Evidence map›Paper›PMID 28372593›Full record

Observational studyBMC musculoskeletal disorders2017

Goldman score, but not Detsky or Lee indices, predicts mortality 6 months after hip fracture.

Paula Schmidt Azevedo, David Nicoletti Gumieiro, Bertha Furlan Polegato, Gilberto José Cação Pereira, Igor Almonfrey Silva, Stephan Milhorini Pio, Cacionor Pereira Cunha Junior, Edson Luiz Favero Junior, Sergio Alberto Rupp de Paiva, Marcos Ferreira Minicucci and 1 more

Abstract readComparative StudyObservational Study
In one paragraph

Observational study in BMC musculoskeletal disorders, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. POSSUM and P-POSSUM Scoring in Hip Fracture Mortalities.Geriatric orthopaedic surgery & rehabilitation · 2020
    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

11 authors.

Paula Schmidt AzevedoInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil. paulasa@fmb.unesp.br.
David Nicoletti GumieiroSurgery and Orthopedic Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Botucatu, Brazil.
Bertha Furlan PolegatoInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil.
Gilberto José Cação PereiraSurgery and Orthopedic Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Botucatu, Brazil.
Igor Almonfrey SilvaInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil.
Stephan Milhorini PioInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil.
Cacionor Pereira Cunha JuniorInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil.
Edson Luiz Favero JuniorInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil.
Sergio Alberto Rupp de PaivaInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil.
Marcos Ferreira MinicucciInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil.
Leonardo Antonio Mamede ZornoffInternal Medicine Department, Botucatu Medical School, UNESP - Univ Estadual Paulista, Rubião Júnior s/n, ZipCode: 18618-970, Botucatu, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOver the past years, several cardiac risk indices were evaluated and modified, including Goldman, Detsky, and Lee scores. The predictive capacity of these scores in hip fracture patients is lacking. Thus, our objective was to compare the Goldman, Detsky, and Lee scores as predictors of mortality in 6 months after hip fracture.

methodsWe prospectively evaluated 80 consecutive patients with hip fractures, over the age of 65 admitted to an orthopedic ward at Botucatu Medical School. Patient demographic information, Goldman, Detsky and Lee scores were recorded. All patients were followed for 6 months after hip fracture, and mortality was recorded. Multiple logistic regression analyses were performed for mortality prediction.

resultsThe mortality rate was 23% after a 6-month follow-up period. Patients who died had advanced age and the majority of them were male. They also had lower values of handgrip strength, and higher values of creatinine and urea. In the multiple logistic regression models when adjusted by age, gender, handgrip strength and creatinine, Goldman's score (OR:3.025; 95%CI:1.022-8.953; p:0.046), but not Detsky (OR:2.328; 95%CI:0.422-12.835; p:0.332) and Lee (OR:1.262; 95%CI:0.649-2.454; p:0.494), was associated with mortality 6 months after hip fracture. Each 1 category increase in Goldman score increased the mortality to more than 3-fold.

conclusionsIn conclusion, our data suggest that Goldman score, but not Detsky or Lee indices, predicts mortality associated with hip fracture at up to 6 months post-injury.

Indexed as

Health Status IndicatorsAgedAged, 80 and overBrazilFemaleHip FracturesHumansMaleProspective StudiesCardiovascular scoreHip fractureMortalityPerioperative assessment

Identifiers

PMID28372593
PMCPMC5379496

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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.