Evidence map›Paper›PMID 37946100›Full record

SynthesisBMC infectious diseases2023

Efficacy and safety of therapies for COVID-19 in pregnancy: a systematic review and meta-analysis.

Francesco Di Gennaro, Giacomo Guido, Luisa Frallonardo, Francesco Vladimiro Segala, Rosalba De Nola, Gianluca Raffaello Damiani, Elda De Vita, Valentina Totaro, Mario Barbagallo, Emanuele Nicastri and 5 more

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in BMC infectious diseases, 2023. 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
1.2field-weighted citation impact, top 20% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Observational
  2. Review
  3. Article
  4. Article
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

15 authors at 3 institutions in 1 country.

Francesco Di GennaroClinic of Infectious Diseases, Department of Precision and Regenerative Medicine and Ionian Area - (DiMePRe-J), University of "Aldo Moro", University of Bari "Aldo Moro", Piazza Giulio Cesare N. 11 Cap 70124, Bari, Italy.
Giacomo GuidoClinic of Infectious Diseases, Department of Precision and Regenerative Medicine and Ionian Area - (DiMePRe-J), University of "Aldo Moro", University of Bari "Aldo Moro", Piazza Giulio Cesare N. 11 Cap 70124, Bari, Italy.
Luisa FrallonardoClinic of Infectious Diseases, Department of Precision and Regenerative Medicine and Ionian Area - (DiMePRe-J), University of "Aldo Moro", University of Bari "Aldo Moro", Piazza Giulio Cesare N. 11 Cap 70124, Bari, Italy. luisana.frallonardo@gmail.com.
Francesco Vladimiro SegalaClinic of Infectious Diseases, Department of Precision and Regenerative Medicine and Ionian Area - (DiMePRe-J), University of "Aldo Moro", University of Bari "Aldo Moro", Piazza Giulio Cesare N. 11 Cap 70124, Bari, Italy.
Rosalba De NolaClinic of Obstetrics & Gynaecology, University of Bari "Aldo Moro", Bari, Italy.
Gianluca Raffaello DamianiClinic of Obstetrics & Gynaecology, University of Bari "Aldo Moro", Bari, Italy.
Elda De VitaClinic of Infectious Diseases, Department of Precision and Regenerative Medicine and Ionian Area - (DiMePRe-J), University of "Aldo Moro", University of Bari "Aldo Moro", Piazza Giulio Cesare N. 11 Cap 70124, Bari, Italy.
Valentina TotaroClinic of Infectious Diseases, Department of Precision and Regenerative Medicine and Ionian Area - (DiMePRe-J), University of "Aldo Moro", University of Bari "Aldo Moro", Piazza Giulio Cesare N. 11 Cap 70124, Bari, Italy.
Mario BarbagalloGeriatrics Section, Department of Internal Medicine, University of Palermo, Palermo, Italy.
Emanuele NicastriNational Institute for Infectious Diseases 'Lazzaro Spallanzani' (IRCCS), Rome, Italy.
Antonella VimercatiClinic of Obstetrics & Gynaecology, University of Bari "Aldo Moro", Bari, Italy.
Ettore CicinelliClinic of Obstetrics & Gynaecology, University of Bari "Aldo Moro", Bari, Italy.
Giuseppina LiuzziNational Institute for Infectious Diseases 'Lazzaro Spallanzani' (IRCCS), Rome, Italy.
Nicola VeroneseGeriatrics Section, Department of Internal Medicine, University of Palermo, Palermo, Italy.
Annalisa SaracinoClinic of Infectious Diseases, Department of Precision and Regenerative Medicine and Ionian Area - (DiMePRe-J), University of "Aldo Moro", University of Bari "Aldo Moro", Piazza Giulio Cesare N. 11 Cap 70124, Bari, Italy.
University of Bari Aldo Moro · ITIstituto Nazionale per le Malattie Infettive Lazzaro Spallanzani · ITUniversity of Palermo · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical evidence suggests that pregnant women are more vulnerable to COVID-19, since they are at increased risk for disease progression and for obstetric complications, such as premature labor, miscarriage, preeclampsia, cesarean delivery, fetal growth restriction and perinatal death. Despite this evidence, pregnant women are often excluded from clinical trials, resulting in limited knowledge on COVID-19 management. The aim of this systematic review and meta-analysis is to provide better evidence on the efficacy and safety of available COVID-19 treatment in pregnant women.

methodsFour authors searched major electronic databases from inception until 1 st November-2022 for controlled trials/observational studies, investigating outcomes after the administration of anti-SARS-CoV-2 treatments in pregnant women affected by COVID-19. The analyses investigated the cumulative incidence of delivery and maternal outcomes in pregnant women, comparing those taking active medication vs standard care. Risk ratios (RRs) with 95% confidence intervals were calculated. Statistical significance was assessed using the random effects model and inverse-variance method. This systematic review and meta-analysis was conducted in accordance with the updated 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The protocol has been registered in Prospero (number registration: CRD42023397445).

resultsFrom initially 937 non duplicate records, we assessed the full texts of 40 articles, finally including ten studies. In six studies, including 1627 patients, the use of casirivimab/imdevimab (CAS/IMD), remdesivir, and IFN-alpha 2b significantly decreased the need of cesarean section ((RR = 0.665; 95%CI: 0.491-0.899; p = 0.008; I 2 = 19.5%;) (Table 1, (Fig. 1). Treatments did not decrease the risk of preterm delivery, admission to neonatal ICU, or stillbirth/perinatal loss (p-values > 0.50 for all these outcomes) and did not prevent the progression of disease towards severe degrees (k = 8; 2,374 pregnant women; RR = 0.778; 95%CI: 0.550-1.099; p = 0.15; I 2 = 0%). Moreover, the use of medications during pregnancy did not modify the incidence of maternal death in two studies (Table 2).

conclusionsTo our analysis, CAS/IMD, remdesivir, and IFN alpha 2b reduced the number of cesarean sections but demonstrated no effect on disease progression and other obstetric and COVID-19 related outcomes. The inability to evaluate the influence of viral load on illness development in pregnant women was attributed to lack of data. In our systematic review, no major side effects were reported. Though, it is essential for the medical community to focus more on clinical trials and less on episodic case reports and case series, with standardization of fetal and maternal outcomes.

Indexed as

COVID-19Cesarean SectionCOVID-19 Drug TreatmentDisease ProgressionFemaleHumansInfant, NewbornPregnancyPregnancy OutcomeStillbirthAntiviralsCOVID-19Maternal morbidityMonoclonal antibodiesPregnancySARS-CoV-2

Identifiers

PMID37946100
PMCPMC10634005
OpenAlexW4388534482

What Socratic 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 Socratic graph.