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Record W2589170171 · doi:10.1177/2049463717695695

Short- and long-term results of an inpatient programme to manage Complex Regional Pain Syndrome in children and adolescents

2017· article· en· W2589170171 on OpenAlexaboutno aff
Giovanni Cucchiaro, Kevin Craig, K. Marks, Kristin Cooley, Thalitha Kay Black Cox, Jennifer E. Schwartz

Bibliographic record

VenueBritish Journal of Pain · 2017
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineComplex regional pain syndromeRehabilitationFunctional Independence MeasurePhysical therapyAnesthesia

Abstract

fetched live from OpenAlex

The aim of this retrospective study was to determine whether an inpatient approach and the use of regional anaesthesia techniques can accelerate the recovery to normal functions in children with Complex Regional Pain Syndrome (CRPS). This study looked at the data of patients admitted to the rehabilitation unit with a diagnosis of CRPS from January 2010 to April 2015. Variables such as hospital stay, medications administered, regional anaesthesia procedures, changes in functional status prior to treatment and at the time of discharge, psychological evaluation and diagnosis were evaluated. A total of 31 patients (21 females and 10 males) were admitted with a diagnosis of CRPS 1 and 2. In all, 97% of the patients received a peripheral or central nerve catheter for an average of 4 days with pain scores of Verbal Numeric Scale (VNS) score = 1.0 ± 0.7 and an average length of hospital stay of 8.2 ± 2.6 days. The modified Functional Independence Measure for Children (WeeFIM) scores and Canadian Association of Occupational Therapists tests significantly improved at the time of hospital discharge, as well as their pain scores, which decreased from 8.2 ± 2 to 1.6 ± 3. In conclusion, these data suggest that the use of regional anaesthesia techniques and an intensive inpatient rehabilitation programme could accelerate the recovery of children with CRPS.

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)0.003
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 score0.297
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.284
Teacher spread0.254 · 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

Citations22
Published2017
Admission routes1
Has abstractyes

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