Evidence map›Paper›PMID 24789551›Full record

ArticleClinical journal of the American Society of Nephrology : CJASN2014

Derivation of urine output thresholds that identify a very high risk of AKI in patients with septic shock.

David D Leedahl, Erin N Frazee, Garrett E Schramm, Ross A Dierkhising, Eric J Bergstralh, Lakhmir S Chawla, Kianoush B Kashani

Abstract read
In one paragraph

Article in Clinical journal of the American Society of Nephrology : CJASN, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Review
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Sepsis-Associated Acute Kidney Injury.Critical care clinics · 2021
    Review
  11. Article
  12. Article
  13. Article
  14. Observational
  15. Observational
  16. Review
  17. Review
  18. A simple score to predict severe leptospirosis.PLoS neglected tropical diseases · 2019
    Article
  19. Article
  20. 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

7 authors.

David D LeedahlPharmacy Services, Sanford Medical Center, Fargo, North Dakota;
Erin N FrazeePharmacy Services, frazee.erin@mayo.edu.
Garrett E SchrammPharmacy Services.
Ross A DierkhisingDivision of Biomedical Statistics and Informatics, and.
Eric J BergstralhDivision of Biomedical Statistics and Informatics, and.
Lakhmir S ChawlaDepartment of Anesthesiology and Critical Care Medicine and Division of Renal Diseases and Hypertension, George Washington University Medical Center, Washington, DC.
Kianoush B KashaniDivision of Nephrology and Hypertension and Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota; and.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesTo promote early detection of AKI, recently proposed pretest probability models combine sub-Kidney Disease Improving Global Outcomes (KDIGO) AKI criteria with baseline AKI risk. The primary objective of this study was to determine sub-KDIGO thresholds that identify patients with septic shock at highest risk for AKI. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This was a retrospective analysis of 390 adult patients admitted to the medical intensive care unit (ICU) of a tertiary, academic medical center with septic shock between January 2008 and December 2010. Hourly urine output was collected from the time of septic shock recognition (hour 0) to hour 96, urine catheter removal, or ICU discharge (whichever occurred first). All available serum creatinine (SCr) measurements were collected until hour 96. The AKI pretest probability model was assessed during the first 12 hours of resuscitation and included the initial episode of oliguria, increase from baseline to peak SCr level, and Acute Physiology and Chronic Health Evaluation (APACHE) III score in a multivariable receiver-operator characteristic (ROC) analysis. The primary outcome was the incidence of stage II or III (stage II+) AKI defined by KDIGO criteria. Secondary outcomes included the need for RRT and 28-day mortality.

resultsNinety-eight (25%) patients developed stage II+ AKI after septic shock recognition. APACHE III score and increase in SCr level in the first 12 hours were not statistically associated with stage II+ AKI in multivariable ROC analysis. Consecutive oliguria for 3 hours had fair predictive ability for achieving stage II+ AKI criteria (area under ROC curve, 0.73; 95% confidence interval [95% CI], 0.68 to 0.78), and oliguria for 5 hours demonstrated optimal accuracy (82%; 95% CI, 79% to 86%).

conclusionsThree to 5 hours of consecutive oliguria in patients with septic shock may provide a valuable measure of AKI risk. Further validation to support this finding is needed.

Indexed as

UrinationUrodynamicsAcademic Medical CentersAcute Kidney InjuryAgedAged, 80 and overAPACHEArea Under CurveBiomarkersCreatinineDistrict of ColumbiaEarly DiagnosisFemaleHumansLogistic ModelsMaleBiomarkersCreatinineAcute kidney injuryclinical alarmsearly diagnosisintensive care unitskidney function testsseptic shock

Identifiers

PMID24789551
PMCPMC4078959

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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.