Medication quantification scores and evaluation of patient pharmacology profiles

Stormo, Karla J.; Kee, William G.; Steedham, Susan; Middaugh, Susan J.

doi:10.1007/s11916-998-0015-4

Cited by 11 publications

(7 citation statements)

References 8 publications

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“…The patients preoperative pain medication (type and dosage) was noted and the Medication Quantification Score, which is a reliable and validated score for quantifying analgesics, was calculated in order to obtain a comparable metric for different analgesic classes [ 11 ]. It was calculated for each non-opioid and opioid based on weights assigned by medication class and dosage level (level 1 = sub-therapeutic dosage and/or on demand, level 2 = <50% of the daily dosage, level 3 >50% of the daily dosage, level 4 = over dosage) using the 1998 detriment weights [ 12 ]. These scores were summed to provide a quantitative index for analgesic usage suitable for statistical analysis.…”

Section: Methodsmentioning

confidence: 99%

The cortical responses to evoked clinical pain in patients with hip osteoarthritis

et al. 2017

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BackgroundExperimental models have been used extensively to evaluate pain using e.g., visual analogue scales or electroencephalography (EEG). Stimulation using tonic pain has been shown to better mimic the unpleasantness of chronic pain, but has mainly been evoked by non-clinical stimuli. This study aims to, evaluate the EEG during clinical pain in patients scheduled for total hip replacement with control and resting conditions.MethodsThe hip scheduled for replacement was moved by the examiner to evoke pain for 30 seconds while recording EEG. The control condition entailed movement of the opposite hip in a similar fashion and holding it for 30 seconds. In addition, EEG was recorded during the resting condition with open eyes. The relative spectral content was calculated from the EEG as well as functional connectivity using phase-lag index for frequency bands delta (1–4Hz), theta (4–8Hz), alpha (8–12Hz) and beta (12–32Hz). A mixed model was used for statistical comparison between the three recording conditions.ResultsSpectral content differed between conditions in all bands. Functional connectivity differed in delta and theta frequency bands. Post-hoc analysis revealed differences between the painful and control condition in delta, theta and beta for spectral content. Pain during the hip rotation was correlated to the theta (r = -0.24 P = 0.03) and beta (r = 0.25 P = 0.02) content in the EEG.ConclusionEEG differences during hip movements in the affected and unaffected hip appeared in the spectral beta and theta content. This was correlated to the reported pain perceived, pointing towards pain specific brain activity related to clinical pain.

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Section: Methodsmentioning

confidence: 99%

The cortical responses to evoked clinical pain in patients with hip osteoarthritis

et al. 2017

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“…It was originally developed for pain patient trials and has sound validity and reliability. 51 The MQS scores are derived on the basis of weights assigned to each type of medication and the actual dosage levels used. For example, a prn nonsteroidal anti-inflammatory medication is assigned a predetermined detrimental weight which is multiplied by dosage weights and then summed across days monitored.…”

Section: Medication Quantification Scalementioning

confidence: 99%

Cognitive Behavioral Insomnia Therapy for Those With Insomnia and Depression: A Randomized Controlled Clinical Trial

Carney

Edinger

Kuchibhatla

et al. 2017

Sleep

153

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Study Objective: To compare cognitive behavioral therapy for insomnia (CBT-I) + antidepressant medication (AD) against treatments that target solely depression or solely insomnia. Design: A blinded, randomized split-plot experimental study. Setting: Two urban academic clinical centers. Participants: 107 participants (68% female, mean age 42 ± 11) with major depressive disorder and insomnia. Interventions: Randomization was to one of three groups: antidepressant (AD; escitalopram) + CBT-I (4 sessions), CBT-I + placebo pill, or AD + 4-session sleep hygiene control (SH). Measurements and Results: Subjective sleep was assessed via 2 weeks of daily sleep diaries (use of medication was covaried in all analyses); although there were no statistically significant group differences detected, all groups improved from baseline to posttreatment on subjective sleep efficiency (SE) and total wake time (TWT) and the effect sizes were large. Objective sleep was assessed via overnight polysomnographic monitoring at baseline and posttreatment; analyses revealed both CBT groups improved on TWT (p = .03), but the AD + SH group worsened. There was no statistically significant effect for PSG SE (p = .07). There was a between groups medium effect observed for the AD + SH and CBT + placebo group differences on diary TWT and both PSG variables. All groups improved significantly from baseline to posttreatment on the Hamilton Rating Scale for Depression (HAMD-17); the groups did not differ. Conclusions: Although all groups self-reported sleeping better after treatment, only the CBT-I groups improved on objective sleep, and AD + SH's sleep worsened. This suggests that we should be treating sleep in those with depression with an effective insomnia treatment and relying on self-report obscures sleep worsening effects. All groups improved on depression, even a group with absolutely no depression-focused treatment component (CBT-I + placebo). The depression effect in CBT-I only group has been reported in other studies, suggesting that we should further investigate the antidepressant properties of CBT-I.

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“…It enables characterization of analgesics when many analgesics are involved and doses are irregular, as is the case for the patient group in this study. It was calculated for each non-opioid and opioid based on weights assigned by medication class and dosage level (level 1 = sub-therapeutic dosage and/or on demand, level 2 = lower 50% of the therapeutic dose range, level 3 = upper 50% of the therapeutic dose range, level 4 = supra-therapeutic dose) using the 1998 detriment weights (Stormo et al, 1998). The detriment weights are summed by the dosage level to provide the final score.…”

Section: Perioperative Pain Managementmentioning

confidence: 99%

Prediction of postoperative opioid analgesia using clinical‐experimental parameters and electroencephalography

Gram

Erlenwein

Petzke

et al. 2016

European Journal of Pain

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Medication quantification scores and evaluation of patient pharmacology profiles

Cited by 11 publications

References 8 publications

The cortical responses to evoked clinical pain in patients with hip osteoarthritis

The cortical responses to evoked clinical pain in patients with hip osteoarthritis

Cognitive Behavioral Insomnia Therapy for Those With Insomnia and Depression: A Randomized Controlled Clinical Trial

Prediction of postoperative opioid analgesia using clinical‐experimental parameters and electroencephalography

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