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Record W1970639348 · doi:10.1097/bcr.0b013e3181cb8e94

Effectiveness of Pain Management Following Electrical Injury

2010· article· en· W1970639348 on OpenAlexaff
Adrienne L K Li, Manuel Gómez, Joel Fish

Bibliographic record

VenueJournal of Burn Care & Research · 2010
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsSt. John's Rehab HospitalHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRehabilitationElectrical burnPhysical therapyShouldersAcetaminophenMedical recordAnesthesiaSurgeryBurn injury

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the effectiveness of pain management after electrical injury. A retrospective hospital chart review was conducted among electrically injured patients discharged from the outpatient burn clinic of a rehabilitation hospital (July 1, 1999, to July 31, 2008). Demographic data, numeric pain ratings (NPRs) at initial assessment and discharge, medications, nonpharmacologic modalities, and their effects before admission and after rehabilitation were collected. Pain management effects were compared between high (> or =1000 v) and low (<1000 v) voltage, and between electrical contact and electrical flash patients, using Student's t-test and chi, with a P < .05 considered significant. Of 82 electrical patients discharged during the study period, 27 were excluded because of incomplete data, leaving 55 patients who had a mean age +/-SD of 40.7 +/- 11.3 years, TBSA of 19.2 +/- 22.7%, and treatment duration of 16.5 +/- 15.7 months. The majority were men (90.9%), most injuries occurred at work (98.2%), mainly caused by low voltage (n = 32, 58.2%), and the rest caused by high voltage (n = 18, 32.7%). Electrical contact was more common (54.5%) than electrical flash (45.5%). Pain was a chief complaint (92.7%), and hands were the most affected (61.8%), followed by head and neck (38.2%), shoulders (38.2%), and back torso (38.2%). Before rehabilitation, the most common medication were opioids (61.8%), relieving pain in 82.4%, followed by acetaminophen (47.3%) alleviating pain in 84.6%. Heat treatment was the most common nonpharmacologic modality (20.0%) relieving pain in 81.8%, followed by massage therapy (14.5%) alleviating pain in 75.0%. During the rehabilitation program, antidepressants were the most common medication (74.5%), relieving pain in 22.0%, followed by nonsteroidal antiinflammatory drugs (61.8%), alleviating pain in 70.6%. Massage therapy was the most common nonpharmacologic modality (60.0%), alleviating pain in 75.8%, and then cognitive behavioral therapy (54.5%), alleviating pain in 40.0%. There were pain improvements in all anatomic locations after rehabilitation except for the back torso, where pain increased 0.7 +/- 2.9 points. Opioids were more commonly used in high voltage (P < .05), and cognitive behavioral therapy in low-voltage injuries (P < .05). Opioids were used in both electrical flash and electrical contact injuries. Pain in electrically injured patients remains an important issue and should continue to be addressed in a multimodal way. It is hoped that this study will guide us to design future interventions for pain control after electrical injury.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.391
Teacher spread0.367 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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