Evidence map›Paper›PMID 34069041›Full record

ArticleJournal of clinical medicine2021

Stay Home! Stay Safe! First Post-Discharge Cardiologic Evaluation of Low-Risk-Low-BNP Heart Failure Patients in COVID-19 Era.

Nadia Aspromonte, Luigi Cappannoli, Pietro Scicchitano, Francesco Massari, Ivan Pantano, Massimo Massetti, Filippo Crea, Roberto Valle

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

8 authors.

Nadia AspromonteDepartment of Cardiovascular Sciences, Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, 00168 Rome, Italy.
Luigi CappannoliInstitute of Cardiology, Catholic University of the Sacred Heart, 00168 Rome, Italy.ORCID 0000-0002-6905-9268
Pietro ScicchitanoCardiology Section, F. Perinei Hospital, 70022 Altamura (BA), Italy.
Francesco MassariCardiology Section, F. Perinei Hospital, 70022 Altamura (BA), Italy.
Ivan PantanoCardiology Department, Madonna della Navicella Hospital, 30015 Chioggia (VE), Italy.
Massimo MassettiDepartment of Cardiovascular Sciences, Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, 00168 Rome, Italy.
Filippo CreaDepartment of Cardiovascular Sciences, Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, 00168 Rome, Italy.
Roberto ValleCardiology Department, Madonna della Navicella Hospital, 30015 Chioggia (VE), Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has had a deep impact on periodic outpatient evaluations. The aim of this study was to evaluate the impact of low brain natriuretic peptide (BNP) values in predicting adverse events in heart failure (HF) patients in order to evaluate implications for safe delay of outpatient visits.

methodsThis was a retrospective study. One-thousand patients (mean age: 72 ± 10 years, 561 women) with HF and BNP values <250 pg/mL at discharge were included. A 6-month follow-up was performed. The primary endpoint was a combination of deaths and readmissions for HF within 6-month after discharge.

resultsAt 6-month follow-up, 104 events (10.4%) were recorded (65 HF readmissions and 39 all-cause deaths). Univariate Cox analysis identified as significant predictors of outcome were age (

conclusionsLow pre-discharge BNP levels were associated with low rates of cardiovascular events in HF patients, independently of the frequency of follow-up.

Indexed as

B-type natriuretic peptideheart failuremanagementprognosis

Identifiers

PMID34069041
PMCPMC8156599

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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.