Evidence map›Paper›PMID 24610167›Full record

ArticleLa Radiologia medica2014

Congenital cystic lung disease: prenatal ultrasound and postnatal multidetector computer tomography evaluation. Correlation with surgical and pathological data.

Maria Pia Bondioni, Diego Gatta, Vassilios Lougaris, Nicoletta Palai, Marino Signorelli, Silvia Michelini, Giuseppe Di Gaetano, Paola Tessitore, Lorella Mascaro, Andrea Tironi and 3 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in La Radiologia medica, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 86% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
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

13 authors at 2 institutions in 1 country.

Maria Pia BondioniDepartment of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy, bondioni.pia@tin.it.
Diego Gatta
Vassilios Lougaris
Nicoletta Palai
Marino Signorelli
Silvia Michelini
Giuseppe Di Gaetano
Paola Tessitore
Lorella Mascaro
Andrea Tironi
Giovanni Boroni
Roberto Maroldi
Daniele Alberti
University of Brescia · ITAzienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this study was to evaluate the diagnostic accuracy of postnatal multidetector computed tomography (MDCT) compared with prenatal ultrasound (US), surgical findings, and histology, in 33 patients with congenital cystic lung disease.

methodsThirty-three patients, 17 males and 16 females, were evaluated by MDCT. Twenty-seven of these patients underwent prenatal US between week 18 and 22, and between week 32 and 35 of gestation. Lung lobectomy, segmentectomy, atypical resection, lesion resection were performed in 31 patients and surgical specimens were analysed.

resultsPrenatal US and MDCT correctly diagnosed 76.9 and 94 % of the lesions, respectively. Disagreement occurred in six lesions with prenatal US and in two lesions with MDCT. No statistically significant differences were observed between the two techniques (P = 0.122).

conclusionsAs most surgeons consider the surgical resection of these lesions mandatory, our study underscores the essential role of imaging, in particular CT, in providing invaluable preoperative information on congenital cystic lung diseases recognised in uterus.

Indexed as

Tomography, X-Ray ComputedUltrasonography, PrenatalFemaleHumansInfantInfant, NewbornLung DiseasesMaleMultidetector Computed TomographyReproducibility of ResultsRetrospective Studies

Identifiers

PMID24610167
OpenAlexW2060782618

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.