Evidence map›Paper›PMID 34661665›Full record

ArticleJAMA network open2021

External Validation of a Prediction Model for Acute Kidney Injury Following Noncardiac Surgery.

Masatoshi Nishimoto, Miho Murashima, Maiko Kokubu, Masaru Matsui, Masahiro Eriguchi, Ken-Ichi Samejima, Yasuhiro Akai, Kazuhiko Tsuruya

Abstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
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

8 authors.

Masatoshi NishimotoDepartment of Nephrology, Nara Medical University, Kashihara, Nara, Japan.
Miho MurashimaDepartment of Nephrology, Nara Medical University, Kashihara, Nara, Japan.
Maiko KokubuDepartment of Nephrology, Nara Prefecture General Medical Center, Nara, Nara, Japan.
Masaru MatsuiDepartment of Nephrology, Nara Medical University, Kashihara, Nara, Japan.
Masahiro EriguchiDepartment of Nephrology, Nara Medical University, Kashihara, Nara, Japan.
Ken-Ichi SamejimaDepartment of Nephrology, Nara Medical University, Kashihara, Nara, Japan.
Yasuhiro AkaiDepartment of Nephrology, Nara Medical University, Kashihara, Nara, Japan.
Kazuhiko TsuruyaDepartment of Nephrology, Nara Medical University, Kashihara, Nara, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The Simple Postoperative AKI Risk (SPARK) index is a prediction model for postoperative acute kidney injury (PO-AKI) in patients undergoing noncardiac surgery. External validation has not been performed. Objective: To externally validate the SPARK index. Design, Setting, and Participants: This single-center retrospective cohort study included adults who underwent noncardiac surgery under general anesthesia from 2007 to 2011. Those with obstetric or urological surgery, estimated glomerular filtration rate (eGFR) of less than 15 mL/min/1.73 m2, preoperative dialysis, or an expected surgical duration of less than 1 hour were excluded. The study was conducted at Nara Medical University Hospital. Data analysis was conducted from January to July 2021. Exposures: Risk factors for AKI included in SPARK index. Main Outcomes And Measures: PO-AKI, defined as an increase in serum creatinine of at least 0.3 mg/dL within 48 hours or 150% compared with preoperative baseline value or urine output of less than 0.5 mL/kg/h for at least 6 hours within 1 week after surgery, and critical AKI, defined as either AKI stage 2 or greater and/or any AKI connected to postoperative death or requiring kidney replacement therapy before discharge. The discrimination and calibration of the SPARK index were examined with area under the receiver operating characteristic curves (AUC) and calibration plots, respectively. Results: Among 5135 participants (2410 [46.9%] men), 303 (5.9%) developed PO-AKI, and 137 (2.7%) developed critical AKI. Compared with the SPARK cohort, participants in our cohort were older (median [IQR] age, 56 [44-66] years vs 63 [50-73] years), had lower baseline eGFR (median [IQR], 82.1 [71.4-95.1] mL/min/1.73 m2 vs 78.2 [65.6-92.2] mL/min/1.73 m2), and had a higher prevalence of comorbidities (eg, diabetes: 3956 of 51 041 [7.8%] vs 802 [15.6%]). The incidence of PO-AKI and critical AKI increased as the scores on the SPARK index increased. For example, 10 of 593 participants (1.7%) in SPARK class A, indicating lowest risk, experienced PO-AKI, while 53 of 332 (16.0%) in SPARK class D, indicating highest risk, experienced PO-AKI. However, AUCs for PO-AKI and critical AKI were 0.67 (95% CI, 0.63-0.70) and 0.62 (95% CI, 0.57-0.67), respectively, and the calibration was poor (PO-AKI: y = 0.24x + 3.28; R2 = 0.86; critical AKI: y = 0.20x + 2.08; R2 = 0.51). Older age, diabetes, expected surgical duration, emergency surgery, renin-angiotensin-aldosterone system blockade use, and hyponatremia were not associated with PO-AKI in our cohort, resulting in overestimation of the predicted probability of AKI in our cohort. Conclusions and Relevance: In this study, the incidence of PO-AKI increased as the scores on the SPARK index increased. However, the predicted probability might not be accurate in cohorts with older patients with more comorbidities.

Indexed as

Predictive Value of TestsAcute Kidney InjuryAdultAgedArea Under CurveFemaleHumansIncidenceMaleMiddle AgedPostoperative ComplicationsReproducibility of ResultsRisk AssessmentROC CurveSurgical Procedures, Operative

Identifiers

PMID34661665
PMCPMC8524308

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.