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Record W2241953676 · doi:10.1007/s40801-015-0048-z

Efficacy of Low-Dose Oral Liquid Morphine for Elderly Patients with Chronic Non-Cancer Pain: Retrospective Chart Review

2015· article· en· W2241953676 on OpenAlexaffabout
Joyce Lee, S. Fatima Lakha, Angela Mailis

Bibliographic record

VenueDrugs - Real World Outcomes · 2015
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsMedicineDosingChronic painOpioidMorphineRetrospective cohort studyRating scaleDemographicsCancerPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The use of medications among older persons can often be challenging as physiological changes may affect metabolism and cognitive abilities. Several studies show that the elderly with chronic pain are seriously undertreated or inappropriately treated, particularly with respect to opioids. OBJECTIVE: To determine whether very low doses of oral liquid morphine (LM) in patients over 65 years of age with chronic non-cancer pain provides meaningful pain improvement. METHODS: A retrospective chart review was conducted for ten carefully selected older patients seen at a tertiary care pain clinic in Toronto Ontario (2009-2011) with serious biomedical painful conditions and intolerance to other opioid analgesics. Data collected included demographics, LM dosing, diagnosis and average Numeric Rating Scale (NRS) pain ratings pre- and post-administration of LM. RESULTS: Of the ten eligible patients, the female/male ratio was 4:1, mean age 75.5 years and mean pain duration 7.9 years. The initial dose of LM for all patients was 1-3 mg three times/day and the maintenance dose ranged from 5 to 30 mg/day. Overall, pain ratings dropped from 6.35 to 2.95 (3.4 point drop on the NRS score) with a mean follow-up of 14 months (range 10-21). CONCLUSION: The case series showed that carefully selected elderly patients with biomedical pathology can benefit from very low doses of LM. Future larger and well-designed studies need to focus on the use of LM for elderly patients.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.306
Teacher spread0.288 · 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 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

Citations9
Published2015
Admission routes2
Has abstractyes

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