The post-hemodialysis rebound: Predicting and quantifying its effect on Kt/V

The post-hemodialysis rebound: Predicting and quantifying its effect on Kt/V. Immediately after hemodialysis, the urea concentration rebounds upwards as urea continues to be transferred into the arterial circulation from peripheral body compartments. This rebound takes at least 30 minutes to complete. Hemodialysis is quantified as the Kt/V, calculated prom pre- and post-dialysis urea samples. Unless the post-dialysis sample is taken at least 30 minutes after dialysis, the Kt/V will be overestimated. This overestimation will be relatively greater in short high-efficiency dialyses, which have greater post-dialysis rebounds. We propose a method of correction that uses only the conventional pre- and immediate post-dialysis samples and is based on the physiologically-appropriate patient clearance time (tp). This is the time needed to clear all body compartments when the dialyzer clearance is infinite. The tp can be calculated from the pre-, immediate post- and 30-minute post-dialysis urea concentrations and was 35 minutes (SD 16) in 29 patients undergoing short (149 min) hemodiafiltration and standard (243 min) hemodialysis the following week. There was no significant difference between tp values calculated during the two treatments. Standard Kt/V can be corrected by multiplying by t/(t + tp) and dialysis time should be increased by tp × Kt/V minutes to compensate for the rebound. Despite individual variations in tp, a value of tp = 35 was sufficient to correct Kt/V in all patients. Kt/V corrected in this way agreed with Kt/V calculated using a 60-minute post-dialysis sample (r = 0.856, P < 0.001). The method predicted the 60-minute post-rebound concentration (SE 0.5mM, r = 0.983, P < 0.001) and the addition of 35 minutes to the treatment time corrected for the rebound in both conventional and short treatments. Similar simple equations corrected the error in V caused by rebound effects

Trends in multiplicity of Plasmodium falciparum infections among asymptomatic residents in the middle belt of Ghana.

BACKGROUND: Malaria is the most important cause of mortality and morbidity in children living in the Kintampo districts in the middle part of Ghana. This study has investigated the multiplicity of infection (MOI) within asymptomatic residents of the Kintampo districts, and the influence of age and seasonality on MOI, by studying the distribution of the polymorphic Plasmodium falciparum antigen merozoite surface protein 2 (MSP2). METHODS: DNA was extracted from an asymptomatic cohort of children and adults infected with P. falciparum during the period November 2003 to October 2004. Polymerase chain reaction was carried out and multiplicity of infection (MOI) was determined. RESULTS: Children under 10 years of age had an average MOI of 2.3 while adults 18 years and above had an average MOI of 1.4. Children below five years had high and low average MOIs of 2.8 in the March/April survey and 0.9 in the May/June survey respectively. A similar trend in the monthly distribution of MOI was observed for the entire cohort. IC/3D7 strains outnumbered the FC27 strains throughout the year by a ratio of about 4:1 with the difference between the prevalence of the two strains being least marked in the March/April survey, at the beginning of the rainy season. MOI was not linked to the level of malaria transmission as measured by the entomological inoculation rate. DISCUSSION/CONCLUSION: The impact of interventions, introduced since this baseline study was carried out on the parasite diversity of asymptomatic residents will be the subject of further investigations

Patterns and seasonality of malaria transmission in the forest-savannah transitional zones of Ghana

BACKGROUND: Knowledge of the local pattern of malaria transmission and the effect of season on transmission is essential for the planning and evaluation of malaria interventions. Therefore, entomological surveys were carried out in the forest-savannah transitional belt of Ghana (Kintampo) from November 2003 to November 2005 in preparation for drug and vaccine trials. RESULTS: A total of 23,406 mosquitoes were caught from 919 traps over the two-year period (November 2003 to November 2005): 54.3% were Culicines, 36.2% Anopheles funestus, and 9.4% Anopheles gambiae. Infection rates with Plasmodium falciparum were 4.7% and 1.5% for Anopheles gambiae and Anopheles funestus, respectively. Entomological inoculation rates (EIRs) were 269 infective bites per person per year in the first year (November 2003-October 2004) and 231 the following year (November 2004-November 2005). Polymerase Chain Reaction (PCR) analysis detected only Anopheles gambiae s.s. Nineteen mosquitoes were tested by PCR in the wet season; 16 were S-molecular form, 2 M-molecular form and 1 hybrid (S/M). In the dry season, sixteen mosquitoes were tested; 11 S-molecular form, 2 M-molecular form and 3 S/M hybrids. The frequency of knock down resistance (kdr) genotypes F(R) was 0.60. CONCLUSION: The dynamics and seasonal abundance of malaria vectors in the Kintampo area was influenced by micro-ecology, rainfall and temperature patterns. Transmission patterns did not differ significantly between the two years (2004 and 2005) and both Anopheles gambiae and Anopheles funestus were identified as effective vectors. EIR estimates in 2004/2005 were between 231 and 269 infective bites per person per year. The information provided by the study will help in planning intensified malaria control activities as well as evaluating the impact of malaria interventions in the middle belt of Ghana

Cognitive Remediation Works But How Should We Provide It? An Adaptive Randomized Controlled Trial of Delivery Methods Using a Patient Nominated Recovery Outcome in First-Episode Participants

BACKGROUND AND HYPOTHESIS: Cognitive remediation (CR) benefits cognition and functioning in psychosis but we do not know the optimal level of therapist contact, so we evaluated the potential benefits of different CR modes. STUDY DESIGN: A multi-arm, multi-center, single-blinded, adaptive trial of therapist-supported CR. Participants from 11 NHS early intervention psychosis services were independently randomized to Independent, Group, One-to-One, or Treatment-as-usual (TAU). The primary outcome was functional recovery (Goal Attainment Scale [GAS]) at 15-weeks post randomization. Independent and TAU arms were closed after an interim analysis, and three informative contrasts tested (Group vs One-to-One, Independent vs TAU, Group + One-to-One vs TAU). Health economic analyses considered the cost per Quality Adjusted Life Year (QALY). All analyses used intention-to-treat principles. STUDY RESULTS: We analyzed 377 participants (65 Independent, 134 Group, 112 One-to-One, 66 TAU). GAS did not differ for Group vs One-to-One: Cohen's d: 0.07, -0.25 to 0.40 95% CI, P = .655; Independent vs TAU: Cohen's d: 0.07, -0.41 to 0.55 95% CI, P = .777. GAS and the cognitive score improved for Group + One-to-One vs TAU favoring CR (GAS: Cohen's d: 0.57, 0.19-0.96 95% CI, P = .003; Cognitive score: Cohens d: 0.28, 0.07-0.48 95% CI, P = .008). The QALY costs were £4306 for Group vs TAU and £3170 for One-to-One vs TAU. Adverse events did not differ between treatment methods and no serious adverse events were related to treatment. CONCLUSIONS: Both active therapist methods provided cost-effective treatment benefiting functional recovery in early psychosis and should be adopted within services. Some individuals benefited more than others so needs further investigation. TRIAL REGISTRATION: ISRCTN14678860 https://doi.org/10.1186/ISRCTN14678860Now closed

Satisfaction with cognitive remediation therapy: its effects on implementation and outcomes using the cognitive remediation satisfaction scale

Cognitive Remediation (CR) improves cognition and functioning but is implemented in a variety of ways (independent, group and one-to-one). There is no information on whether service users find these implementation methods acceptable or if their satisfaction influences CR outcomes. We used mixed participatory methods, including focus groups, to co-develop a CR satisfaction scale. This was refined using three psychometric criteria (Cronbach's alpha, item discrimination, test-retest agreement) to select items. Factor analysis explored potential substructures. The refined measure was used in structural equation joint modelling to evaluate whether satisfaction with CR is affected by implementation method and treatment engagement or influences recovery outcome, using data from a randomised controlled trial. Four themes (therapy hours, therapist, treatment effects, computer use) generated a 31-item Cognitive Remediation Satisfaction scale (CRS) that reduced to 18 Likert items, 2 binary and 2 open-ended questions following psychometric assessment. CRS had good internal consistency (Alpha = 0.814), test-retest reliability (r= 0.763), and concurrent validity using the Working Alliance Inventory (r = 0.56). A 2-factor solution divided items into therapy engagement and therapy effects. Satisfaction was not related to implementation method but was significantly associated with CR engagement. Therapy hours were significantly associated with recovery, but there was no direct effect of satisfaction on outcome. Although satisfaction is important to therapy engagement, it has no direct effect on outcome. CR therapy hours directly affect outcome irrespective of which implementation model is used, so measuring satisfaction early might help to identify those who are likely to disengage. The study has mixed methods design

Satisfaction with cognitive remediation therapy:its effects on implementation and outcomes using the cognitive remediation satisfaction scale

Cognitive Remediation (CR) improves cognition and functioning but is implemented in a variety of ways (independent, group and one-to-one). There is no information on whether service users find these implementation methods acceptable or if their satisfaction influences CR outcomes. We used mixed participatory methods, including focus groups, to co-develop a CR satisfaction scale. This was refined using three psychometric criteria (Cronbach’s alpha, item discrimination, test-retest agreement) to select items. Factor analysis explored potential substructures. The refined measure was used in structural equation joint modelling to evaluate whether satisfaction with CR is affected by implementation method and treatment engagement or influences recovery outcome, using data from a randomised controlled trial. Four themes (therapy hours, therapist, treatment effects, computer use) generated a 31-item Cognitive Remediation Satisfaction scale (CRS) that reduced to 18 Likert items, 2 binary and 2 open-ended questions following psychometric assessment. CRS had good internal consistency (Alpha = 0.814), test-retest reliability (r= 0.763), and concurrent validity using the Working Alliance Inventory (r = 0.56). A 2-factor solution divided items into therapy engagement and therapy effects. Satisfaction was not related to implementation method but was significantly associated with CR engagement. Therapy hours were significantly associated with recovery, but there was no direct effect of satisfaction on outcome. Although satisfaction is important to therapy engagement, it has no direct effect on outcome. CR therapy hours directly affect outcome irrespective of which implementation model is used, so measuring satisfaction early might help to identify those who are likely to disengage. The study has mixed methods design

Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

Personality is influenced by genetic and environmental factors1 and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132–260,861). Of these genomewide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit– hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion–introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety)

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P &lt; 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P &lt; 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder