Evidence map›Paper›PMID 35509052›Full record

ArticleJournal of occupational medicine and toxicology (London, England)2022

Forecasting the rate of hand injuries in Singapore.

Liau Zi Qiang Glen, Joel Yat Seng Wong, Wei Xuan Tay, Jiayi Weng, Gregory Cox, Andre Eu Jin Cheah

Abstract read
In one paragraph

Article in Journal of occupational medicine and toxicology (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Liau Zi Qiang GlenDepartment of Orthopaedic Surgery, National University Health System, Singapore, Singapore. glen_liau@nuhs.edu.sg.ORCID http://orcid.org/0000-0002-0498-9237
Joel Yat Seng WongUniversity Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, 5 Lower Kent Ridge Rd, Main Building 1, Level 2, Singapore, 119074, Singapore.
Wei Xuan TayUniversity Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, 5 Lower Kent Ridge Rd, Main Building 1, Level 2, Singapore, 119074, Singapore.
Jiayi WengUniversity Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, 5 Lower Kent Ridge Rd, Main Building 1, Level 2, Singapore, 119074, Singapore.
Gregory CoxDepartment of Economics, National University of Singapore, 1 Arts Link, Singapore, 117568, Singapore.
Andre Eu Jin CheahUniversity Orthopaedic, Hand and Reconstructive Microsurgery Cluster, National University Health System, 5 Lower Kent Ridge Rd, Main Building 1, Level 2, Singapore, 119074, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aims to analyse the correlation between the incidence rate of hand injuries and various major economic indicators in Singapore. We hypothesise that the number of hand injuries is correlated to activity in the construction and manufacturing industries in Singapore.

methodsTwenty thousand seven hundred sixty-four patients who underwent hand surgeries in a tertiary institution between 2012 to 2018 were reviewed. Two independent, blinded observers extracted the frequency of hand surgeries performed from Electronic Medical Records. Economic indicators pertinent to Singapore's economic activity were collected and smoothed by simple moving average of the prior 3 months. Results were analysed using IBM SPSS v25.0.

resultsSignificant independent univariate variables were Purchasing-Manager-Index and Industrial-Production-Index. Multiple linear regression of quarterly reported figures showed that Total-Livestock-Slaughtered, Total-Seafood-Handled, Purchasing-Manger-Index, Industrial-Production-Index, Gas-Tariffs, Construction-Index, Consumer-Price-Index, Total-Air-Cargo-Handled, Total-Container-Throughput, Total-Road-Traffic-Accident-Casualties, Food-&-Beverage-Services-Index were significantly correlated (p < 0.05) with hand injuries, with R

conclusionQuarterly economic indicators from major economic industries can be used to predict the incidence of hand injuries with a 62.3% correlation. These findings may be useful for anticipating healthcare resource allocation to treat hand injuries. TYPE OF STUDY AND LEVEL OF EVIDENCE: Economic and decision, Level II.

Indexed as

DemandHealthLabourSupply

Identifiers

PMID35509052
PMCPMC9066836

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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.