Baseline depression severity, co-morbid anxiety, executive dysfunction, current episode duration, early improvement, physical illnesses and age were reported as statistically significant predictors of treatment outcomes. Only the first three were significant in meta-analyses. Subgroup analyses showed differences in predictor effect between biological and psychosocial treatment. However, high heterogeneity and small study numbers suggest a cautious interpretation of results. These predictors were associated with various mechanisms including brain pathophysiology, perceived social support and proposed distinct types of depressive disorder. Further investigation of the clinical utility of these predictors is suggested.

IntroductionAcute pain is a hallmark of sickle cell disease (SCD) for which frequent hospital admissions may be required, affecting the quality of life of patients.ObjectivesTo characterise the relationship between adult patient self-reported sickle cell pain, mood and quality of life during and after hospital admissions.DesignLongitudinal study across three time-points.SettingSecondary care, single specialist sickle cell centre.Participants510 adult patients with SCD admitted to hospital daycare or inpatient units.Outcome measuresSelf-assessments of pain, mood and health-related quality of life with health utility (measured on the EQ-5D) on admission, before discharge and at 1-week postdischarge.ResultsMood, general health and quality of life showed significant steady improvements with reduction of pain in patients with SCD on admission to hospital, before discharge and at 1-week follow-up (p<0.01). Health utility scores derived from the EQ-5D showed a negative association with pain in regression analysis over the three time-points.ConclusionExamining health-related quality of life and health utility in relation to pain during hospital admissions is valuable in terms of targeting appropriate psychological interventions within the context of a multidisciplinary approach to managing sickle cell pain. This has implications for healthcare costs.