Evidence map›Paper›PMID 29628154›Full record

ArticleBrazilian journal of anesthesiology (Elsevier)

[Severity of disease scoring systems and mortality after non-cardiac surgery].

Pedro Videira Reis, Gabriela Sousa, Ana Martins Lopes, Ana Vera Costa, Alice Santos, Fernando José Abelha

Abstract readEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

Article in Brazilian journal of anesthesiology (Elsevier). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Pedro Videira ReisHospital de São João, Serviço de Anestesiologia, Porto, Portugal; Universidade do Porto, Faculdade de Medicina, Porto, Portugal.
Gabriela SousaHospital de São João, Serviço de Anestesiologia, Porto, Portugal.
Ana Martins LopesHospital de São João, Serviço de Anestesiologia, Porto, Portugal.
Ana Vera CostaUniversidade do Porto, Faculdade de Medicina, Porto, Portugal.
Alice SantosHospital de São João, Serviço de Anestesiologia, Porto, Portugal.
Fernando José AbelhaHospital de São João, Serviço de Anestesiologia, Porto, Portugal; Universidade do Porto, Faculdade de Medicina, Porto, Portugal. Electronic address: fernando.abelha@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMortality after surgery is frequent and severity of disease scoring systems are used for prediction. Our aim was to evaluate predictors for mortality after non-cardiac surgery.

methodsAdult patients admitted at our surgical intensive care unit between January 2006 and July 2013 was included. Univariate analysis was carried using Mann-Whitney, Chi-square or Fisher's exact test. Logistic regression was performed to assess independent factors with calculation of odds ratio and 95% confidence interval (95% CI).

results4398 patients were included. Mortality was 1.4% in surgical intensive care unit and 7.4% during hospital stay. Independent predictors of mortality in surgical intensive care unit were APACHE II (OR=1.24); emergent surgery (OR=4.10), serum sodium (OR=1.06) and FiO

conclusionSome factors influenced both surgical intensive care unit and hospital mortality.

Indexed as

APACHE IICirurgia não cardíacaMortalidade após cirurgiaNon‐cardiac surgeryPostoperative mortalitySAPS IISeverity of disease scoring systemsSistemas de classificação da gravidade da doençaSurgical intensive care unitUnidade de terapia intensiva cirúrgica

Identifiers

PMID29628154
PMCPMC9391813

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.