Evidence map›Paper›PMID 29353400›Full record

ArticleJournal of nephrology2018

A STARD-compliant prediction model for diagnosing thrombotic microangiopathies.

Pietro Manuel Ferraro, Gianmarco Lombardi, Alessandro Naticchia, Antonio Sturniolo, Cecilia Zuppi, Valerio De Stefano, Patrizia Bonelli, Ruggero Buonocore, Gianfranco Cervellin, Giuseppe Lippi and 1 more

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In one paragraph

Article in Journal of nephrology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Pietro Manuel FerraroDivisione di Nefrologia, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Via G. Moscati 31, 00168, Rome, Italy. pietromanuel.ferraro@unicatt.it.ORCID http://orcid.org/0000-0002-1379-022X
Gianmarco LombardiDivisione di Nefrologia, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Via G. Moscati 31, 00168, Rome, Italy.
Alessandro NaticchiaDivisione di Nefrologia, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Via G. Moscati 31, 00168, Rome, Italy.
Antonio SturnioloDivisione di Nefrologia, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Via G. Moscati 31, 00168, Rome, Italy.
Cecilia ZuppiDivisione di Biochimica Clinica, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Rome, Italy.
Valerio De StefanoDivisione di Ematologia, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Rome, Italy.
Patrizia BonelliClinical Chemistry and Hematology Laboratory, Parma University Hospital, Parma, Italy.
Ruggero BuonocoreClinical Chemistry and Hematology Laboratory, Parma University Hospital, Parma, Italy.
Gianfranco CervellinA&E Department, Parma University Hospital, Parma, Italy.
Giuseppe LippiClinical Biochemistry Section, University of Verona, Verona, Italy.
Giovanni GambaroDivisione di Nefrologia, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Via G. Moscati 31, 00168, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim of the study was the definition of a predictive model for the initial diagnosis of thrombotic microangiopathies (TMA). We retrospectively collected data on all adult patients admitted to the Gemelli Hospital from 2010 to 2014. ICD-9 codes from primary diagnoses were used for TMA diagnosis. Demographic and laboratory characteristics on admission of patients with TMA were then compared with a random sample of 500 patients with other diagnoses. The prediction model was externally validated in a cohort from another hospital. Overall, 23 of 187,183 patients admitted during the study period received a primary diagnosis of TMA. LDH (OR 1.26, 95% CI 1.05, 1.63) and platelets (OR 0.96, 95% CI 0.94, 0.98) were the only independent predictors of TMA. The AUROC of the final model including only LDH and platelets was 0.96 (95% CI 0.91, 1.00). The Hosmer-Lemeshow (HL) test (p = 0.54) suggested good calibration. Our model also confirmed good discriminatory power (AUROC 0.72 95% CI 0.60, 0.84) and calibration (HL test p = 0.52) in the validation sample. We present a simple prediction model for use in diagnosing TMA in hospitalized patients. The model performs well and can help clinicians to identify patients at high risk of TMA.

Indexed as

AdultAgedAged, 80 and overArea Under CurveCase-Control StudiesFemaleHumansLactate DehydrogenasesLogistic ModelsMaleMiddle AgedPlatelet CountPredictive Value of TestsRetrospective StudiesROC CurveThrombotic MicroangiopathiesLactate DehydrogenasesExternal validationMultivariate analysisPredictive modelThrombotic microangiopathies

Identifiers

PMID29353400

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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.