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Record W1993214465 · doi:10.4236/ojped.2014.43028

The Influence of Pain: Quality of Life after <i>Pectus excavatum</i> Correction

2014· article· en· W1993214465 on OpenAlexaff
Wietse P. Zuidema, Alida F. W. van der Steeg, Jan Wolter Oosterhuis, Christien Sleeboom, Stefan M. van der Heide, Elly S.M. de Lange–de Klerk, Hugo A. Heij

Bibliographic record

VenueOpen Journal of Pediatrics · 2014
Typearticle
Languageen
FieldMedicine
TopicPectus Deformity Diagnosis and Treatment
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsPectus excavatumMedicineQuality of life (healthcare)Facet (psychology)Physical therapyPatient satisfactionProspective cohort studySurgery

Abstract

fetched live from OpenAlex

Introduction: The main indication for surgery of thoracic wall deformities (TWD) is psychological due to cosmetic complaints. The assumption is that appearances have a negative effect on self-esteem and quality of life (QoL). Correction should result in improvement. Methods: Prospective trial. QoL was assessed using the CHQ and the WHOQOL-bref. Measurements were taken before surgery (T1) and 6 weeks thereafter (T2). Results: Forty-two patients were included. WHOQOL-bref showed differences between pre-operative and six weeks past surgery on facet body image (p = 0.003). Self-esteem (CHQ) did not show a significant improvement at T2. Concerning the scores on the single step questionnaire (SSQ), 33 patients were “very” to “extremely satisfied” with appearance and increased self-esteem (p < 0.001). Concerning the domain “pain and physical complaints”, CHQ did show a significant change (p < 0.001) with more complaints at T2. Conclusion: Six weeks after surgical correction of a TWD satisfaction with the “new” chest is good; pain seems to be a problem with possible negative influence on self-esteem.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.318
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2014
Admission routes1
Has abstractyes

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Same venueOpen Journal of PediatricsSame topicPectus Deformity Diagnosis and TreatmentFrench-language works237,207