Evidence map›Paper›PMID 33811493›Full record

ArticleOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA2021

Efficiently stratifying mid-term death risk in femoral fractures in the elderly: introducing the ASAgeCoGeCC Score.

C Trevisan, G Gallinari, A Carbone, R Klumpp

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Article in Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

C TrevisanUOC Ortopedia e Traumatologia, Ospedale Bolognini Seriate ASST-Bergamo Est, Via Paderno 21, 24065, Seriate, BG, Italia. carlo.trevisan@tiscali.it.ORCID http://orcid.org/0000-0002-9129-6825
G GallinariUOC Ortopedia e Traumatologia, Ospedale Bolognini Seriate ASST-Bergamo Est, Via Paderno 21, 24065, Seriate, BG, Italia.
A CarboneUOC Ortopedia e Traumatologia, Ospedale Bolognini Seriate ASST-Bergamo Est, Via Paderno 21, 24065, Seriate, BG, Italia.
R KlumppUOC Ortopedia e Traumatologia, Ospedale Bolognini Seriate ASST-Bergamo Est, Via Paderno 21, 24065, Seriate, BG, Italia.
Azienda Ospedaliera Bolognini Seriate · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We evaluated mortality in a cohort of hip fracture patients and implemented a risk prediction score named ASAgeCoGeCC with excellent discrimination. It allowed to separate patients in 3 different risk groups with distinct mortality rates. Recognition of the heterogeneity of patients with femoral fractures may have relevant implications for their management.

introductionUsage of risk prediction models to estimate postoperative mortality risk for hip fracture patients represents a useful tool to give insight in the prognosis and assist in clinical decision-making. The aim of this study was to identify a predictive model able to determine the possible presence of distinct subgroups of hip fracture patients by risk classes in the mid-term.

methodsThree hundred twenty-three hip fracture patients were evaluated, and mortality rates at 30 days, 1, 2, and 4 years were calculated. A multivariate logistic regression analysis using mortality 4 years after fracture as a dependent variable found ASA score, age, cognitive status, gender, and Charlson Comorbidities Index (CCI) as significant risk factors. Using these items, a score named ASAgeCoGeCC was implemented and compared with CCI and Nottingham Hip Fracture Score (NHFS) by a receiver operating characteristic (ROC) curve.

resultsThe area under the ROC curve for ASAgeCoGeCC was always greater than that of CCI and NHFS and ranged between 0.804 and 0.820 suggesting an excellent discrimination. The ASAgeCoGeCC logistic model showed also a good calibration. Patients were divided in 3 groups: a low risk group, an intermediate risk group with an odds ratio for 4-year mortality of 5.6 (95% CI 2.9-10.6), and a high risk group with an odds ratio 21.6 (95% CI 10.6-44).

conclusionThe ASAgeCoGeCC Score is a predictive tool for mortality after hip fracture with good calibration and excellent discrimination properties. It is the first scoring system stratifying hip fracture patients' mortality at 4 years from fracture.

Indexed as

Hip FracturesAgedCohort StudiesHumansLogistic ModelsRisk AssessmentRisk FactorsROC CurveHip fractureMortalityOsteoporosisRisk prediction

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PMID33811493
OpenAlexW3149222552

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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.