte to Lymphocyte Ratio (MLR), Systemic Immuno-Inflammatory Index (SII), Systemic Inflammatory Response Index (SIRI) and Peripheral Immunity Index (PIV) were calculated. The analysis indicated significant differences in MLR, SII, SIRI and PIV. A multifactorial binary logistic regression model was established, incorporating age, MLR, SII, SIRI, and PIV as variables. The results identified age and SIRI as independent risk factors for bone abnormalities in non-diabetic elderly populations, while PIV served as an independent protective factor. Receiver operating characteristic analysis demonstrated that SIRI and PIV predicted osteoporosis with areas under the curve (AUC) of 0.609 and 0.620, respectively. The diagnostic value was enhanced when combined with age, yielding AUC values of 0.725 for PIV combined with age. PIV combined with age was particularly effective as a biomarker for bone abnormalities in this population. The optimal Youden's index was calculated to be 0.367, corresponding to a sensitivity of 63.8% and a specificity of 72.9%. Conclusions: For non-diabetic elderly populations, SIRI is a risk factor, while PIV serves as a protective factor against bone abnormalities. Combined with previous studies, we suggest that people at high risk of osteoporosis should avoid or minimize the intake of pro-inflammatory dietary patterns. Meanwhile, research from an immune perspective is expected to open new avenues for osteoporosis treatment.

Indexed as

OsteoporosisAgedAged, 80 and overBiomarkersBone DensityFemaleHumansInflammationMaleMiddle AgedProtective FactorsRetrospective StudiesRisk FactorsBiomarkerselderly populationsnon-diabetic populationsosteoporosisPIVSIRI

Identifiers

PMID39610846
PMCPMC11602317

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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.