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Record W2143715556 · doi:10.1186/1753-6561-9-s1-a5

Can aggressive postoperative non-narcotic therapy replace narcotics in patients undergoing laparoscopic hysterectomies?

2015· article· en· W2143715556 on OpenAlexaffabout
Gurdeep Singh, SK Bates

Bibliographic record

VenueBMC Proceedings · 2015
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineNarcoticNauseaAnalgesicVomitingAnesthesiaAcetaminophenSedationAdverse effectOpioidSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Pain, although invariably present after surgical procedures, is not always well controlled. Medications from different analgesic groups are often used to control post-operative pain. Recently, attention has turned towards the optimization of non-opioid analgesics including NSAIDS and acetaminophen. After gynaecologic laparoscopy up to 80% of patients may require opioid analgesia. However, opioids can have adverse effects including nausea, vomiting, sedation, and respiratory depression. Thus the prudent surgeon attempts to use a narcotic-sparing approach to post-operative analgesia. Theoretically, aggressive non-narcotic analgesic administration will result in less narcotic use. Fortunately, both NSAIDs and acetaminophen are very effective in the control of moderate to severe pain and have few side effects. Our research question then is: “What is the post-operative narcotic use amongst women undergoing laparoscopic hysterectomy who receive aggressive non-narcotic therapy?” The subjects of interest were undergoing laparoscopic hysterectomy in a Canadian community hospital. Data from one calendar year was reviewed. For all patients the same routine pre-printed orders were used by the nursing staff. The order set included non-prn (non-discretionary) post-operative non-narcotic analgesics (ketorolac and acetaminophen). Narcotics were administered by the nursing staff on a prn basis for non-response/breakthrough pain after administration of the non-narcotic analgesics. Two databases, Meditech® and OR Manager® were used to extract information. Medication administration was determined from the Meditech® “Medications” module. Only ward administration of narcotics was included. All narcotics were converted to IV-morphine equivalents using Canadian Pharmacist Association (2008) morphine-centric equi-analgesic conversions. The data was tabulated and analyzed using Microsoft Excel. Two hundred sixteen women underwent laparoscopic hysterectomy in the year ending July 30 2013. Meperedine, morphine, codeine, tramadol, and oxycodone were the narcotics administered. Overall, only 29% of the patients received narcotics. The mean narcotic dose in those patients who received narcotics was 4.1 morphine-equivalent mgs IV. Of those who received post-op narcotics 22% did so between hours 0 and 6 and 23% between hours 6 and 12. When between-surgeon comparison was performed there was marked variation in narcotic consumption by patients ranging from approximately 20% to 40%. Most (71%) women in this laparoscopic hysterectomy cohort did not receive any narcotics. This is likely attributable to the aggressive use of non-narcotic analgesics. There was unexplained between-surgeon variability in patient narcotic usage. Routine non-prn (non-discretionary) order sets offer an attractive therapeutic option for the management of post-op pain.

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)0.000
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 score0.032
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.269
Teacher spread0.239 · 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".

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Citations0
Published2015
Admission routes2
Has abstractyes

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