Evidence map›Paper›PMID 37881743›Full record

ArticleIndian journal of nephrology

A Simplified Risk Score to Estimate the Risk of Contrast-Induced Nephropathy after Contrast Exposure.

Chaitanya S Kulkarni, Jatin P Kothari, Rashika A Sirsat, Alan F Almeida

Abstract read
In one paragraph

Article in Indian journal of nephrology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

4 authors.

Chaitanya S KulkarniAssistant Professor, Department of Nephrology, Gandhi Medical College and HH, Bhopal, Madhya Pradesh, India.
Jatin P KothariDirector of Nephrology and Chief Consultant-Renal Transplant Medicine, Nanavati Max Superspeciality Hospital, Mumbai, India.
Rashika A SirsatConsultant Nephrologist and Transplant Physician, Department of Nephrology, P D Hinduja National Hospital and MRC Mahim-Mumbai, India.
Alan F AlmeidaConsultant Nephrologist and Transplant Physician, Department of Nephrology, P D Hinduja National Hospital and MRC Mahim-Mumbai, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Scores are available to predict the probability of contrast-induced nephropathy (CIN) after cardiac interventions, but not many scores are available for non-cardiac interventions and there are none for intravenous exposure to contrast. We designed this study to develop a simplified score to determine the probability of developing CIN in patients exposed to the parenteral contrast medium. Methods: This was a prospective study of patients who received parenteral contrast. Of 1300 patients, the first 1000 comprised the derivation cohort and the next 300 comprised the validation cohort. The patient variables in the development cohort were studied using univariate analysis. Statistically significant individual variables were used as independent variables, and CIN was used as the dependent variable in the final multivariate logistic regression model. Then, the risk score was obtained and validated. Results: The incidence of CIN was 3.8%. The risk factors, namely the presence of diabetes mellitus, e-GFR, and route and volume of contrast material were significantly associated with the risk of CIN ( Conclusions: The route and volume of contrast administered, low e-GFR, and diabetes mellitus were the significant risk factors. The developed risk score exhibited very good sensitivity and specificity and excellent accuracy in predicting the probability of CIN.

Indexed as

Contrastdiabetes mellitusnephropathyrisk score

Identifiers

PMID37881743
PMCPMC10593291

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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.