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Record W2278840164 · doi:10.1213/ane.0000000000000672

Chronic Opioid Use and Central Sleep Apnea

2015· review· en· W2278840164 on OpenAlexaff
Denis Correa, Robert J. Farney, Frances Chung, Arun Prasad, David K. Lam, Jean Wong

Bibliographic record

VenueAnesthesia & Analgesia · 2015
Typereview
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicinePolysomnographyOpioidSleep apneaPerioperativeCentral sleep apneaMEDLINEChronic painObstructive sleep apneaAnesthesiaIntensive care medicineApneaInternal medicinePhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic opioid use has been associated with the development of sleep-disordered breathing (SDB) such as central sleep apnea (CSA). Patients receiving chronic opioids may suffer from unrecognized sleep apnea that contributes to opioid-overdose death. Currently, information regarding the perioperative management of patients with chronic opioid-associated CSA is limited. The objectives of this review are to define the clinical manifestations of SDB associated with chronic opioid therapy, especially CSA, and to highlight their prevalence, mechanisms, risk factors, and perioperative management. METHODS: We searched Medline (1983-2014), Medline In-Process and other nonindexed citations (July 2014), EMBASE (1983-2014), the Cochrane Database of Systematic Reviews (January 2005-2014), the Cochrane Central Registry of Controlled Trials (July 2014), and PubMed basic search for new materials (1983-2014). Anesthesia and Sleep Medicine meeting abstracts were also searched for relevant articles. We included all prospective, retrospective studies and case reports in which CSA and chronic opioid use was confirmed by polysomnography. CSA was defined as the absence of airflow for ≥ 10 seconds with the absence of breathing efforts. A Central Apnea Index ≥ 5 events/h was considered significant. RESULTS: The search strategy yielded 8 studies which included 560 patients. The overall prevalence of CSA in patients taking chronic opioids was high (24%). The morphine equivalent daily dose (MEDD) was strongly associated with the severity of the SDB, predominantly CSA, with an MEDD of >200 mg being a threshold of particular concern. Concurrent use of benzodiazepines or hypnotics was associated with the severity of CSA in one study. Body mass index was inversely related to the severity of SDB. There were various recommendations regarding the best type of positive airway pressure therapy for the treatment of opioid-associated CSA. Continuous positive airway pressure may be ineffective in eliminating, or may even increase, CSA. Adaptive servoventilation and bilevel positive airway pressure ventilation were effective according to some reports. CONCLUSIONS: The overall prevalence of CSA in patients taking chronic opioids was 24%. The most important risk factors for severity of CSA were an MEDD >200 mg, and low or normal body mass index. Continuous positive airway pressure is often ineffective for treating CSA. Limited data are available on the perioperative management of patients with CSA associated with chronic opioid use. Further prospective studies on the perioperative risks and management of these patients are needed.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.054
GPT teacher head0.334
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations195
Published2015
Admission routes1
Has abstractyes

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