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Opioid Prescribing and Use Following Common Plastic Surgery Procedures

2020· article· en· W3160832456 on OpenAlexaff
Colton Boudreau, Osama A. Samargandi, Connor McGuire, Kaleigh MacIssac, Adel Helmi, David Tang

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2020
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineMedical prescriptionHydromorphoneOpioidNarcoticBreast surgeryAdverse effectAnesthesiaEmergency medicineMedical emergencyBreast cancerInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Overprescribing of opioids has become a topic of interest given the potential adverse outcomes associated with their use. Excess prescribing of opioids has been shown to have individual and societal impacts such as addiction, dependence, and misuse. Opioids are frequently prescribed for analgesia following plastic surgery procedures. This study aims to investigate prescribing patterns and explores self-reported patient experiences with opioid use, pain control and disposal of unused tablets following common hand and breast surgeries. METHODS: Patients undergoing 5 common predetermined breast procedures and 6 common hand procedures in a specified 14-week period were identified by billing code through health information services. Sixty-two hand procedures 46 breast procedures were identified. Collaboration with opioid monitoring services of the Nova Scotia Provincial Monitoring Program (NSPMP) allowed for data surrounding prescription filling rates, drug type, dose and tablets dispensed. Additionally, all patients were contacted to participate in a structured telephone interview surrounding prescription awareness, pain control, and disposal of excess medication. RESULTS: 55.4% and 41.6% of patients received and filled an opioid prescription following a hand or breast procedure, respectively. Hydromorphone was the most commonly prescribed narcotic for both hand and breast procedures. Average number of opioid tablets dispensed following hand and breast procedures was 36.1 and 31.9, respectively. Forty-eight percent and fifty-two percent of hand and breast patients completed phone interviews. 4.2% of breast patients required an opioid refill, whereas no hand patients did. Seventy-three percent of hand 75% of breast patients used at least one over-counter analgesic, most common being acetaminophen alone. Average self-reported pain score and total pain period was not significantly different between those using opioids and those not for both hand and breast procedures. 6.7% and 23.1% of patients report returning excess narcotics to pharmacy, whereas the majority report still having or self-disposing excess tablets. CONCLUSIONS: Opioid prescriptions are frequent following the procedures studied. In general, opioids appear to be prescribed in excess as denoted by self-report low prescription usage, statistically insignificant differences in pain for those using and not using opioids and low refill rates. Additionally, the majority of unused opioids were noted to be still at home or disposed of inappropriately. Taken together, this study suggests a role for reviewing opioid prescribing patterns for common hand and breast procedures to reduce contributions of excess opioids to an ongoing opioid epidemic.

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)0.000
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.039
GPT teacher head0.280
Teacher spread0.240 · 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.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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