Evidence map›Paper›PMID 33387336›Full record

ArticleJournal of nephrology2021

Risk factors and action thresholds for the novel coronavirus pandemic. Insights from the Italian Society of Nephrology COVID-19 Survey.

Maurizio Nordio, Gianpaolo Reboldi, Anteo Di Napoli, Giuseppe Quintaliani, Federico Alberici, Maurizio Postorino, Filippo Aucella, Piergiorgio Messa, Giuliano Brunori, Italian Society of Nephrology COVID-19 Research Group

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in Journal of nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

10 citing papers in PubMed, 12 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

10 authors at 7 institutions in 1 country.

Maurizio Nordio *Unit of Nephrology, General Hospital, Piazzale Ospedale, 23, 31100, Treviso, Italy.ORCID http://orcid.org/0000-0002-9054-1593
Gianpaolo Reboldi *Department of Medicine, University of Perugia, Perugia, Italy.ORCID https://orcid.org/0000-0002-9877-0702
Anteo Di Napoli *National Institute for Health Migration and Poverty (INMP), Rome, Italy.
Giuseppe QuintalianiItalian Society of Nephrology, Viale dell'Università, 11, 00185, Rome, RM, Italy.
Federico AlbericiDepartment of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy.
Maurizio PostorinoUnit of Nephrology, Grande Ospedale Metropolitano Reggio Calabria, Reggio Calabria, Italy.
Filippo AucellaNephrology and Dialysis Unit, IRCCS "Casa Sollievo Della Sofferenza" Scientific Institute for Research and Health Care, San Giovanni Rotondo, Italy.
Piergiorgio MessaDivision of Nephrology, Dialysis and Renal Transplantation, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Milan, Italy.
Giuliano BrunoriItalian Society of Nephrology, Viale dell'Università, 11, 00185, Rome, RM, Italy. giuliano.brunori@apss.tn.it.
Italian Society of Nephrology COVID-19 Research Group
Italian Society of Physiotherapy · ITCa' Foncello Hospital · ITCasa Sollievo della Sofferenza · ITFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico · ITUniversity of Brescia · ITUniversity of Perugia · ITUniversity of Reggio Calabria · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimOver 80% (365/454) of the nation's centers participated in the Italian Society of Nephrology COVID-19 Survey. Out of 60,441 surveyed patients, 1368 were infected as of April 23rd, 2020. However, center-specific proportions showed substantial heterogeneity. We therefore undertook new analyses to identify explanatory factors, contextual effects, and decision rules for infection containment.

methodsWe investigated fixed factors and contextual effects by multilevel modeling. Classification and Regression Tree (CART) analysis was used to develop decision rules.

resultsIncreased positivity among hemodialysis patients was predicted by center location [incidence rate ratio (IRR) 1.34, 95% confidence interval (CI) 1.20-1.51], positive healthcare workers (IRR 1.09, 95% CI 1.02-1.17), test-all policy (IRR 5.94, 95% CI 3.36-10.45), and infected proportion in the general population (IRR 1.002, 95% CI 1.001-1.003) (all p < 0.01). Conversely, lockdown duration exerted a protective effect (IRR 0.95, 95% CI 0.94-0.98) (p < 0.01). The province-contextual effects accounted for 10% of the total variability. Predictive factors for peritoneal dialysis and transplant cases were center location and infected proportion in the general population. Using recursive partitioning, we identified decision thresholds at general population incidence ≥ 229 per 100,000 and at ≥ 3 positive healthcare workers.

conclusionsBeyond fixed risk factors, shared with the general population, the increased and heterogeneous proportion of positive patients is related to the center's testing policy, the number of positive patients and healthcare workers, and to contextual effects at the province level. Nephrology centers may adopt simple decision rules to strengthen containment measures timely.

Indexed as

NephrologyPandemicsSocieties, MedicalCOVID-19FemaleHumansItalyMaleRisk AssessmentRisk FactorsSurveys and QuestionnairesClassification treeContextual analysisCOVID-19Renal replacement therapy

Identifiers

PMID33387336
PMCPMC7776284
OpenAlexW3113394057

What OpenQuestion holds

Textmetadata
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.