Evidence map›Paper›PMID 29268425›Full record

ArticleJournal of thoracic disease2017

The biostatistical minimum.

Luca Bertolaccini, Alessandro Pardolesi, Piergiorgio Solli

Abstract readEditorial
In one paragraph

Article in Journal of thoracic disease, 2017. 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
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.

  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

3 authors.

Luca BertolacciniDepartment of Thoracic Surgery, Maggiore-Bellaria Teaching Hospitals, Bologna, Italy.
Alessandro PardolesiDepartment of Thoracic Surgery, Maggiore-Bellaria Teaching Hospitals, Bologna, Italy.
Piergiorgio SolliDepartment of Thoracic Surgery, Maggiore-Bellaria Teaching Hospitals, Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Every day in our clinical practice, probability and statistics are used for a broad variety of actions, including the explanation of levels of risk to patients, the access to clinical guidelines, the understanding of research publications, and the writing of investigation papers for analysing numerical data and treatments options. Therefore, an unintentional statistical misconduct may originate from many sources. It is often difficult to detect, and little is known regarding the prevalence or underlying causes of research misconduct among biomedical researchers. The improvements in teaching statistics to thoracic surgeons should improve the thoughtful of statistical concepts and should reduce the incidence of fallacies. The Biostatistical basis should comprise the aspect of the Biostatistics that surgeons should be aware of correctly interpreting in their research findings: the understanding of p-values, confidence intervals, Student's t-tests, Z test, chi-square goodness of fit, ANOVA tables, and basic statistical models (linear or logistic regression). The understanding of Biostatistics is essential to all thoracic surgeons, and it is not unaware since most received some statistics lessons in their training. The Statistic Corner of the Journal of Thoracic Diseases kept the emphasis on Biostatistical methods to applies and when. Thus, various authors wrote about the analyses of several types of outcomes variables, the analyses of study design, the measures of association and impact, and the general strategies for the statistical analyses. Deceptively, these Statistic Corner articles have only scratched the surface. Nonetheless, we hope that had provided a stimulus to enhance the skills to interpret Biostatistics.

Indexed as

biostatisticsLung cancermethodologystatistics

Identifiers

PMID29268425
PMCPMC5723836

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.