scholarly journals Examination of the Use Survey and the Usefulness of Tramadol in Cancer Pain Patients

2016 ◽  
Vol 42 (2) ◽  
pp. 69-77
Author(s):  
Fumika Matsuoka ◽  
Aya Goto ◽  
Mio Takeuchi ◽  
Hiroshi Kato ◽  
Misato Ota ◽  
...  
Keyword(s):  
Cancer Pain ◽  
Pain Patients

679 Prevalence of Sleep Disturbances in Patients with Chronic Non-cancer Pain: A Systematic Review and Meta-Analysis

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A265-A266
Author(s):  
Yishi Sun ◽  
Isabelle Laksono ◽  
Janannii Selvanathan ◽  
Aparna Saripella ◽  
Mahesh Nagappa ◽  
...  
Keyword(s):  
Systematic Review ◽  
Chronic Pain ◽  
Sleep Quality ◽  
Cancer Pain ◽  
Sleep Disturbances ◽  
Meta Analysis ◽  
Pain Group ◽  
Pooled Prevalence ◽  
Chronic Pain Patients ◽  
Pain Patients

Abstract Introduction In individuals with chronic pain, sleep disturbances have been suggested to increase suffering, perception of pain, and to negatively affect long-term prognosis. This systematic review and meta-analysis aims to determine the pooled prevalence of sleep disturbances in chronic non-cancer pain patients with no other sleep disorders, using the patient-rated questionnaires Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI). Methods Multiple databases were searched for studies reporting the prevalence of sleep disturbances in chronic pain patients. Chronic pain was defined as pain >3 months. Comorbid sleep disorders such as sleep disordered breathing and restless leg syndrome were excluded. Sleep disturbances were defined using the PSQI cutoff of > 5 (poor sleep quality) and ISI ≥ 8 (subthreshold to clinical insomnia). The meta-analysis was conducted to examine the pooled prevalence of PSQI and ISI data using the inverse-variance random-effects model and to examine mean differences in PSQI scores. Results The systematic search resulted in 25,486 articles and 20 were included for analysis. In 12 studies using PSQI, the pooled prevalence of sleep disturbance was 75.3% among 3,597 chronic pain patients (mean age 53 ± 12 years; 74% female). In eight studies using ISI, the pooled prevalence was 72.9% among 2,578 chronic pain patients (mean age 63 ± 12 years; 57% female). The meta-analysis showed a significant mean difference of 2.75 (p < 0.001) in the global PSQI score between the chronic pain group versus the non-chronic pain group. The meta-analysis also showed a significant mean difference in the scores of four of seven PSQI components: sleep latency, sleep efficiency, sleep duration, and sleep disturbances (p < 0.05). Conclusion In chronic pain patients, the pooled prevalence of sleep disturbances as measured by PSQI (75.3%) and ISI (72.9%) studies was much higher than those reported for the general population. The relatively high prevalence of sleep disturbances in chronic pain patients emphasizes the importance of further characterizing the relationship between sleep and chronic pain. Support (if any):

Gabapentin enhances the antinociceptive effect of intrathecal morphine in refractory cancer pain patients

2021 ◽  
Author(s):  
Lei Teng ◽  
Junzhu Dai ◽  
Hongxue Shao ◽  
Liuyuan Zhao ◽  
Shiyan Lin ◽  
...  
Keyword(s):  
Cancer Pain ◽  
Intrathecal Morphine ◽  
Antinociceptive Effect ◽  
Pain Patients

A Pain Education Program for chronic cancer pain patients: follow-up results from a randomized controlled trial

Pain ◽  
1997 ◽  
Vol 73 (1) ◽  
pp. 55-69 ◽  
Author(s):  
Rianne de Wit ◽  
Frits van Dam ◽  
Linda Zandbelt ◽  
Anneke van Buuren ◽  
Karin van der Heijden ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Cancer Pain ◽  
Education Program ◽  
Controlled Trial ◽  
Pain Education ◽  
Randomized Controlled ◽  
Chronic Cancer Pain ◽  
Pain Patients

Identifying Prevalence of and Risk Factors for Abnormal Urine Drug Tests in Cancer Pain Patients

2020 ◽  
Author(s):  
Kelly E. Leap ◽  
Grant H. Chen ◽  
Jasme Lee ◽  
Kay See Tan ◽  
Vivek Malhotra
Keyword(s):  
Risk Factors ◽  
Cancer Pain ◽  
Urine Drug ◽  
Pain Patients

scholarly journals Prediction of opioid dose in cancer pain patients using genetic profiling: not yet an option with support vector machine learning

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Anne Estrup Olesen ◽  
Debbie Grønlund ◽  
Mikkel Gram ◽  
Frank Skorpen ◽  
Asbjørn Mohr Drewes ◽  
...  
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Cancer Pain ◽  
Support Vector ◽  
Genetic Profiling ◽  
Opioid Dose ◽  
Pain Patients

Symptoms and side effects in chronic non-cancer pain patients: clinical implications and development of new assessment tools

2015 ◽  
Vol 59 (8) ◽  
pp. 1060-1067
Author(s):  
T. S. Olsen ◽  
T. Jonsson ◽  
J. Højsted ◽  
P. Sjøgren ◽  
L. Christrup
Keyword(s):  
Side Effects ◽  
Cancer Pain ◽  
Assessment Tools ◽  
Clinical Implications ◽  
Pain Patients

scholarly journals Transdermal Fentanyl in Opioid-Naive Cancer Pain Patients

2000 ◽  
Vol 19 (3) ◽  
pp. 185-192 ◽  
Author(s):  
Ans P.E Vielvoye-Kerkmeer ◽  
Carlien Mattern ◽  
Martin P Uitendaal
Keyword(s):  
Cancer Pain ◽  
Transdermal Fentanyl ◽  
Pain Patients
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