Evidence map›Paper›PMID 33453011›Full record

ArticleInternal and emergency medicine2021

Serial KL-6 measurements in COVID-19 patients.

Miriana d'Alessandro, Laura Bergantini, Paolo Cameli, Giuseppe Curatola, Lorenzo Remediani, David Bennett, Francesco Bianchi, Felice Perillo, Luca Volterrani, Maria Antonietta Mazzei and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Internal and emergency medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
6.6field-weighted citation impact, top 2% 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.

  1. Pooled it
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  13. Autophagy in Inflammatory Response against SARS-CoV-2.International journal of molecular sciences · 2023
    Review
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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

12 authors at 1 institution in 1 country.

Miriana d'AlessandroRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy. dalessandro.miriana@gmail.com.ORCID 0000-0002-2368-5722
Laura BergantiniRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
Paolo Cameli
Giuseppe CuratolaRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
Lorenzo RemedianiRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
David BennettRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
Francesco BianchiRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
Felice PerilloRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
Luca VolterraniRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
Maria Antonietta MazzeiRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
Elena BargagliRespiratory Diseases and Lung Transplantation, Department of Medical and Surgical Sciences & Neurosciences, Siena University Hospital, Siena, Italy.
Siena COVID
University of Siena · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV2-induced direct cytopathic effects against type II pneumocytes are suspected to play a role in mediating and perpetuating lung damage. The aim of this study was to evaluate serum KL-6 behavior in COVID-19 patients to investigate its potential role in predicting clinical course. Sixty patients (median age IQR, 65 (52-69), 43 males), hospitalized for COVID-19 at Siena COVID Unit University Hospital, were prospectively enrolled. Twenty-six patients were selected (median age IQR, 63 (55-71), 16 males); all of them underwent follow-up evaluations, including clinical, radiological, functional, and serum KL-6 assessments, after 6 (t1) and 9 (t2) months from hospital discharge. At t0, KL-6 concentrations were significantly higher than those at t1 (760 (311-1218) vs. 309 (210-408) p = 0.0208) and t2 (760 (311-1218) vs 324 (279-458), p = 0.0365). At t0, KL-6 concentrations were increased in patients with fibrotic lung alterations than in non-fibrotic group (755 (370-1023) vs. 305 (225-608), p = 0.0225). Area under the receiver operating curve (AUROC) analysis showed that basal KL-6 levels showed good accuracy in discriminating patients with fibrotic sequelae radiologically documented (AUC 85%, p = 0.0404). KL-6 concentrations in patients with fibrotic involvement were significantly reduced at t1 (755 (370-1023) vs. 290 (197-521), p = 0.0366) and t2 (755 (370-1023) vs. 318 (173-435), p = 0.0490). Serum concentrations of KL-6 in hospitalized COVID-19 patients may contribute to identify severe patients requiring mechanical ventilation and to predict those who will develop pulmonary fibrotic sequelae in the follow-up.

Indexed as

Severity of Illness IndexAdultAgedBiomarkersCOVID-19Disease ProgressionHumansMaleMiddle AgedMucin-1PrognosisSARS-CoV-2BiomarkersMUC1 protein, humanMucin-1BiomarkerCOVID-19KL-6Prognosis

Identifiers

PMID33453011
PMCPMC7811154
OpenAlexW3124963771

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.