Hypoglycemia in Non-Diabetic In-Patients: Clinical or Criminal?

BACKGROUND AND AIM: We wished to establish the frequency of unexpected hypoglycemia observed in non diabetic patients outside the intensive care unit and to determine if they have a plausible clinical explanation. METHODS: We analysed data for 2010 from three distinct sources to identify non diabetic hypoglycaemic patients: bedside and laboratory blood glucose measurements; medication records for those treatments (high-strength glucose solution and glucagon) commonly given to reverse hypoglycemia; and diagnostic codes for hypoglycemia. We excluded from the denominator admissions of patients with a diagnosis of diabetes or prescribed diabetic medication. Case notes of patients identified were reviewed. We used capture-recapture methods to establish the likely frequency of hypoglycemia in non-diabetic in-patients outside intensive care unit at different cut-off points for hypoglycemia. We also recorded co-morbidities that might have given rise to hypoglycemia. RESULTS: Among the 37,898 admissions, the triggers identified 71 hypoglycaemic episodes at a cut-off of 3.3 mmol/l. Estimated frequency at 3.3 mmol/l was 50(CI 33-93), at 3.0 mmol/l, 36(CI 24-64), at 2.7 mmol/l, 13(CI 11-19), at 2.5 mmol/l, 11(CI 9-15) and at 2.2 mmol/l, 8(CI 7-11) per 10,000 admissions. Admissions of patients aged above 65 years were approximately 50% more likely to have an episode of hypoglycemia. Most were associated with important co-morbidities. CONCLUSION: Significant non-diabetic hypoglycemia in hospital in-patients (at or below 2.7 mmol/l) outside critical care is rare. It is sufficiently rare for occurrences to merit case-note review and diagnostic blood tests, unless an obvious explanation is found

Prenatal Detection of Aneuploidy and Imbalanced Chromosomal Arrangements by Massively Parallel Sequencing

Fetal chromosomal abnormalities are the most common reasons for invasive prenatal testing. Currently, G-band karyotyping and several molecular genetic methods have been established for diagnosis of chromosomal abnormalities. Although these testing methods are highly reliable, the major limitation remains restricted resolutions or can only achieve limited coverage on the human genome at one time. The massively parallel sequencing (MPS) technologies which can reach single base pair resolution allows detection of genome-wide intragenic deletions and duplication challenging karyotyping and microarrays as the tool for prenatal diagnosis. Here we reported a novel and robust MPS-based method to detect aneuploidy and imbalanced chromosomal arrangements in amniotic fluid (AF) samples. We sequenced 62 AF samples on Illumina GAIIx platform and with averagely 0.01× whole genome sequencing data we detected 13 samples with numerical chromosomal abnormalities by z-test. With up to 2× whole genome sequencing data we were able to detect microdeletion/microduplication (ranged from 1.4 Mb to 37.3 Mb of 5 samples from chorionic villus sampling (CVS) using SeqSeq algorithm. Our work demonstrated MPS is a robust and accurate approach to detect aneuploidy and imbalanced chromosomal arrangements in prenatal samples

Chromosomal disorders:estimating baseline birth prevalence and pregnancy outcomes worldwide

Chromosomal disorders, of which Down syndrome is the most common, can cause multi-domain disability. In addition, compared to the general population, there is a higher frequency of death before the age of five. In many settings, large gaps in data availability have hampered policy-making, programme priorities and resource allocation for these important conditions. We have developed methods, which overcome this lack of data and allow estimation of the burden of affected pregnancies and their outcomes in different settings worldwide. For example, the methods include a simple equation relating the percentage of mothers 35 and over to Down syndrome birth prevalence. The results obtained provide a starting point for consideration of services that can be implemented for the care and prevention of these disorders

Differences in pregnancy outcomes in donor egg frozen embryo transfer (FET) cycles following preimplantation genetic screening (PGS): a single center retrospective study

PURPOSE: This study aims to test the hypothesis, in a single-center retrospective analysis, that live birth rates are significantly different when utilizing preimplantation genetic screening (PGS) compared to not utilizing PGS in frozen–thawed embryo transfers in our patients that use eggs from young, anonymous donors. The question therefore arises of whether PGS is an appropriate intervention for donor egg cycles. METHODS: Live birth rates per cycle and live birth rates per embryo transferred after 398 frozen embryo transfer (FET) cycles were examined from patients who elected to have PGS compared to those who did not. Blastocysts derived from donor eggs underwent trophectoderm biopsy and were tested for aneuploidy using array comparative genomic hybridization (aCGH) or next-generation sequencing (NGS), then vitrified for future use (test) or were vitrified untested (control). Embryos were subsequently warmed and transferred into a recipient or gestational carrier uterus. Data was analyzed separately for single embryo transfer (SET), double embryo transfer (DET), and for own recipient uterus and gestational carrier (GC) uterus recipients. RESULTS: Rates of implantation of embryos leading to a live birth were significantly higher in the PGS groups transferring two embryos (DET) compared to the no PGS group (GC, 72 vs. 56 %; own uterus, 60 vs. 36 %). The live birth implantation rate in the own uterus group for SET was higher in the PGS group compared to the control (58 vs. 36 %), and this almost reached significance but the live birth implantation rate for the SET GC group remained the same for both tested and untested embryos. Live births per cycle were nominally higher in the PGS GC DET and own uterus SET and DET groups compared to the non-PGS embryo transfers. These differences almost reached significance. The live birth rate per cycle in the SET GC group was almost identical. CONCLUSIONS: Significant differences were noted only for DET; however, benefits need to be balanced against risks associated with multiple pregnancies. Results observed for SET need to be confirmed on larger series and with randomized cohorts

Rhegmatogenous retinal detachment in Scotland: research design and methodology

<p>Abstract</p> <p>Background</p> <p>Rhegmatogenous retinal detachment (RRD) is a potentially blinding condition and a common cause of ocular morbidity. Establishing an accurate estimate of disease incidence and distribution is an important first step in assessing the healthcare burden related to this condition and in subsequent planning and provision of treatment strategies. The aim of this study is to obtain a first estimate incidence of RRD in Scotland, to estimate the incidence of familial RRD and to describe the known associations of RRD within the study population.</p> <p>Methods/Design</p> <p>We have established a national prospective observational study seeking to identify and recruit all incident cases of RRD in the Scottish population over a 2 year period. After fully informed consent, all participants will have a blood sample taken and a full medical history and clinical examination performed including visual acuity, refraction, slit-lamp examination, intra-ocular pressure measurement and detailed fundal examination. We describe the study design and protocol.</p> <p>Conclusion</p> <p>This study will provide the first estimate of the annual incidence of RRD in Scotland. The findings of this study will be important in estimating the burden of disease and in the planning of future health care policy related to this condition. This study will also establish a genetic resource for a genome wide association study to investigate if certain genetic variants predispose to RRD.</p

Inference of the infection status of individuals using longitudinal testing data from cryptic populations: Towards a probabilistic approach to diagnosis

Effective control of many diseases requires the accurate detection of infected individuals. Confidently ascertaining whether an individual is infected can be challenging when diagnostic tests are imperfect and when some individuals go for long periods of time without being observed or sampled. Here, we use a multi-event capture-recapture approach to model imperfect observations of true epidemiological states. We describe a method for interpreting potentially disparate results from individuals sampled multiple times over an extended period, using empirical data from a wild badger population naturally infected with Mycobacterium bovis as an example. We examine the effect of sex, capture history and current and historical diagnostic test results on the probability of being truly infected, given any combination of diagnostic test results. In doing so, we move diagnosis away from the traditional binary classification of apparently infected versus uninfected to a probability-based interpretation which is updated each time an individual is re-sampled. Our findings identified temporal variation in infection status and suggest that capture probability is influenced by year, season and infection status. This novel approach to combining ecological and epidemiological data may aid disease management decision-making by providing a framework for the integration of multiple diagnostic test data with other information