GP consultations for medically unexplained physical symptoms in parents and their children: a systematic review.

BACKGROUND: There is evidence of an association of medically unexplained physical symptoms (MUPS) between parents and children, but it is unclear whether this association is also present for GP consultations. AIM: To review the literature investigating the association of GP consultations for MUPS between parents and children. DESIGN OF STUDY: Systematic review. METHOD: Systematic search of MEDLINE(®), Embase, CINAHL, and PsycINFO databases from their inception to October 2012. Observational studies examining the association of GP consultations for MUPS between parents and children were included. RESULTS: Eight studies were included in the review. Three studies found significant associations between GP consultations for multiple MUPS between parents and children. Two studies reported significant associations between irritable bowel syndrome diagnosis in parents and multiple MUPS in children. One study showed no significant associations between multiple MUPS in mothers and functional abdominal pain in children. Two studies investigated the association of non-specific low back pain in parents and children; one study showed a significant association, whereas the other study found no significant association. Formal pooling of the results was not performed owing to a high degree of study heterogeneity. CONCLUSION: This review provides evidence of an association between GP consultations for MUPS in parents and children, although the evidence is limited by some potential biases and study heterogeneity. GPs need to be aware of this association, which has implications for management of children presenting with MUPS. More longitudinal research focusing on all common MUPS in children, which relies on more precise sources of data, is needed to further investigate this association.

Missing data and imputation: a practical illustration in a prognostic study on low back pain.

OBJECTIVE: When designing prediction models by complete case analysis (CCA), missing information in either baseline (predictors) or outcomes may lead to biased results. Multiple imputation (MI) has been shown to be suitable for obtaining unbiased results. This study provides researchers with an empirical illustration of the use of MI in a data set on low back pain, by comparing MI with the more commonly used CCA. Effects will be shown of imputing missing information on the composition and performance of prognostic models, distinguishing imputation of missing values in baseline characteristics and outcome data. METHODS: Data came from the Beliefs about Backpain cohort, a study of psychologic obstacles to recovery in primary care back pain patients in the United Kingdom. Candidate predictors included demographics, back pain characteristics, and psychologic variables. Complete case analysis was compared with MI within patients with complete outcome but missing baseline data (n=809) and patients with missing baseline or outcome data (n=1591). Multiple imputation was performed by a Multiple Imputation by Chained Equations procedure. RESULTS: Cases with missing outcome data (n=782, 49.1%) or with missing baseline data (n=116, 8%) both differed from complete cases regarding the distribution of some predictors and more often had a poor outcome. When comparing CCA with MI, model composition showed to be affected. CONCLUSIONS: Complete case analysis can give biased results, even when only small amounts of data are missing. Now that MI is available in standard statistical software, we recommend that it be used to handle missing data.

Relationship of opioid use and dosage levels to fractures in older chronic pain patients.

BACKGROUND: Opioids have been linked to increased risk of fractures, but little is known about how opioid dose affects fracture risk. OBJECTIVE: To assess whether risk of fracture increases with opioid dose among older patients initiating sustained use of opioids for chronic non-cancer pain. DESIGN: A cohort study that uses Cox proportional hazards models to compare fracture risk among current opioid users vs. persons no longer using opioids. PARTICIPANTS: Members of an integrated health care plan (N = 2,341) age 60 years and older who received 3+ opioid prescriptions within a 90-day period for chronic, non-cancer pain between 2000 and 2005. MEASUREMENTS: Time-varying measures of opioid use and average daily dose in morphine equivalents were calculated from automated data. Fractures were identified from automated data and then validated through medical record review. RESULTS: Compared with persons not currently using opioids, opioid use was associated with a trend towards increased fracture risk (1.28 (95% CI (0.99, 1.64 )). Higher dose opioid use (>or=50 mg/day) was associated with a 9.95% annual fracture rate and a twofold increase in fracture risk (2.00 (95% CI (1.24, 3.24)). Of the fractures in the study cohort, 34% were of the hip or pelvis, and 37% were associated with inpatient care. CONCLUSIONS: Higher doses (>or=50 mg/day) of opioids for chronic non-cancer pain were associated with a 2.00 increase in risk of fracture confirmed by medical record review. Clinicians should consider fracture risk when prescribing higher-dose opioid therapy for older adults.