Evidence map›Paper›PMID 38495575›Full record

ReviewJournal of orthopaedics2024

Osteoporosis management-current and future perspectives - A systemic review.

Rajamohanan Jalaja Anish, Aswathy Nair

Open access · greenAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of orthopaedics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
20.5field-weighted citation impact, top 1% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.

  1. Pooled it
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  11. Machine learning is changing osteoporosis detection: an integrative review.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025
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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

2 authors at 1 institution in 1 country.

Rajamohanan Jalaja AnishDepartment of Biochemistry, University of Kerala, Kariyavattom Campus, Trivandrum, 695581, India.
Aswathy NairDepartment of Biochemistry, University of Kerala, Kariyavattom Campus, Trivandrum, 695581, India.
University of Kerala · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Osteoporosis is a geriatric metabolic ailment distinguished by low bone mineral density (BMD) and strength with enhanced micro-architectural retrogression of the extracellular matrix, further increasing bone fragility risk. Osteoporotic fractures and associated complications become common in women and men after 55 and 65 years, respectively. The loss in BMD markedly enhances the risk of fracture, non-skeletal injury, and subsequent pain, adversely affecting the quality of life. Methods: Data summarised in this review were sourced and summarised, including contributions from 2008 to 2023, online from scientific search engines, based on scientific inclusion and exclusion criteria. Results: Biochemical serum markers such as BALP, collagen, osteocalcin, and cathepsin-K levels can reveal the osteoporotic status. DEXA scan techniques evaluate the whole body's BMD and bone mineral content (BMC), crucial in osteoporosis management. Anabolic and anti-osteoporotic agents are commonly used to enhance bone formation, minimize bone resorption, and regulate remodelling. The challenges and side effects of drug therapy can be overcome by combining the various drug moieties. Conclusion: The current review discusses the management protocol for osteoporosis, ranging from lifestyle modification, including physical exercise, pharmaceutical approaches, drug delivery applications, and advanced therapeutic possibilities of AI and machine learning techniques to reduce osteoporosis complications and fracture risk.

Indexed as

Anabolic agentsArtificial intelligenceBisphosphonatesBone mineral densityCalciumOsteoporosis

Identifiers

PMID38495575
PMCPMC10940894
OpenAlexW4392349358

What OpenQuestion holds

Textmetadata
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.