Evidence map›Paper›PMID 38360688›Full record

ArticleEuropean journal of medical research2024

New score to predict COVID-19 progression in vaccine and early treatment era: the COVID-19 Sardinian Progression Score (CSPS).

Andrea De Vito, Laura Saderi, Agnese Colpani, Mariangela V Puci, Beatrice Zauli, Vito Fiore, Marco Fois, Maria Chiara Meloni, Alessandra Bitti, Giulia Moi and 4 more

Open access · goldAbstract read
In one paragraph

Article in European journal of medical research, 2024. 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
1.2field-weighted citation impact, top 25% 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, 3 citations in OpenAlex.

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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

14 authors at 1 institution in 1 country.

Andrea De Vito *Unit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy. andreadevitoaho@gmail.com.
Laura Saderi *Clinical Epidemiology and Medical Statistics Unit, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Agnese ColpaniUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Mariangela V PuciClinical Epidemiology and Medical Statistics Unit, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Beatrice ZauliUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Vito FioreUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Marco FoisUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Maria Chiara MeloniUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Alessandra BittiUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Giulia MoiUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Ivana MaidaUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Sergio BabudieriUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Giovanni SotgiuClinical Epidemiology and Medical Statistics Unit, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
Giordano MadedduUnit of Infectious Disease, Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100, Sassari, Italy.
University of Sassari · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral scores aimed at predicting COVID-19 progression have been proposed. As the variables vaccination and early SARS-CoV-2 treatment were systematically excluded from the prognostic scores, the present study's objective was to develop a new model adapted to the current epidemiological scenario.

methodsWe included all patients evaluated by the Infectious Disease Unit in Sassari, with SARS-CoV-2 infection and without signs of respiratory failure at the first evaluation (P/F > 300). Disease progression was defined by the prescription of supplemental oxygen. In addition, variables related to demographics, vaccines, comorbidities, symptoms, CT scans, blood tests, and therapies were collected. Multivariate logistic regression modelling was performed to determine factors associated with progression; any variable with significant univariate test or clinical relevance was selected as a candidate for multivariate analysis. Hosmer-Lemeshow (HL) goodness of fit statistic was calculated. Odds ratio values were used to derive an integer score for developing an easy-to-use progression risk score. The discrimination performance of the risk index was determined using the AUC, and the best cut-off point, according to the Youden index, sensitivity, specificity, predictive value, and likelihood ratio, was chosen.

results1145 patients [median (IQR) age 74 (62-83) years; 53.5% males] were enrolled; 336 (29.3%) had disease progression. Patients with a clinical progression were older and showed more comorbidities; furthermore, they were less vaccinated and exposed to preventive therapy. In the multivariate logistic regression analysis, age ≥ 60 years, COPD, dementia, haematological tumours, heart failure, exposure to no or one vaccine dose, fever, dyspnoea, GGO, consolidation, ferritin, De Ritis ≥ 1.2, LDH, and no exposure to early anti-SARS-CoV-2 treatment were associated with disease progression. The final risk score ranged from 0 to 45. The ROC curve analysis showed an AUC of 0.92 (95% CI 0.90-0.93) with a 93.7% specificity and 72.9% sensitivity. Low risk was defined when the cut-off value was less than 23. Three risk levels were identified: low (0-23 points), medium (24-35), and high (≥ 36).

conclusionsThe proportion of patients with progression increases with high scores: the assessment of the risk could be helpful for clinicians to plan appropriate therapeutic strategies.

Indexed as

COVID-19VaccinesAgedDisease ProgressionFemaleHumansMaleMiddle AgedRetrospective StudiesSARS-CoV-2VaccinesAntiviral treatmentCOVID-19Progression risk scoreSARS-CoV-2ScoreVaccination

Identifiers

PMID38360688
PMCPMC10868088
OpenAlexW4391842989

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.