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Analysis of ralated factors of chronic post surgical pain of video assisted thoracic surgery

2017· article· en· W3029256696 on OpenAlexaboutno aff
Qingzhen Xu, Guiqi Song, Jing He, Mingran Xie

Bibliographic record

VenueZhonghua xiandai huli zazhi · 2017
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIncidence (geometry)Visual analogue scaleSurgeryPostoperative painCardiothoracic surgeryElective surgeryAnesthesia

Abstract

fetched live from OpenAlex

Objective To explore the incidence of chronic postsurgical pain (CPSP) of video assisted thoracic surgery (VATS) and its influencing factors. Methods Totally 216 patients who received elective VATS in a class Ⅲ grade A hospital between January and June 2016 were selected by convenience sampling. Their pain level was assessed with Visual Analogue Scale (VAS) in 1 to 3 days after surgery. The patients were then investigated with Simplified McGill Pain Questionnaire (SF-MPQ) in 1 to 3 months after surgery, with the features of CPSP analyzed and 11 related risk factors statistically analyzed. Results The incidence of CPSP in 3 months after surgery in the 199 patients who received follow-up visits was 49.20%, of which 18.37% suffered moderate pain, and 32.65% felt constant pain. Age (OR=2.16) and pain level in 1-3 days after surgery (OR=2.25) were independent risk factors to CPSP (P<0.05) . Conclusions CPSP occurred in a certain proportion of patients who received VATS. Actively and effectively controlling acute post surgical pain in especially young patients may help to reduce the incidenc of CPSP. Key words: Pain, postsurgerical; Thoracic surgery; Thoracoscope; Risk factors

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.030
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.333
Teacher spread0.303 · 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 teacher head, 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

Citations0
Published2017
Admission routes1
Has abstractyes

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