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Record W2924811243 · doi:10.6004/jnccn.2018.7118

QIM19-115: Barriers and Trends in Cancer Patients` Pain Management in Qatar: A Randomized Cohort Prospective Study

2019· article· en· W2924811243 on OpenAlexaboutno aff
Rehab Abdelwahab, Anas Hamad, Randa Al Okka, Mohd A. Wahid, Khalil Ullah Shibli, Wael Saleem, Ahmed El Geziry, Fathi Saleh, Kakil Ibrahim Rasul, Shereen Elazzazy

Bibliographic record

VenueJournal of the National Comprehensive Cancer Network · 2019
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancer painPharmacyCancerMcGill Pain QuestionnairePopulationPhysical therapyPatient satisfactionPain medicineFamily medicinePain assessmentPain controlDescriptive statisticsPain managementPsychiatryNursingInternal medicineSurgeryVisual analogue scale

Abstract

fetched live from OpenAlex

Background: Up to 70% of cancer patients experience pain during the course of illness (Fallon, Support Care Cancer 2008). Studies showed that 40%–50% of patients with cancer pain receive insufficient analgesia due to different factors. Physicians are facing different challenges to accurately assess pain which might affect drug selection and pain control (Beyeler et al, Support Care Cancer 2008; Salminen et al, Support Cancer Care 2008; Stewart, Ulster Med J 2014). In NCCCR, treating physicians may prescribe analgesics to their patients or refer them to the Pain Management Service (PMS) based on their evaluation or as requested by patients. This study explored the factors which might lead to undertreatment of cancer pain in Qatar. In addition, focused on cancer patients’ pain management satisfaction and PMS awareness. Objectives: To assess the existing PMS at NCCCR from patients' perspective. Methods: In this study, we evaluated patients’ pain management perception via a validated written (Arabic and English) questionnaire (SF-MPQ-2; available at https://eprovide.mapi-trust.org/instruments/short-form-mcgill-pain-questionnaire#DESCRIPTIVE_INFORMATION ; Gauthier et al, J Pain 2014) and a structured interview by outpatient pharmacists at a single point of time, to assess patients` awareness towards the PMS, if they are receiving pain medications or not, if they are experiencing any pain regardless on pain medications or not, pain severity, and patients’ level of satisfaction towards their medications. A sample of 400 patients was randomly selected amongst the total cancer population visiting NCCCR Pharmacy over a specific period of time. Participants were consented and interviewed. Results: 400 patients agreed to participate; the median age was 50. Male to female ratio was 3 to 7. Data showed that 61% (245/400) of participants were not aware of the existence of the PMS. Only 20% (78/400) were aware and followed by PMS, with a satisfaction rate of 76% (59/78). Although 69% (276/400) of the patients were on pain medications, only 70% (191/276) were satisfied with their current medications. However from the satisfied patients, 57% (109/191) rated their pain as 4–10 at the time of interview (ATI). In the 31% (124/400) that were not taking any pain medications; 77% (96/124) didn’t know about the PMS, and 44% (55/124) had 4–10 pain severity (ATI). Conclusion: These findings provide clear evidence that factors leading to undertreating of cancer pain in Qatar might be unawareness of the PMS existence, pain treatment by unspecialized physicians, and patients’ reluctance to express their pain. Thus, raising patients’ awareness and standardizing the referral criteria can improve pain control and quality of life amongst cancer 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 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)0.001
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 score0.064
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.303
Teacher spread0.289 · 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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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