Evidence map›Paper›PMID 29771962›Full record

ArticlePloS one2018

Progression of the Radiologic Severity Index predicts mortality in patients with parainfluenza virus-associated lower respiratory infections.

Ajay Sheshadri, Dimpy P Shah, Myrna Godoy, Jeremy J Erasmus, Juhee Song, Liang Li, Scott E Evans, Roy F Chemaly, Burton F Dickey, David E Ost

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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

10 authors.

Ajay SheshadriDepartment of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.ORCID 0000-0002-8091-0180
Dimpy P ShahDepartment of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Myrna GodoyDepartment of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Jeremy J ErasmusDepartment of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Juhee SongDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Liang LiDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Scott E EvansDepartment of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Roy F ChemalyDepartment of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Burton F DickeyDepartment of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
David E OstDepartment of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Inducible epithelial antiviral resistance to prevent asthmaDP2HL123229 · NHLBI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI EVANS, SCOTT E. · 2013 to 2013
$2.4M
PREDICTORS OF RESPONSE TO BRONCHIAL THERMOPLASTY IN SEVERE ASTHMAK23AI117024 · NIAID · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SHESHADRI, AJAY · 2016 to 2020
$823k
NCI NIH HHS P30 CA016672NHLBI NIH HHS DP2 HL123229NIAID NIH HHS K23 AI117024
6 · The paper itself

Abstract

backgroundRadiologic severity may predict adverse outcomes after lower respiratory tract infection (LRI). However, few studies have quantified radiologic severity of LRIs. We sought to evaluate whether a semi-quantitative scoring tool, the Radiologic Severity Index (RSI), predicted mortality after parainfluenza virus (PIV)-associated LRI.

methodsWe conducted a retrospective review of consecutively-enrolled adult patients with hematologic malignancy or hematopoietic stem cell transplantation and with PIV detected in nasal wash who subsequently developed radiologically-confirmed LRI. We measured RSI (range 0-72) in each chest radiograph during the first 30 days after LRI diagnosis. We used extended Cox proportional hazards models to identify factors associated with mortality after onset of LRI with all-cause mortality as our failure event.

resultsAfter adjustment for patient characteristics, each 1-point increase in RSI was associated with an increased hazard of death (HR 1.13, 95% confidence interval [CI] 1.05-1.21, p = 0.0008). Baseline RSI was not predictive of death, but both peak RSI and the change from baseline to peak RSI (delta-RSI) predicted mortality (odds ratio for mortality, peak: 1.11 [95%CI 1.04-1.18], delta-RSI: 1.14 [95%CI 1.06-1.22]). A delta-RSI of ≥19.5 was 89% sensitive and 91% specific in predicting 30-day mortality.

conclusionsWe conclude that the RSI offers precise, informative and reliable assessments of LRI severity. Progression of RSI predicts 30-day mortality after LRI, but baseline RSI does not. Our results were derived from a cohort of patients with PIV-associated LRI, but can be applied in validated in other populations of patients with LRI.

Indexed as

Disease ProgressionHumansRespiratory Tract InfectionsRetrospective StudiesRubulavirus

Identifiers

PMID29771962
PMCPMC5957350

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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.