Dynamic ploidy changes drive fluconazole resistance in human cryptococcal meningitis.

BACKGROUND: Cryptococcal meningitis (CM) causes an estimated 180,000 deaths annually, predominantly in sub-Saharan Africa, where most patients receive fluconazole (FLC) monotherapy. While relapse after FLC monotherapy with resistant strains is frequently observed, the mechanisms and impact of emergence of FLC resistance in human CM are poorly understood. Heteroresistance (HetR) - a resistant subpopulation within a susceptible strain - is a recently described phenomenon in Cryptococcus neoformans (Cn) and Cryptococcus gattii (Cg), the significance of which has not previously been studied in humans. METHODS: A cohort of 20 patients with HIV-associated CM in Tanzania was prospectively observed during therapy with either FLC monotherapy or in combination with flucytosine (5FC). Total and resistant subpopulations of Cryptococcus spp. were quantified directly from patient cerebrospinal fluid (CSF). Stored isolates underwent whole genome sequencing and phenotypic characterization. RESULTS: Heteroresistance was detectable in Cryptococcus spp. in the CSF of all patients at baseline (i.e., prior to initiation of therapy). During FLC monotherapy, the proportion of resistant colonies in the CSF increased during the first 2 weeks of treatment. In contrast, no resistant subpopulation was detectable in CSF by day 14 in those receiving a combination of FLC and 5FC. Genomic analysis revealed high rates of aneuploidy in heteroresistant colonies as well as in relapse isolates, with chromosome 1 (Chr1) disomy predominating. This is apparently due to the presence on Chr1 of ERG11, which is the FLC drug target, and AFR1, which encodes a drug efflux pump. In vitro efflux levels positively correlated with the level of heteroresistance. CONCLUSION: Our findings demonstrate for what we believe is the first time the presence and emergence of aneuploidy-driven FLC heteroresistance in human CM, association of efflux levels with heteroresistance, and the successful suppression of heteroresistance with 5FC/FLC combination therapy. FUNDING: This work was supported by the Wellcome Trust Strategic Award for Medical Mycology and Fungal Immunology 097377/Z/11/Z and the Daniel Turnberg Travel Fellowship

How is place of death from cancer changing and what affects it? Analysis of cancer registration and service data

We aimed to compare trends in place of cancer death with the growth of palliative care and nursing home services, and investigate demographic, disease-related and area influences on individual place of death, using registration data for 216404 patients with breast, lung, colorectal and prostate cancer and aggregate data on services in South East England. Between 1985 and 1994 there was a trend away from hospital death (67–44%), to home (17–30%) and hospice death (8–20%). After 1995, this partly reversed. By 2002, hospital death rose to 47%, home death dropped to 23%, hospice death remained stable and nursing home death rose from 3 to 8%. Numbers of palliative care services increased, but trends for hospice and nursing home deaths most clearly followed the beds available. Cancer diagnosis and treatment influenced individual place of death, but between 1998 and 2002, age and area of residence were associated with most variation. Older patients and those living in more deprived areas died more often in hospitals and less often at home. Despite more palliative care services the proportion of people dying at home has not increased. Variation by age, deprivation and area of residence is unlikely to reflect patient preference. More active surveillance and planning must support policies for choice in end of life care

Variation in the use of observation status evaluation in Massachusetts acute care hospitals, 2003–2006

Background Observation evaluation is an alternate pathway to inpatient admission following Emergency Department (ED) assessment. Aims We aimed to describe the variation in observation use and charges between acute care hospitals in Massachusetts from 2003 to 2006. Methods Retrospective pilot analysis of hospital administrative data. Patients discharged from a Massachusetts hospital between 2003 and 2006 after an observation visit or inpatient hospitalization for six emergency medical conditions, grouped by the Clinical Classification System (CCS), were included. Patients discharged with a primary obstetric condition were excluded. The primary outcome measure, “Observation Proportion ” (pOBS), was the use of observation evaluation relative to inpatient evaluation (pOBS = n Observation/(n Observation + n Inpatient). We calculated pOBS, descriptive statistics of use and charges by the hospital for each condition. Results From 2003 to 2006 the number of observation visits in Massachusetts increased 3.9 % [95 % confidence interval (CI) 3.8 % to 4.0%] from 128,825 to 133,859, while inpatient hospitalization increased 1.29 % (95 % CI 1.26 % to 1.31%) from 832,415 to 843,617. Nonspecific chest pain (CCS 102) was the most frequently observed condition with 85,843 (16.3 % of total) observation evaluations. Observation visits for nonspecific chest pain increased 43.5 % from 2003 to 2006. Relative observation utilization (pOBS) for nonspecific chest pain ranged from 25 % to 95% across hospitals. Wide variation in hospital use of observation and charges was seen for all six emergency medical conditions. Conclusions There was wide variation in use of observation across six common emergency conditions in Massachusetts in this pilot analysis. This variation may have a substantial impact on hospital resource utilization. Further investigation into the patient, provider and hospital-level characteristics that explain the variation in observation use could help improve hospital efficiency

Do pediatric hospitalizations have a unique geography?

BACKGROUND: In the U.S. small-area health services research studies are often based on the hospital service areas (HSAs) defined by the Dartmouth Atlas of Healthcare project. These areas are based on the geographic origins of Medicare Part A hospital patients, the great majority of whom are seniors. It is reasonable to question whether the geographic system so defined is appropriate for health services research for all ages, particularly for children, who have a very different system of healthcare financing and provision in the U.S. METHODS: This article assesses the need for a unique system of HSAs to support pediatric small-area analyses. It is a cross-sectional analysis of California hospital discharges for two age groups – non-newborns 0–17 years old, and seniors. The measure of interest was index of localization, which is the percentage of HSA residents hospitalized in their home HSA. Indices were computed separately for each age group, and index agreement was assessed for 219 of the state's HSAs. We examined the effect of local pediatric inpatient volume and pediatric inpatient resources on the divergence of the age group indices. We also created a new system of HSAs based solely on pediatric patient origins, and visually compared maps of the traditional and the new system. RESULTS: The mean localization index for pediatric discharges was 20 percentage points lower than for Medicare cases, indicating a poorer fit of the traditional geographic system for children. The volume of pediatric cases did not appear to be associated with the magnitude of index divergence between the two age groups. Pediatric medical and surgical case subgroups gave very similar results, and both groups differed substantially from seniors. Location of children's hospitals and local pediatric bed supply were associated with Medicare-pediatric divergence. There was little visual correspondence between the maps of traditional and pediatric-specific HSAs. CONCLUSION: Children and seniors have significantly different geographic patterns of hospitalization in California. Medicare-based HSAs may not be appropriate for all age groups and service types throughout the U.S

Reprint: Good laboratory practice: preventing introduction of bias at the bench

As a research community, we have failed to show that drugs, which show substantial efficacy in animal models of cerebral ischemia, can also improve outcome in human stroke. Accumulating evidence suggests this may be due, at least in part, to problems in the design, conduct, and reporting of animal experiments which create a systematic bias resulting in the overstatement of neuroprotective efficacy. Here, we set out a series of measures to reduce bias in the design, conduct and reporting of animal experiments modeling human stroke

Supplier-induced demand for psychiatric admissions in Northern New England

The development of hospital service areas (HSAs) using small area analysis has been useful in examining variation in medical and surgical care; however, the techniques of small area analysis are underdeveloped in understanding psychiatric admission rates. We sought to develop these techniques in order to understand the relationship between psychiatric bed supply and admission rates in Northern New England. Our primary hypotheses were that there would be substantial variation in psychiatric admission across geographic settings and that bed availability would be positively correlated with admission rates, reflecting a supplier-induced demand phenomenon. Our secondary hypothesis was that the construction of psychiatric HSAs (PHSAs) would yield more meaningful results than the use of existing general medical hospital service areas

Unusual exanthema combined with cerebral vasculitis in pneumococcal meningitis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Bacterial meningitis is a complex, rapidly progressive disease in which neurological injury is caused in part by the causative organism and in part by the host's own inflammatory responses.</p> <p>Case presentation</p> <p>We present the case of a two-year-old Greek girl with pneumococcal meningitis and an atypical curvilinear-like skin eruption, chronologically associated with cerebral vasculitis. A diffusion-weighted MRI scan showed lesions with restricted diffusion, reflecting local areas of immunologically mediated necrotizing vasculitis.</p> <p>Conclusions</p> <p>Atypical presentations of bacterial meningitis may occur, and they can be accompanied by serious unexpected complications.</p

Application of multiple statistical tests to enhance mass spectrometry-based biomarker discovery

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry-based biomarker discovery has long been hampered by the difficulty in reconciling lists of discriminatory peaks identified by different laboratories for the same diseases studied. We describe a multi-statistical analysis procedure that combines several independent computational methods. This approach capitalizes on the strengths of each to analyze the same high-resolution mass spectral data set to discover consensus differential mass peaks that should be robust biomarkers for distinguishing between disease states.</p> <p>Results</p> <p>The proposed methodology was applied to a pilot narcolepsy study using logistic regression, hierarchical clustering, t-test, and CART. Consensus, differential mass peaks with high predictive power were identified across three of the four statistical platforms. Based on the diagnostic accuracy measures investigated, the performance of the consensus-peak model was a compromise between logistic regression and CART, which produced better models than hierarchical clustering and t-test. However, consensus peaks confer a higher level of confidence in their ability to distinguish between disease states since they do not represent peaks that are a result of biases to a particular statistical algorithm. Instead, they were selected as differential across differing data distribution assumptions, demonstrating their true discriminatory potential.</p> <p>Conclusion</p> <p>The methodology described here is applicable to any high-resolution MALDI mass spectrometry-derived data set with minimal mass drift which is essential for peak-to-peak comparison studies. Four statistical approaches with differing data distribution assumptions were applied to the same raw data set to obtain consensus peaks that were found to be statistically differential between the two groups compared. These consensus peaks demonstrated high diagnostic accuracy when used to form a predictive model as evaluated by receiver operating characteristics curve analysis. They should demonstrate a higher discriminatory ability as they are not biased to a particular algorithm. Thus, they are prime candidates for downstream identification and validation efforts.</p