Assessing the uptake of incentivised physical health checks for people with serious mental illness: a cohort study in primary care.

BACKGROUND: People with serious mental illness are more likely to experience physical illnesses. The onset of many of these illnesses can be prevented if detected early. Physical health screening for people with serious mental illness is incentivised in primary care in England through the Quality and Outcomes Framework (QOF). GPs are paid to conduct annual physical health checks on patients with serious mental illness, including checks of body mass index (BMI), cholesterol, and alcohol consumption. AIM: To assess the impact of removing and reintroducing QOF financial incentives on uptake of three physical health checks (BMI, cholesterol, and alcohol consumption) for patients with serious mental illness. DESIGN AND SETTING: Cohort study using UK primary care data from the Clinical Practice Research Datalink between April 2011 and March 2020. METHOD: A difference-in-difference analysis was employed to compare differences in the uptake of physical health checks before and after the intervention, accounting for relevant observed and unobserved confounders. RESULTS: An immediate change was found in uptake after physical health checks were removed from, and after they were added back to, the QOF list. For BMI, cholesterol, and alcohol checks, the overall impact of removal was a reduction in uptake of 14.3, 6.8, and 11.9 percentage points, respectively. The reintroduction of BMI screening in the QOF increased the uptake by 10.2 percentage points. CONCLUSION: This analysis supports the hypothesis that QOF incentives lead to better uptake of physical health checks.

Measuring the overall performance of mental healthcare providers.

To date there have been no attempts to construct composite measures of healthcare provider performance which reflect preferences for health and non-health benefits, as well as costs. Health and non-health benefits matter to patients, healthcare providers and the general public. We develop a novel provider performance measurement framework that combines health gain, non-health benefit, and cost and illustrate it with an application to 54 English mental health providers. We apply estimates from a discrete choice experiment eliciting the UK general population's valuation of non-health benefits relative to health gains, to administrative and patient survey data for years 2013-2015 to calculate equivalent health benefit (eHB) for providers. We measure costs as forgone health and quantify the relative performance of providers in terms of equivalent net health benefit (eNHB): the value of the health and non-health benefits minus the forgone benefit equivalent of cost. We compare rankings of providers by eHB, eNHB, and by the rankings produced by the hospital sector regulator. We find that taking account of the non-health benefits in the eNHB measure makes a substantial difference to the evaluation of provider performance. Our study demonstrates that the provider performance evaluation space can be extended beyond measures of health gain and cost, and that this matters for comparison of providers.

Severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions among the UK Biobank cohort.

BACKGROUND: People with mental disorders have worse physical health compared with the general population, which could be attributable to receiving poorer quality healthcare. AIMS: To examine the relationship between severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions (ACSCs), and factors associated with increased risk. METHOD: Baseline data for England (N = 445 814) were taken from UK Biobank, which recruited participants aged 37-73 years during 2006-2010, and linked to hospital admission records up to 31 December 2019. Participants were grouped into those with a history of either schizophrenia, bipolar disorder, depression or anxiety, or no mental disorder. Survival analysis was used to assess the risk of hospital admission for ACSCs among those with mental disorders compared with those without, adjusting for factors in different domains (sociodemographic, socioeconomic, health and biomarkers, health-related behaviours, social isolation and psychological). RESULTS: People with schizophrenia had the highest (unadjusted) risk of hospital admission for ACSCs compared with those with no mental disorder (hazard ratio 4.40, 95% CI 4.04-4.80). People with bipolar disorder (hazard ratio 2.48, 95% CI 2.28-2.69) and depression or anxiety (hazard ratio 1.76, 95% CI 1.73-1.80) also had higher risk. Associations were more conservative when including all admissions, as opposed to first admissions only. The observed associations persisted after adjusting for a range of factors. CONCLUSIONS: People with severe mental disorders have the highest risk of preventable hospital admissions. Ensuring people with mental disorders receive adequate ambulatory care is essential to reduce the large health inequalities they experience.

The impact of COVID-19 on mental health service utilisation in England.

The COVID-19 pandemic has had a significant impact on population mental health and the need for mental health services in many countries, while also disrupting critical mental health services and capacity, as a response to the pandemic. Mental health providers were asked to reconfigure wards to accommodate patients with COVID-19, thereby reducing capacity to provide mental health services. This is likely to have widened the existing mismatch between demand and supply of mental health care in the English NHS. We quantify the impact of these rapid service reconfigurations on activity levels for mental health providers in England during the first thirteen months (March 2020-March 2021) of the COVID-19 pandemic. We use monthly mental health service utilisation data for a large subset of mental health providers in England from January 1, 2015 to March 31, 2021. We use multivariate regression to estimate the difference between observed and expected utilisation from the start of the pandemic in March 2020. Expected utilisation levels (i.e. the counterfactual) are estimated from trends in utilisation observed during the pre-pandemic period January 1, 2015 to February 31, 2020. We measure utilisation as the monthly number of inpatient admissions, discharges, net admissions (admissions less discharges), length of stay, bed days, number of occupied beds, patients with outpatient appointments, and total outpatient appointments. We also calculate the accumulated difference in utilisation from the start of the pandemic period. There was a sharp reduction in total inpatient admissions and net admissions at the beginning of the pandemic, followed by a return to pre-pandemic levels from September 2020. Shorter inpatient stays are observed over the whole period and bed days and occupied bed counts had not recovered to pre-pandemic levels by March 2021. There is also evidence of greater use of outpatient appointments, potentially as a substitute for inpatient care.

Association of environmental and socioeconomic indicators with serious mental illness diagnoses identified from general practitioner practice data in England: A spatial Bayesian modelling study.

BACKGROUND: The evidence is sparse regarding the associations between serious mental illnesses (SMIs) prevalence and environmental factors in adulthood as well as the geographic distribution and variability of these associations. In this study, we evaluated the association between availability and proximity of green and blue space with SMI prevalence in England as a whole and in its major conurbations (Greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle). METHODS AND FINDINGS: We carried out a retrospective analysis of routinely collected adult population (≥18 years) data at General Practitioner Practice (GPP) level. We used data from the Quality and Outcomes Framework (QOF) on the prevalence of a diagnosis of SMI (schizophrenia, bipolar affective disorder and other psychoses, and other patients on lithium therapy) at the level of GPP over the financial year April 2014 to March 2018. The number of GPPs included ranged between 7,492 (April 2017 to March 2018) to 7,997 (April 2014 to March 2015) and the number of patients ranged from 56,413,719 (April 2014 to March 2015) to 58,270,354 (April 2017 to March 2018). Data at GPP level were converted to the geographic hierarchy unit Lower Layer Super Output Area (LSOA) level for analysis. LSOAs are a geographic unit for reporting small area statistics and have an average population of around 1,500 people. We employed a Bayesian spatial regression model to explore the association of SMI prevalence in England and its major conurbations (greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle) with environmental characteristics (green and blue space, flood risk areas, and air and noise pollution) and socioeconomic characteristics (age, ethnicity, and index of multiple deprivation (IMD)). We incorporated spatial random effects in our modelling to account for variation at multiple scales. Across England, the environmental characteristics associated with higher SMI prevalence at LSOA level were distance to public green space with a lake (prevalence ratio [95% credible interval]): 1.002 [1.001 to 1.003]), annual mean concentration of PM2.5 (1.014 [1.01 to 1.019]), and closeness to roads with noise levels above 75 dB (0.993 [0.992 to 0.995]). Higher SMI prevalence was also associated with a higher percentage of people above 24 years old (1.002 [1.002 to 1.003]), a higher percentage of ethnic minorities (1.002 [1.001 to 1.002]), and more deprived areas. Mean SMI prevalence at LSOA level in major conurbations mirrored the national associations with a few exceptions. In Birmingham, higher average SMI prevalence at LSOA level was positively associated with proximity to an urban green space with a lake (0.992 [0.99 to 0.998]). In Liverpool and Manchester, lower SMI prevalence was positively associated with road traffic noise ≥75 dB (1.012 [1.003 to 1.022]). In Birmingham, Liverpool, and Manchester, there was a positive association of SMI prevalence with distance to flood zone 3 (land within flood zone 3 has ≥1% chance of flooding annually from rivers or ≥0.5% chance of flooding annually from the sea, when flood defences are ignored): Birmingham: 1.012 [1.000 to 1.023]; Liverpool and Manchester: 1.016 [1.006 to 1.026]. In contrast, in Leeds, there was a negative association between SMI prevalence and distance to flood zone 3 (0.959 [0.944 to 0.975]). A limitation of this study was because we used a cross-sectional approach, we are unable to make causal inferences about our findings or investigate the temporal relationship between outcome and risk factors. Another limitation was that individuals who are exclusively treated under specialist mental health care and not seen in primary care at all were not included in this analysis. CONCLUSIONS: Our study provides further evidence on the significance of socioeconomic associations in patterns of SMI but emphasises the additional importance of considering environmental characteristics alongside socioeconomic variables in understanding these patterns. In this study, we did not observe a significant association between green space and SMI prevalence, but we did identify an apparent association between green spaces with a lake and SMI prevalence. Deprivation, higher concentrations of air pollution, and higher proportion of ethnic minorities were associated with higher SMI prevalence, supporting a social-ecological approach to public health prevention. It also provides evidence of the significance of spatial analysis in revealing the importance of place and context in influencing area-based patterns of SMI.

Valuing quality in mental healthcare: A discrete choice experiment eliciting preferences from mental healthcare service users, mental healthcare professionals and the general population.

High and sustained healthcare quality is important worldwide, though health policy may prioritise the achievement of certain aspects of quality over others. This study determines the relative importance of different aspects of mental healthcare quality to different stakeholders by eliciting preferences in a UK sample using a discrete choice experiment (DCE). DCE attributes were generated using triangulation between policy documents and mental healthcare service user and mental healthcare professional views, whilst ensuring attributes were measurable using available data. Ten attributes were selected: waiting times; ease of access; person-centred care; co-ordinated approach; continuity; communication, capacity and resources; treated with dignity and respect; recovery focus; inappropriate discharge; quality of life (QoL). The DCE was conducted online (December 2018 to February 2019) with mental healthcare service users (n = 331), mental healthcare professionals (n = 510), and members of the general population (n = 1018). Respondents' choices were analysed using conditional logistic regression. Relative preferences for each attribute were generated using the marginal rate of substitution (MRS) with QoL as numeraire. Across all stakeholders, being treated with dignity and respect was of high importance. A coordinated approach was important across all stakeholders, whereas communication had higher relative importance for healthcare professionals and service users and ease of access had higher relative importance for the general population. This implies that policy could be affected by the choice of whose preferences (service users, healthcare professionals or general population) to use, since this impacts on the relative value and implied ranking of different aspects of mental healthcare quality.

The long-run effects of diagnosis related group payment on hospital lengths of stay in a publicly funded health care system: Evidence from 15 years of micro data.

Diagnosis Related Group (DRG) payment systems are a common means of paying for hospital services. They reward greater activity and therefore potentially encourage more rapid treatment. This paper uses 15 years of administrative data to examine the impact of a DRG system introduced in England on hospital lengths of stay. We utilize different econometric models, exploiting within and cross jurisdiction variation, to identify policy effects, finding that the reduction of lengths of stay was greater than previously estimated and grew over time. This constitutes new and important evidence of the ability of financing reform to generate substantial and persistent change in healthcare delivery.

The sensitivity of hospital coding to prices: evidence from Indonesia.

This study examines a newly introduced DRG system in Indonesia. We use secondary data for 2015 and 2017 from Jaminan Kesehatan Nasional (JKN), a patient level dataset for Indonesia created in 2014 to record public and private hospitals' claims to the national health insurance system to investigate whether there is an association between changes in tariffs paid and the severity of inpatient activity recorded in hospitals. We find a consistent small, positive and statistically significant correlation between changes in tariffs and changes in concentration of activity, indicating discretionary but limited coding behaviour by hospitals. The results indicate that reducing price differentials may mitigate discretionary coding, but that the benefits of this are limited and need to be compared to the potential risk of having to rebase all prices upwards.

Trends in and drivers of healthcare expenditure in the English NHS: a retrospective analysis.

BACKGROUND: In England, rises in healthcare expenditure consistently outpace growth in both GDP and total public expenditure. To ensure the National Health Service (NHS) remains financially sustainable, relevant data on healthcare expenditure are needed to inform decisions about which services should be delivered, by whom and in which settings. METHODS: We analyse routine data on NHS expenditure in England over 9 years (2008/09 to 2016/17). To quantify the relative contribution of the different care settings to overall healthcare expenditure, we analyse trends in 14 healthcare settings under three broad categories: Hospital Based Care (HBC), Diagnostics and Therapeutics (D&T) and Community Care (CC). We exclude primary care and community mental health services settings due to a lack of consistent data. We employ a set of indices to aggregate diverse outputs and to disentangle growth in healthcare expenditure that is driven by activity from that due to cost pressures. We identify potential drivers of the observed trends from published studies. RESULTS: Over the 9-year study period, combined NHS expenditure on HBC, D&T and CC rose by 50.2%. Expenditure on HBC rose by 54.1%, corresponding to increases in both activity (29.2%) and cost (15.7%). Rises in expenditure in inpatient (38.5%), outpatient (57.2%), and A&E (59.5%) settings were driven predominately by higher activity. Emergency admissions rose for both short-stay (45.6%) and long-stay cases (26.2%). There was a switch away from inpatient elective care (which fell by 5.1%) and towards day case care (34.8% rise), likely reflecting financial incentives for same-day discharges. Growth in expenditure on D&T (155.2%) was driven by rises in the volume of high cost drugs (270.5%) and chemotherapy (110.2%). Community prescribing grew by 45.2%, with costs falling by 24.4%. Evidence on the relationship between new technologies and healthcare expenditure is mixed, but the fall in drug costs could reflect low generic prices, and the use of health technology assessment or commercial arrangements to inform pricing of new medicines. CONCLUSIONS: Aggregate trends in HCE mask enormous variation across healthcare settings. Understanding variation in activity and cost across settings is an important initial step towards ensuring the long-term sustainability of the NHS.

Healthcare Costs for People with Serious Mental Illness in England: An Analysis of Costs Across Primary Care, Hospital Care, and Specialist Mental Healthcare.

BACKGROUND: Serious mental illness (SMI) is a set of disabling conditions associated with poor outcomes and high healthcare utilisation. However, little is known about patterns of utilisation and costs across sectors for people with SMI. OBJECTIVE: The aim was to develop a costing methodology and estimate annual healthcare costs for people with SMI in England across primary and secondary care settings. METHODS: A retrospective observational cohort study was conducted using linked administrative records from primary care, emergency departments, inpatient admissions, and community mental health services, covering financial years 2011/12-2013/14. Costs were calculated using bottom-up costing and are expressed in 2013/14 British pounds (GBP). Determinants of annual costs by sector were estimated using generalised linear models. RESULTS: Mean annual total healthcare costs for 13,846 adults with SMI were £4989 (median £1208), comprising 19% from primary care (£938, median £531), 34% from general hospital care (£1717, median £0), and 47% from inpatient and community-based specialist mental health services (£2334, median £0). Mean annual costs related specifically to mental health, as distinct from physical health, were £2576 (median £290). Key predictors of total cost included physical comorbidities, ethnicity, neighbourhood deprivation, SMI diagnostic subgroup, and age. Some associations varied across care context; for example, older age was associated with higher primary care and hospital costs, but lower mental healthcare costs. CONCLUSIONS: Annual healthcare costs for people with SMI vary significantly across clinical and socioeconomic characteristics and healthcare sectors. This analysis informs policy and research, including estimation of health budgets for particular patient profiles, and economic evaluation of health services and policies.

Can productivity growth measures identify best performing hospitals? Evidence from the English National Health Service.

Health-care systems around the world face limited financial resources, and England is no exception. The ability of the health-care system in England to operate within its financial resources depends in part on continually increasing its productivity. One means of achieving this is to identify and disseminate throughout the system the most efficient processes. We examine the annual productivity growth achieved by 151 hospitals over five financial years, using the same methods developed to measure productivity of the National Health Service as a whole. We consider whether there are hospitals that consistently achieve higher than average productivity growth. These could act as examples of good practice for others to follow and provide a means of increasing system performance. We find that the productivity growth of some hospitals over the whole period exhibits better than average performance, but there is little or no evidence of consistency in the performance of these hospitals over adjacent years. Even the best performers exhibit periods of very poor performance and vice versa. We therefore conclude that accepted methods of measuring productivity growth for the health system as a whole do not appear suitable for identifying good performance at the hospital level.

Prospective payment systems and discretionary coding-Evidence from English mental health providers.

Reimbursement of English mental health hospitals is moving away from block contracts and towards activity and outcome-based payments. Under the new model, patients are categorised into 20 groups with similar levels of need, called clusters, to which prices may be assigned prospectively. Clinicians, who make clustering decisions, have substantial discretion and can, in principle, directly influence the level of reimbursement the hospital receives. This may create incentives for upcoding. Clinicians are supported in their allocation decision by a clinical clustering algorithm, the Mental Health Clustering Tool, which provides an external reference against which clustering behaviour can be benchmarked. The aims of this study are to investigate the degree of mismatch between predicted and actual clustering and to test whether there are systematic differences amongst providers in their clustering behaviour. We use administrative data for all mental health patients in England who were clustered for the first time during the financial year 2014/15 and estimate multinomial multilevel models of over, under, or matching clustering. Results suggest that hospitals vary systematically in their probability of mismatch but this variation is not consistently associated with observed hospital characteristics.

Incidencia del derrame pleural en pacientes con enfermedad renal crónica estadio v en diálisis peritoneal intermitente atendidos en el Hospital Nacional Rosales del periodo comprendido 1 de junio del 2016 al 30 de junio del 2017 / Incidence of pleural effusion in patients with stage v chronic kidney disease on intermittent peritoneal dialysis treated at the Rosales National Hospital from June 1, 2016 to June 30, 2017

La Enfermedad Renal Crónica Terminal (ERCT) se ha convertido en un problema de Salud Pública, debido al número elevado de pacientes que son diagnosticados, día a día. Las complicaciones respiratorias, son comunes en los pacientes con ERCT, y pueden ser detectados hasta en el 70% de los casos, siendo el Derrame Pleural una de las más frecuentes. El objetivo del estudio fue determinar la incidencia de derrame pleural en los pacientes ERCT estadio V, que ingresaban por primera vez a diálisis peritoneal intermitente. Se realizó un estudio observacional, descriptivo, retrospectivo, longitudinal, de pacientes de nacionalidad salvadoreña, mayores de 12 años con diagnóstico de Enfermedad Renal Crónica Terminal de primera vez, en el período comprendido del 1 de Junio 2016 al 30 de Junio 2017, que recibieron tratamiento dialítico a través de catéter rígido y que desarrollaron Derrame Pleural; se determinó el perfil clínico, así como las características bioquímicas del líquido pleural. Se incluyeron 489 pacientes, 306 hombres (62.57%), y 183 mujeres (37.43%), con una edad media de 55.18 ± 13.78 años. 56 (11.5%) pacientes desarrollaron Derrame pleural, se realizó toracocentesis diagnóstica al 8.92%, de los cuales 60% era compatible con trasudado y 40 % con exudado (según criterios de Light). Los síntomas más frecuentes fueron: disnea y edema de miembros inferiores. Las comorbilidades concomitantes encontradas fueron HTA, Anemia y sobrecarga hidrica. Además niveles de albumina por debajo de 3.4 gr/dl se registraron en 68% de estos pacientes. Muchos de los pacientes en estudio presentaron múltiples comorbilidades, y desarrollaron derrame pleural en los primeros 3 meses de inicio de terapia dialítica, el hemitórax derecho fue el más afectado; en el perfil bioquímico predominó el trasudado. Los síntomas más frecuentemente presentados fueron: disnea (33%), seguido del edema de miembros inferiores (26%) y tos 20.5%. Los mayores de 50 años tuvieron más predisposición. La incidencia de derrame pleural en un año de seguimiento fue de 11.5%

Funding approaches for mental health services: Is there still a role for clustering?

Funding for mental health services in England faces many challenges including operating under financial constraints where it is not easy to demonstrate the link between activity and funding. Mental health services need to operate alongside and collaborate with acute hospital services where there is a well-established system for paying for activity. The funding landscape is shifting at a rapid pace and we outline the distinctions between the three main options - block contracts, episodic payment and capitation. Classification of treatment episodes via clustering presents an opportunity to demonstrate activity and reward it within these payment approaches. We have been engaged in research to assess how well the clustering system is performing against a number of fundamental criteria. Clusters need to be reliably recorded, to correspond to health needs, and to treatments that require roughly similar resources. We find that according to these criteria, clusters are falling short of providing a sound basis for measuring and financing services. Yet, we argue, it is the best available option and is essential for a more transparent funding approach for mental health to demonstrate its claim on resources, and that, as such, clusters should be a starting point for evolving a better funding system.

How do time trends in inhospital mortality compare? A retrospective study of England and Scotland over 17 years using administrative data.

OBJECTIVES: To examine the trends in inhospital mortality for England and Scotland over a 17-year period to determine whether and if so to what extent the time trends differ after controlling for differences in the patients treated. DESIGN: Analysis of retrospective administrative hospital data using descriptive aggregate statistics of trends in inhospital mortality and estimates of a logistic regression model of individual patient-level inhospital mortality accounting for patient characteristics, case-mix, and country-specific and year-specific intercepts. SETTING: Secondary care across all hospitals in England and Scotland from 1997 to 2013. POPULATION: Over 190 million inpatient admissions, either electively or emergency, in England or Scotland from 1997 to 2013. DATA: Hospital Episode Statistics for England and the Scottish Morbidity Record 01 for Scotland. MAIN OUTCOME MEASURES: Separately for two admission pathways (elective and emergency), we examine aggregate time trends of the proportion of patients who die in hospital and a binary variable indicating whether an individual patient died in hospital or survived, and how that indicator is influenced by the patient's characteristics, the year and the country (England or Scotland) in which they were admitted. RESULTS: Inhospital mortality has declined in both countries over the period studied, for both elective and emergency admissions, but has declined more in England than Scotland. The difference in trend reduction is greater for elective admissions. These differences persist after controlling for patient characteristics and case-mix. CONCLUSIONS: Comparing data at country level suggests questions about the roles performed by or functioning of their healthcare systems. We found substantial differences between Scotland and England in regard to the trend reductions in inhospital mortality. Hospital resources are therefore being deployed increasingly differently over time in these two countries for reasons that have yet to be explained.

Hospital Trusts productivity in the English NHS: Uncovering possible drivers of productivity variations.

BACKGROUND: Health care systems in OECD countries are increasingly facing economic challenges and funding pressures. These normally demand interventions (political, financial and organisational) aimed at improving the efficiency of the health system as a whole and its single components. In 2009, the English NHS Chief Executive, Sir David Nicholson, warned that a potential funding gap of £20 billion should be met by extensive efficiency savings by March 2015. Our study investigates possible drivers of differential Trust performance (productivity) for the financial years 2010/11-2012/13. METHODS: Following accounting practice, we define Productivity as the ratio of Outputs over Inputs. We analyse variation in both Total Factor and Labour Productivity using ordinary least squares regressions. We explicitly included in our analysis factors of differential performance highlighted in the Nicholson challenge as the sources were the efficiency savings should come from. Explanatory variables include efficiency in resource use measures, Trust and patient characteristics, and quality of care. RESULTS: We find that larger Trusts and Foundation Trusts are associated with lower productivity, as are those treating a greater proportion of both older and/or younger patients. Surprisingly treating more patients in their last year of life is associated with higher Labour Productivity.

Na3V2(PO4)3/C Nanorods with Improved Electrode-Electrolyte Interface As Cathode Material for Sodium-Ion Batteries.

Na3V2(PO4)3/C nanocomposites are synthesized by an oleic acid-based surfactant-assisted method. XRD patterns reveal high-purity samples, whereas Raman spectroscopy evidence the highly disordered character of the carbon phase. Electron micrographs show submicron agglomerates with a sea-urchin like morphology consisting of primary nanorods coated by a carbon phase. The electrode material was tested in half and full sodium cells. The electrochemical performance is clearly improved by this optimized morphology, particularly at high C rates. Thus, 76.6 mA h g(-1) was reached at 40C for Na3V2(PO4)3/C nanorods. In addition, 105.3 and 96.7 mA h g(-1) are kept after 100 cycles at rates as high as 5 and 10C. This exceptional Coulombic efficiency can be ascribed to the good mechanical stability and the low internal impedance at the electrode-electrolyte interphase.

Synthesis and electrochemical reaction with lithium of mesoporous iron oxalate nanoribbons.

Mesoporous FeC 2O 4 was prepared by dehydration of bulk monoclinic- and micellar orthorhombic FeC 2O 4.2H 2O precursors at 200 degrees C. The micellar material shows nanoribbon shaped particles, which are preserved after dehydration. These solids are used as high-capacity lithium storage materials with improved rate performance. The mesoporous nanoribbons exhibit higher capacities close to 700 mA h/g after 50 cycles at 2C (C = 1 Li h (-1) mol (-1)) rate between 0 and 2 V.

Specific CAPN10 gene haplotypes influence the clinical profile of polycystic ovary patients.

Recently, several research groups have evaluated CAPN10 gene in polycystic ovarian syndrome (PCOS) patients and other phenotypes, including hirsutism or intermediate phenotypes of PCOS. Molecular genetic analysis of CAPN10 gene indicates that different alleles may play a role in PCOS susceptibility and could be associated with idiopathic hirsutism. However, these observations are not exempt from controversy, because independent studies cannot replicate these preliminary findings. We present a haplotype-phenotype correlation study of CAPN10 haplotypes in 148 women showing ecographically detected polycystic ovaries (PCO) combined with one or more of these clinical symptoms: amenorrhea or severe oligomenorrhea, hyperandrogenism, and anovulatory infertility, as well as 93 unrelated controls. We have reconstructed and analyzed 482 CAPN10 haplotypes in patients and controls. We detected the association of UCSNP-44 allele with PCO phenotype in the Spanish population (P = 0.02). In addition, we identified several CAPN10 alleles associated to phenotypic differences observed between PCO patients, such as the presence of hypercholesterolemia (haplotype 1121, P = 0.005), presence of hyperandrogenic features (P = 0.05), and familial cancer incidence (haplotype 1111, P = 0.0005). Our results confirm the association of UCSNP-44 allele with PCO phenotype in the Spanish population. Moreover, we have identified novel candidate risk alleles and genotypes, within CAPN10 gene, that could be associated with important phenotypic and prognosis differences observed in PCOS patients.

Comment: CAPN10 alleles are associated with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is characterized by chronic anovulation infertility, hyperandrogenemia, and frequently insulin resistance. This study investigated whether polymorphisms in the CAPN10 gene are related with PCOS etiology. The allelic frequencies and genotypes of CAPN10 polymorphisms UCSNP-44, 43, 19, and 63 were determined in 55 well characterized women with polycystic ovaries and 93 unrelated healthy controls using spectrofluorimetric analyses and real-time PCR. Our data indicate that CAPN10 UCSNP-44 allele is associated with PCOS in the Spanish population (P = 0.01). These results support a role of Calpain 10 gene in PCOS susceptibility in humans.