Opioid Use in Adults With Sickle Cell Disease Hospitalized During Vaso-Occlusive Crisis: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: While pain is the hallmark of sickle cell disease (SCD), healthcare personnel are often ill-equipped to adequately treat patients who present in vaso-occlusive crisis (VOC). Although symptom severity varies from individual to individual, SCD is characterized by intervallic pain as a result of oxygen deprivation in tissues and organs. Regardless of pain severity, SCD patients are often viewed as drug seekers by healthcare personnel who have concerns regarding patients' dependence on opioids which may lead to addiction. The objective was to assess the types and amount of opioids used to treat VOC in comparison to Centers for Disease Control opioid prescription guidelines. METHODS: Literature search was conducted using CINAHL, PubMed, the Cochrane Library, Web of Science and hand search. Data were analyzed from 1999 to 2018. Randomized trials, observational, and case studies involved hospitalized adults with SCD who were prescribed opioids to treat VOC. Quality assessment was conducted using Downs and Black checklist. Meta-analysis was not conducted. RESULTS: Five studies were conducted in the USA, Arabia and the Netherlands, and the USA and Canada were included. Participants were treated with either morphine or morphine milligram equivalent (MME). No study used the same method of opioid administration. CONCLUSIONS: Patients with SCD who are hospitalized secondary to VOC mostly received opioids for pain well within the Centers for Disease Control and Prevention prescription guidelines. No uniform method exists. Additional research is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".