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Individuals with a mental health disorder appear to be at increased risk of medical illness. To examine rates of medical illnesses in patients with bipolar disorder (n = 1720) and to examine the clinical course of the bipolar illness according to lifetime medical illness burden. Participants recruited within the UK were asked about the lifetime occurrence of 20 medical illnesses, interviewed using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) and diagnosed according to DSM-IV criteria. We found significantly increased rates of several medical illnesses in our bipolar sample. A high medical illness burden was associated with a history of anxiety disorder, rapid cycling mood episodes, suicide attempts and mood episodes with a typically acute onset. Bipolar disorder is associated with high rates of medical illness. This comorbidity needs to be taken into account by services in order to improve outcomes for patients with bipolar disorder and also in research investigating the aetiology of affective disorder where shared biological pathways may play a role.

Pregnancy and childbirth are a period of high risk for women with bipolar disorder and involve difficult decisions particularly about continuing or stopping medications.AimsTo explore what clinical predictors may help to individualise the risk of perinatal recurrence in women with bipolar disorder. Information was gathered retrospectively by semi-structured interview, questionnaires and case-note review from 887 women with bipolar disorder who have had children. Clinical predictors were selected using backwards stepwise logistic regression, conditional permutation random forests and reinforcement learning trees. Previous perinatal history of affective psychosis or depression was the most significant predictor of a perinatal recurrence (odds ratio (OR) = 8.5, 95% CI 5.04-14.82 and OR = 3.6, 95% CI 2.55-5.07 respectively) but even parous women with bipolar disorder without a previous perinatal mood episode were at risk following a subsequent pregnancy, with 7% developing postpartum psychosis. Previous perinatal history of affective psychosis or depression is the most important predictor of perinatal recurrence in women with bipolar disorder and can be used to individualise risk assessments.Declaration of interestNone.

It is commonly – but wrongly – assumed that there are no importantdifferences between the clinical presentations of major depressive disorderand bipolar depression. Here we compare clinical course variables anddepressive symptom profiles in a large sample of individuals with majordepressive disorder (n=593) and bipolar disorder(n=443). Clinical characteristics associated with abipolar course included the presence of psychosis, diurnal mood variationand hypersomnia during depressive episodes, and a greater number of shorterdepressive episodes. Such features should alert a clinician to a possiblebipolar course. This is important because optimal management is not the samefor bipolar and unipolar depression.

It is commonly – but wrongly – assumed that there are no important differences between the clinical presentations of major depressive disorder and bipolar depression. Here we compare clinical course variables and depressive symptom profiles in a large sample of individuals with major depressive disorder (n=593) and bipolar disorder (n=443). Clinical characteristics associated with a bipolar course included the presence of psychosis, diurnal mood variation and hypersomnia during depressive episodes, and a greater number of shorter depressive episodes. Such features should alert a clinician to a possible bipolar course. This is important because optimal management is not the same for bipolar and unipolar depression.

Despite compelling evidence for a major genetic contribution to risk of bipolar mood disorder, conclusive evidence implicating specific genes or pathophysiological systems has proved elusive. In part this is likely to be related to the unknown validity of current phenotype definitions and consequent aetiological heterogeneity of samples. In the recent Wellcome Trust Case Control Consortium genome-wide association analysis of bipolar disorder (1868 cases, 2938 controls) one of the most strongly associated polymorphisms lay within the gene encoding the GABA A receptor β1 subunit, GABRB1 . Aiming to increase biological homogeneity, we sought the diagnostic subset that showed the strongest signal at this polymorphism and used this to test for independent evidence of association with other members of the GABA A receptor gene family. The index signal was significantly enriched in the 279 cases meeting Research Diagnostic Criteria for schizoaffective disorder, bipolar type ( P =3.8 × 10 −6 ). Independently, these cases showed strong evidence that variation in GABA A receptor genes influences risk for this phenotype (independent system-wide P =6.6 × 10 −5 ) with association signals also at GABRA4, GABRB3 , GABRA5 and GABRR1 . Our findings have the potential to inform understanding of presentation, pathogenesis and nosology of bipolar disorders. Our method of phenotype refinement may be useful in studies of other complex psychiatric and non-psychiatric disorders.

IntroductionCentral airway nitric oxide flux (J'awNO) and peripheral airway/alveolar nitric oxide concentration (CANO) during asthma exacerbation has not been investigated after correction for axial NO back-diffusion.MethodsAfter measuring exhaled NO (fraction of exhaled nitric oxide (FENO); ppb) at 50, 100, 150 and 200 ml/s, J'awNO (nl/s) and CANO (ppb) were calculated using the two-compartment model and corrected for axial NO back-diffusion. Fifteen (8 males), non-smoking, patients with moderate-to-severe treated (inhaled corticosteroid (ICS) and inhaled long-acting β2-agonist (LABA)) asthma, age 57±13 years (mean±SD), were studied at baseline, during exacerbation prior to oral corticosteroid, and during recovery after an 8 day tapering prednisone course. Based on earlier asthma studies without correction, it was hypothesised that with correction for NO axial back-diffusion, the incidence of abnormal J'awNO and CANO at baseline and after exacerbation would be ≥30% in 15 patients with asthma with 80% power.ResultsAt baseline when clinically stable, after 180 μg of albuterol, forced expiratory volume in 1 s (FEV1; litres) was 78±26% predicted (p=0.009) with increased FENO at 50 ml/s (p=0.01) and J'awNO (p=0.02), but CANO was normal compared with the controls. During exacerbation FEV1 (litres) was 57±20% predicted (p=0.02), with increased FENO at 50 ml/s (p=0.01) and J'awNO (p=0.004), but CANO was normal. Recovery results were similar to baseline. Two of 15 patients with asthma always had normal exhaled NO gas exchange.ConclusionsThe central airways were the major site of abnormal NO flux in 13 of 15 patients with moderate–severe asthma when stable and during exacerbation and could be easily detected with abnormal FENO at 50 ml/s. CANO was normal.Clinical trial numberNCT00576069.

Background:Health care decisions are a critical determinant in the evolution of chronic illness. In shared decision-making (SDM), patients and clinicians work collaboratively to reach evidence-based health decisions that align with individual circumstances, values, and preferences. This personalized approach to clinical care likely has substantial benefits in the oversight of degenerative cervical myelopathy (DCM), a type of nontraumatic spinal cord injury. Its chronicity, heterogeneous clinical presentation, complex management, and variable disease course engenders an imperative for a patient-centric approach that accounts for each patient’s unique needs and priorities. Inadequate patient knowledge about the condition and an incomplete understanding of the critical decision points that arise during the course of care currently hinder the fruitful participation of health care providers and patients in SDM. This study protocol presents the rationale for deploying SDM for DCM and delineates the groundwork required to achieve this.Objective:The study’s primary outcome is the development of a comprehensive checklist to be implemented upon diagnosis that provides patients with essential information necessary to support their informed decision-making. This is known as a core information set (CIS). The secondary outcome is the creation of a detailed process map that provides a diagrammatic representation of the global care workflows and cognitive processes involved in DCM care. Characterizing the critical decision points along a patient’s journey will allow for an effective exploration of SDM tools for routine clinical practice to enhance patient-centered care and improve clinical outcomes.Methods:Both CISs and process maps are coproduced iteratively through a collaborative process involving the input and consensus of key stakeholders. This will be facilitated by Myelopathy.org, a global DCM charity, through its Research Objectives and Common Data Elements for Degenerative Cervical Myelopathy community. To develop the CIS, a 3-round, web-based Delphi process will be used, starting with a baseline list of information items derived from a recent scoping review of educational materials in DCM, patient interviews, and a qualitative survey of professionals. A priori criteria for achieving consensus are specified. The process map will be developed iteratively using semistructured interviews with patients and professionals and validated by key stakeholders.Results:Recruitment for the Delphi consensus study began in April 2023. The pilot-testing of process map interview participants started simultaneously, with the formulation of an initial baseline map underway.Conclusions:This protocol marks the first attempt to provide a starting point for investigating SDM in DCM. The primary work centers on developing an educational tool for use in diagnosis to enable enhanced onward decision-making. The wider objective is to aid stakeholders in developing SDM tools by identifying critical decision junctures in DCM care. Through these approaches, we aim to provide an exhaustive launchpad for formulating SDM tools in the wider DCM community.International Registered Report Identifier (IRRID):DERR1-10.2196/46809

This dissertation concerns the linguistic and reading profiles and predictors of English language learners (ELLs) classified as typically developing or at-risk for poor reading comprehension. The ELLs in the studies came from Chinese, Portuguese, and Spanish home language backgrounds, but had all begun formal schooling in English in kindergarten. An at-risk classification model based on performance on components of the simple view of reading (Gough & Tunmer, 1986), and using cut-off scores at the 30th percentile or below and the 40th percentile or above, was employed for identification of poor and good readers, respectively. ELLs (n = 127) were subtyped in grade 4 as either typically developing or at-risk based on their decoding and language comprehension skills in relation to the ELL sample (and not to monolingual norms). Reader subtypes used in the final analyses were: poor decoders (difficulties with word reading; n = 17), poor language comprehenders (language impaired; n = 15), multi-deficit at-risker (problems in decoding and language comprehension; n = 20), and typical developers (no deficits in decoding or language comprehension; n = 57). Study 1 compared the grade 4 profiles of the ELL reader subtypes on the following skills: word reading, reading fluency at the word- and text-levels, vocabulary, inferencing strategy, and reading comprehension. To validate the at-risk classification model, multivariate analysis of covariance (MANCOVA) results indicated that all three at-risk reader subtypes were experiencing significant problems with their reading comprehension in grade 4 when compared to typically developing ELLs. Different skill profiles were observed across the three at-risk reader groups in grade 4: poor decoders demonstrated difficulties with various aspects of word reading (accuracy and fluency), and inferencing strategy; poor language comprehenders demonstrated difficulties in word reading fluency; and multi-deficit at-riskers demonstrated pervasive difficulties with all the reading and language skills under study, including fluency and inferencing strategy. Study 2 identified longitudinal (from grade 2) linguistic and reading predictors of later at-risk ELL reader subtype in grade 4. Multinomial logistic regression models indicated that there were different predictors of later at-risk status across the reading groups: word reading fluency for poor decoders; receptive vocabulary for poor language comprehenders; and fluency and oral expression for multi-deficit at-riskers. Similar to the findings of previous research with poor reading ELLs (e.g., Geva & Herbert, 2012; Geva & Massey-Garrison, 2013; Li & Kirby, 2014), findings suggest that not all ELL readers with poor reading comprehension are the same; there are different sources of reading comprehension problems which point to different intervention foci. Furthermore, it appears that readers struggling with reading comprehension due to poor language can be successfully identified as early as grade 2, prior to the onset of their later difficulties in reading comprehension. Findings provide support for an enhanced simple view of reading that also includes fluency and inferencing strategy. Directions for future research and implications for practice are presented.