Evidence map›Paper›PMID 29443733›Full record

ArticleMedicine2018

Serial evaluation of the SOFA score is reliable for predicting mortality in acute severe pancreatitis.

Yu-San Tee, Hsin-Yueh Fang, I-Ming Kuo, Yann-Sheng Lin, Song-Fong Huang, Ming-Chin Yu

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
8.5field-weighted citation impact, top 2% 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

38 citing papers in PubMed, 77 citations in OpenAlex.

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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 at 1 institution in 2 countries.

Yu-San TeeDivision of General Surgery, Department of Surgery, Chang Gung Memorial Hospital, Kweishan, Taoyuan city, Taiwan Department of Surgery, Xiamen Chang Gung Hospital, Xiamen, Fujian, China.
Hsin-Yueh Fang
I-Ming Kuo
Yann-Sheng Lin
Song-Fong Huang
Ming-Chin Yu
Chang Gung Memorial Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute severe pancreatitis caused high mortality, and several scoring systems for predicting mortality are available. We evaluated the effectiveness of serial measurement of several scoring systems in patients with acute severe pancreatitis.We retrospectively obtained serial measurements of Ranson, Acute Physiology and Chronic Health Assessment (APACHE) II, and Sequential Organ Failure Assessment (SOFA) scores of 159 patients with acute severe pancreatitis.The overall mortality rate was 20%, and early mortality (in the first 2 weeks) occurred in 10 (7.4%) patients, while late mortality occurred in 17 (12.6%).All scoring systems were reliable for predicting overall and intensive care unit mortality, while the SOFA score on day 7 presented the largest area under the receiver operator characteristic (ROC) curve (0.858, SE 0.055). Changes in scores over time were evaluated for predicting the progression of organ failure, and the change in SOFA score on hospital day 7 or no interval change in SOFA score was associated with higher mortality rates.APACHE II and SOFA scores are both sensitive for predicting mortality in acute pancreatitis. The serial SOFA scores showed reliable for predicting mortality. Hospital day 7 is a reasonable time for SOFA score reassessment to predict late mortality in acute severe pancreatitis.

Indexed as

APACHEHospital MortalityOrgan Dysfunction ScoresAcute DiseaseAdultAgedFemaleHumansIntensive Care UnitsMaleMiddle AgedPancreatitisPredictive Value of TestsReproducibility of ResultsRetrospective StudiesROC Curve

Identifiers

PMID29443733
PMCPMC5839831
OpenAlexW2794058441

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.