Evidence map›Paper›PMID 38005908›Full record

ArticleViruses2023

The Validity of the ROX Index and APACHE II in Predicting Early, Late, and Non-Responses to Non-Invasive Ventilation in Patients with COVID-19 in a Low-Resource Setting.

Sumalatha Arunachala, Ashwaghosha Parthasarathi, Chetak Kadabasal Basavaraj, Mohammed Kaleem Ullah, Shreya Chandran, Hariharan Venkataraman, Prashant Vishwanath, Koustav Ganguly, Swapna Upadhyay, Padukudru Anand Mahesh

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Observational
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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 at 3 institutions in 3 countries.

Sumalatha ArunachalaDepartment of Respiratory Medicine, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru 570015, India.ORCID 0000-0001-5858-8298
Ashwaghosha ParthasarathiAllergy, Asthma, and Chest Centre, Krishnamurthypuram, Mysuru 570004, India.ORCID 0000-0002-7270-0247
Chetak Kadabasal BasavarajDepartment of Respiratory Medicine, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru 570015, India.ORCID 0000-0002-7422-8353
Mohammed Kaleem UllahCentre for Excellence in Molecular Biology and Regenerative Medicine (A DST-FIST Supported Center), Department of Biochemistry (A DST-FIST Supported Department), JSS Medical College, JSS Academy of Higher Education and Research, Mysore 570015, India.ORCID 0000-0001-8470-3114
Shreya ChandranDepartment of Respiratory Medicine, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru 570015, India.
Hariharan VenkataramanDepartment of Respiratory Medicine, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru 570015, India.
Prashant VishwanathCentre for Excellence in Molecular Biology and Regenerative Medicine (A DST-FIST Supported Center), Department of Biochemistry (A DST-FIST Supported Department), JSS Medical College, JSS Academy of Higher Education and Research, Mysore 570015, India.
Koustav GangulyUnit of Integrative Toxicology, Institute of Environmental Medicine (IMM), Karolinska Institutet, 17177 Stockholm, Sweden.ORCID 0000-0001-8531-8154
Swapna UpadhyayUnit of Integrative Toxicology, Institute of Environmental Medicine (IMM), Karolinska Institutet, 17177 Stockholm, Sweden.ORCID 0000-0003-4699-4082
Padukudru Anand MaheshDepartment of Respiratory Medicine, JSS Medical College, JSS Academy of Higher Education and Research, Mysuru 570015, India.ORCID 0000-0003-1632-5945
JSS Academy of Higher Education and Research · INKarolinska Institutet · SERutgers, The State University of New Jersey · US

Funding

Research Training at the Confluence of Infectious and Non-Communicable Diseases in IndiaD43TW010332 · FIC · UNIVERSITY OF CALIFORNIA BERKELEY · PI COX, JEFFERY S · 2017 to 2022
$836k
FIC NIH HHS D43 TW010332NIH HHS National Institutes of Health (NIH), Fogarty International Center, Global Infectious Disease Re-search Training program (GID) [Grant D43TW010332-01A1 to PAM]
6 · The paper itself

Abstract

The use of the Ratio of Oxygen Saturation (ROX) index to predict the success of high-flow nasal oxygenation (HFNO) is well established. The ROX can also predict the need for intubation, mortality, and is easier to calculate compared with APACHE II. In this prospective study, the primary aim is to compare the ROX (easily administered in resource limited setting) to APACHE II for clinically relevant outcomes such as mortality and the need for intubation. Our secondary aim was to identify thresholds for the ROX index in predicting outcomes such as the length of ICU stay and failure of non-invasive respiratory support therapies and to assess the effectiveness of using the ROX (day 1 at admission, day 2, and day 3) versus Acute physiology and chronic health evaluation (APACHE) II scores (at admission) in patients with Coronavirus Disease 2019 (COVID-19) pneumonia and Acute Respiratory Distress Syndrome (ARDS) to predict early, late, and non-responders. After screening 208 intensive care unit patients, a total of 118 COVID-19 patients were enrolled, who were categorized into early (n = 38), late (n = 34), and non-responders (n = 46). Multinomial logistic regression, receiver operating characteristic (ROC), Multivariate Cox regression, and Kaplan-Meier analysis were conducted. Multinomial logistic regressions between late and early responders and between non- and early responders were associated with reduced risk of treatment failures. ROC analysis for early vs. late responders showed that APACHE II on admission had the largest area under the curve (0.847), followed by the ROX index on admission (0.843). For responders vs. non-responders, we found that the ROX index on admission had a slightly better AUC than APACHE II on admission (0.759 vs. 0.751). A higher ROX index on admission [HR (95% CI): 0.29 (0.13-0.52)] and on day 2 [HR (95% CI): 0.55 (0.34-0.89)] were associated with a reduced risk of treatment failure. The ROX index can be used as an independent predictor of early response and mortality outcomes to HFNO and NIV in COVID-19 pneumonia, especially in low-resource settings, and is non-inferior to APACHE II.

Indexed as

COVID-19Noninvasive VentilationPneumoniaAPACHEHumansPrognosisProspective StudiesRetrospective StudiesAPACHE IICOVID-19HFNOhigh-flow nasal oxygenationintensive care unitNIVnon-invasive ventilationROX index

Identifiers

PMID38005908
PMCPMC10675664
OpenAlexW4388534332

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.