Evidence map›Paper›PMID 38503776›Full record

ArticleScientific reports2024

Development of a predictive model for risk stratification of acute kidney injury in patients undergoing cytoreductive surgery with hyperthermic intraperitoneal chemotherapy.

Martin Krause, Soraya Mehdipour, Jula Veerapong, Joel M Baumgartner, Andrew M Lowy, Rodney A Gabriel

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. 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 at 1 institution in 1 country.

Martin KrauseDivision of Perioperative Informatics, Department of Anesthesiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 80203, USA. makrause@health.ucsd.edu.
Soraya MehdipourDivision of Perioperative Informatics, Department of Anesthesiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 80203, USA.
Jula VeerapongDivision of Surgical Oncology, Department of Surgery, University of California San Diego, San Diego, CA, USA.
Joel M BaumgartnerDivision of Surgical Oncology, Department of Surgery, University of California San Diego, San Diego, CA, USA.
Andrew M LowyDivision of Surgical Oncology, Department of Surgery, University of California San Diego, San Diego, CA, USA.
Rodney A GabrielDivision of Perioperative Informatics, Department of Anesthesiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 80203, USA.
University of California, San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute kidney injury (AKI) following hyperthermic intraperitoneal chemotherapy (HIPEC) is common. Identifying patients at risk could have implications for surgical and anesthetic management. We aimed to develop a predictive model that could predict AKI based on patients' preoperative characteristics and intraperitoneal chemotherapy regimen. We retrospectively gathered data of adult patients undergoing HIPEC at our health system between November 2013 and April 2022. Next, we developed a model predicting postoperative AKI using multivariable logistic regression and calculated the performance of the model (area under the receiver operating characteristics curve [AUC]) via tenfold cross-validation. A total of 412 patients were included, of which 36 (8.7%) developed postoperative AKI. Based on our multivariable logistic regression model, multiple preoperative and intraoperative characteristics were associated with AKI. We included the total intraoperative cisplatin dose, body mass index, male sex, and preoperative hemoglobin level in the final model. The mean area under the receiver operating characteristics curve value was 0.82 (95% confidence interval 0.71-0.93). Our risk model predicted AKI with high accuracy in patients undergoing HIPEC in our institution. The external validity of our model should now be tested in independent and prospective patient cohorts.

Indexed as

Acute Kidney InjuryHyperthermia, InducedAdultCombined Modality TherapyCytoreduction Surgical ProceduresHumansHyperthermic Intraperitoneal ChemotherapyMaleProspective StudiesRetrospective StudiesRisk AssessmentAcute kidney injuryHyperthermic intraperitoneal chemotherapyIntraperitoneal carcinomatosisPredictive model

Identifiers

PMID38503776
PMCPMC10951241
OpenAlexW4392939378

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.