Evidence map›Paper›PMID 32300902›Full record

ArticleAnnals of intensive care2020

SEA-MAKE score as a tool for predicting major adverse kidney events in critically ill patients with acute kidney injury: results from the SEA-AKI study.

Theerapon Sukmark, Nuttha Lumlertgul, Kearkiat Praditpornsilpa, Kriang Tungsanga, Somchai Eiam-Ong, Nattachai Srisawat

Abstract read
In one paragraph

Article in Annals of intensive care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

6 authors.

Theerapon SukmarkThungsong Hospital, Nakhon Si Thammarat, Thailand.
Nuttha LumlertgulDivision of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, and King Chulalongkorn Memorial Hospital, Bangkok, 10330, Thailand.
Kearkiat PraditpornsilpaDivision of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, and King Chulalongkorn Memorial Hospital, Bangkok, 10330, Thailand.
Kriang TungsangaDivision of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, and King Chulalongkorn Memorial Hospital, Bangkok, 10330, Thailand.
Somchai Eiam-OngDivision of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, and King Chulalongkorn Memorial Hospital, Bangkok, 10330, Thailand.
Nattachai SrisawatDivision of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, and King Chulalongkorn Memorial Hospital, Bangkok, 10330, Thailand. drnattachai@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute kidney injury (AKI) is a common problem in critically ill patients and associated with high rates of morbidity and mortality. Recently, Major Adverse Kidney Events (MAKE) were introduced as important kidney endpoints. If these endpoints can be predicted, then it may help the physicians to identify high-risk patients and provide the opportunity to have targeted preventive therapy. The objective of this study was to create a simplified scoring system to predict MAKE within 28 days among AKI patients in ICU.

methodsThis is a prospective web-based multicenter cohort study that was conducted in adults who were admitted to the ICU in 17 centers across Thailand from 2013 to 2015. A predicting score was derived from the regression equation with Receiver Operating Characteristic (ROC) analysis to evaluate the diagnostic test and produce predictive models. Internal validation was obtained using the bootstrapping method.

resultsFrom 5071 cases, 2856 (56%) had AKI. Among those with AKI, 1749 (61%) had MAKE. Among those that have MAKE, there were 1175 (41.4%) deaths, 414 (14.4%) were on dialysis and 1154 (40.7%) had non-recovery renal function. The simplified score points of low Glasgow coma scale was 3, tachypnea was 1, vasopressor use was 1, on mechanical ventilation was 2, oliguria was 2, serum creatinine rising ≥ 3 times was 5, high blood urea nitrogen was 3, low hematocrit was 2, and thrombocytopenia was 1. The area under ROC curve for optimism corrected performance was 0.80 (0.78, 0.81). When the cut-off value was 7, the sensitivity, specificity, positive likelihood ratio, and positive predictive values were 0.75, 0.76, 3.10, and 0.84, respectively. When the scoring system was calibrated, the α intercept and β slope were 1.001 and 0, respectively.

conclusionsSEA-MAKE scoring system is a new simplified clinical tool that can be used to predict major adverse kidney events in AKI patients. The simplicity of the scoring system is highly likely to be used in resource-limited settings. However, external validation is necessary before widespread use.

Indexed as

Acute kidney injury (AKI)Clinical Predictive ScoreMajor adverse kidney events (MAKE)

Identifiers

PMID32300902
PMCPMC7162998

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.