No abstract

BackgroundWe have previously demonstrated that routinely collected primary care data can be used to identify potential participants for trials in depression [1]. Here we demonstrate how patients with psychotic disorders can be identified from primary care records for potential inclusion in a cohort study. We discuss the strengths and limitations of this approach; assess its potential value and report challenges encountered.MethodsWe designed an algorithm with which we searched for patients with a lifetime diagnosis of psychotic disorders within the Secure Anonymised Information Linkage (SAIL) database of routinely collected health data. The algorithm was validated against the "gold standard" of a well established operational criteria checklist for psychotic and affective illness (OPCRIT). Case notes of 100 patients from a community mental health team (CMHT) in Swansea were studied of whom 80 had matched GP records.ResultsThe algorithm had favourable test characteristics, with a very good ability to detect patients with psychotic disorders (sensitivity > 0.7) and an excellent ability not to falsely identify patients with psychotic disorders (specificity > 0.9).ConclusionsWith certain limitations our algorithm can be used to search the general practice data and reliably identify patients with psychotic disorders. This may be useful in identifying candidates for potential inclusion in cohort studies.

Objectives Current options for treating emergent episodes of hypomania and mania in bipolar disorder are limited. Our objective was to compare the effectiveness and safety of add‐on melatonin in hypomania or mania over 3 weeks as a well‐tolerated therapy. Methods A randomized, double‐blind, parallel‐group, 3‐week comparison of modified release melatonin (n = 21) vs placebo (n = 20) in adult bipolar patients aged 18‐65 years. Permuted block randomization was used with participants and investigators masked to treatment allocation. Trial registration is ISRCTN28988273 and EUdraCT2008‐000281‐23. Approved by the South Central National Research Ethics Service (Oxford REC A) ref: 09/H0604/63. Results The trial was negative as there was no significant difference between melatonin and placebo on the primary outcome—mean Young Mania Rating Scale (YMRS) score at Day 21: (mean difference [MD] −1.77 ([95% CI: −6.39 to 2.85]; P = .447). Significantly fewer patients on melatonin scored 10 or more on the Altman Self Rating Mania Scale: (odds ratio [OR] 0.164 [95% CI: 0.0260‐1.0002]; P = .05). Quick Inventory of Depression Symptomatology Clinician Version‐16 (QIDS‐C16) scores were not significantly different. (OR 1.77 [95% CI: 0.43‐7.29]; P = .430). The proportion of patients scoring less than or equal to 5 on the self‐report QIDS‐SR16 at end‐point was greater for the melatonin group (OR 8.35 [95% CI: 1.04‐67.23]; P = .046). Conclusions In this small trial, melatonin did not effectively treat emerging hypomania or mania as there was no significant difference on the primary outcome. The sample size limitation and secondary outcomes suggest further investigation of melatonin treatment in mood episodes is indicated.

Social networking sites (SNS) are having an increasing influence on patients' lives and doctors are far from certain about how to deal with this new challenge. In our literature search, we could find no research on how doctors could engage positively with SNS to improve patient outcomes or create more patient-led care. We need to acknowledge the fact that a review of a patient's SNS page has the potential to enhance assessment and management, particularly where a corroborant history is hard to attain. As doctors, we need to think clearly about how to adapt our practice in light of this new form of communication; in particular, whether there is a case for engaging with SNS to improve patient care.