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Record W4401594603 · doi:10.1177/2325967124s00037

Paper 24: Cryocompression Results in a Significant Decrease in Opioid Consumption following Shoulder Surgery – A Multi Center Randomized Controlled Trial

2024· article· en· W4401594603 on OpenAlexaboutno aff
Moin Khan, Steve Phillips, Paul Mathew, Vikram Venkateswaran, John Haverstock, Danielle Dagher, Darryl Yardley, D J Dick, Mohit Bhandari

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialShoulder surgeryCenter (category theory)SurgeryConsumption (sociology)Physical therapy

Abstract

fetched live from OpenAlex

Objectives: Elective shoulder surgical procedures, some of the most commonly performed orthopaedic surgeries, are increasing rapidly. 1 The management of pain following shoulder surgery typically includes the use of cryotherapy and the prescription of pain medication, typically in the form of opioid analgesics. Much focus has been put lately on the opioid epidemic, which in part is fueled by excessive prescription of opioid medications. 2,3 Recent studies have indicated that orthopaedic surgeons are some of the highest opioid prescribers, often prescribing above recommended amounts. 4,5 This is especially critical considering that opioid-naïve patients undergoing shoulder surgery are at an increased risk of long-term dependence. 6 With the increased number of shoulder surgeries performed, identifying ways to reduce opioid consumption post-operatively is imperative for orthopaedic surgeons to reduce opioid prescriptions. Cryotherapy is commonly utilized following shoulder surgery to decrease swelling and inflammation, as well as to help alleviate postoperative pain. The application of cold can come in many forms, from ice packs to more complex cryotherapy devices. Previous studies have found a combination of cryotherapy and compression effective at reducing analgesic consumption and increasing recovery in patients undergoing knee and spine surgery, however, efficacy in patients undergoing shoulder surgery has not been evaluated. 79 The aim of this study was to evaluate the effectiveness of a cryocompression device on postoperative shoulder pain, narcotic use, and quality of life when compared to standard care. Methods: A prospective, unblinded, multicentered, randomized controlled trial of 200 patients was performed in 5 hospitals in Ontario, Canada. Patients over the age of 18 scheduled for primary or revision unilateral shoulder surgery were approached by board-certified orthopaedic surgeons for participation between December 2019 and February 2023. Patients were randomized to either the cryocompression group, or standard care. The intervention group received a cryopneumatic device, which consisted of a Game Ready® GRPro® 2.1 system with a Game Ready® ATX® shoulder wrap. The device provides continuous cold and intermittent pneumatic compression therapy to the shoulder joint and surrounding soft tissues. The standard care group received the treating surgeon’s preferred method of cryotherapy. There were no limitations to the type of cryotherapy that could be used in the standard care group, with the exception of a Game Ready device. The standard of care intervention was used as per the treating surgeon’s standard recommendations to patients. In both groups, patients received a standard shoulder immobilizer, postoperative medications and physical therapy as per their treating surgeon and physiotherapist’s standard practices. Narcotic usage post-surgery was evaluated by the number of opioid morphine oral morphine milligram equivalent (OMMEs) consumed during the postoperative period, as well as the time to cessation of narcotic use. Narcotic usage was collected using a patient drug diary which was completed by the patient during the postoperative period. Patient-reported outcome measures (PROMs) consisted of a numeric pain rating scale (NPRS) on a scale ranging from 0 (no pain) to 10 (worst possible pain), quality of life using the 36 item Short Form Survey (SF-36) and its subscales reported on 0-100 scales with higher values representing better outcomes, patient experience assessed using the Net Promoter Score, and adverse events. Narcotic usage was collected after the patient completed their use of their narcotic medication, while PROMs and adverse events were collected at 2, 6 and 12 weeks postoperative. Normality of data was tested using the Shapiro-Wilk test and visualization of residual Q-Q plots. For continuous outcome measures normally distributed data was analyzed using a one-way ANOVA for OMMEs consumed and time to cessation of narcotics, and a two-way repeated measures ANOVA for PROMs. Non-normally distributed data was analyzed using a Mann-Whitney U test for OMMEs consumed and time to cessation of narcotics, and a generalized linear model (GLM) for PROMs. Adverse events were analyzed using a Pearson’s chi-square test. Results: Patients in the cryocompression group showed a significant decrease in post-operative opioid consumption when compared to standard care (median 56.1 OMME [IQR 66.1] vs. median 112 OMME [IQR 99.4]; p=0.02468) (Figure 1). A significant increase in self-reported function (SF-36 Physical Function subscale) was seen in the cryocompression group at 2 weeks when compared to standard care (mean 61.2 ± 21.2 vs. mean 54.2 ± 22.9; p=0.0412). Time to cessation of opioids was lower in the cryocompression group compared to the standard care group, although this measure did not reach statistical significance (median 4 days [IQR 5] vs. median 6 days [IQR 4.5]; p=0.1543). No significant differences were seen in VAS pain or other SF-36 measures at any timepoints despite significant decrease in opioid consumption in the cryocompression group. No significant difference was seen in adverse events between groups (4 standard care, 2 cryocompression, p=0.4379). Conclusions: In patients undergoing unilateral shoulder surgery, the use of a cryocompression device, when compared to standard of care, resulted in a significant decreased opioid consumption post-operatively, as well as increased function at 2 weeks postoperative. [Figure: see text]

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0200.002

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 head0.327
Teacher spread0.293 · 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 designRandomized trial
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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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