Evidence map›Paper›PMID 37834877›Full record

ArticleJournal of clinical medicine2023

Automatic Variable Selection Algorithms in Prognostic Factor Research in Neck Pain.

Bernard X W Liew, Francisco M Kovacs, David Rügamer, Ana Royuela

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 39% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 3 institutions in 3 countries.

Bernard X W LiewSchool of Sport, Rehabilitation and Exercise Sciences, University of Essex, Colchester CO4 3SQ, Essex, UK.ORCID 0000-0002-7057-7548
Francisco M KovacsUnidad de la Espalda Kovacs, HLA-Moncloa University Hospital, 28008 Madrid, Spain.ORCID 0000-0002-2984-4800
David RügamerDepartment of Statistics, Ludwig-Maximilians-Universität München, 80539 Munich, Germany.
Ana RoyuelaBiostatistics Unit, Hospital Puerta de Hierro, Instituto Investigación Sanitaria Puerta de Hierro-Segovia de Arana, Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública, Red Española de Investigadores en Dolencias de la Espalda, 28222 Madrid, Spain.ORCID 0000-0003-1665-081X
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública · ESLudwig-Maximilians-Universität München · DEUniversity of Essex · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to compare the variable selection strategies of different machine learning (ML) and statistical algorithms in the prognosis of neck pain (NP) recovery. A total of 3001 participants with NP were included. Three dichotomous outcomes of an improvement in NP, arm pain (AP), and disability at 3 months follow-up were used. Twenty-five variables (twenty-eight parameters) were included as predictors. There were more parameters than variables, as some categorical variables had >2 levels. Eight modelling techniques were compared: stepwise regression based on unadjusted

Indexed as

machine learningneck painprognosisstatisticsvariable selection

Identifiers

PMID37834877
PMCPMC10573798
OpenAlexW4387120003

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.