B‐type natriuretic peptide levels in preterm neonates with bronchopulmonary dysplasia: A marker of severity?

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109265/1/ppul22942.pd

Laboratory Markers Predictive of Fulminant \u3ci\u3eClostridioides difficile\u3c/i\u3e Infection Refractory to Fluid Resuscitation

Background Old age, leucocytosis, hypoalbuminemia, and elevated creatinine have been identified as risk factors for fulminant Clostridioides difficile infection (CDI). High ATLAS scores have also been linked to fatal disease. The affiliated studies, however, involved patients prescribed metronidazole - a regimen no longer standard of care. The variables were thus reassessed in patients prescribed optimal therapy. Methods Adults hospitalized with CDI at University of Kentucky Medical Center were retrospectively reviewed. Enrolled subjects were separated according to disease classification i.e. non-severe/severe versus fulminant CDI. Fulminant patients were further subdivided into hypotensive persons responsive to fluid resuscitation, and those with sequent shock, ileus, or megacolon. Following partition, the cohorts underwent correlation analysis. Findings Forty-five subjects had non-severe/severe disease. Thirteen fulminant CDI patients responded to fluid resuscitation. Seventeen fulminant CDI patients developed shock, ileus, or megacolon. Median WBC counts, albumin values, and ATLAS scores varied among the cohorts. Although WBC counts were similar among the fulminant subsets, declining albumin values and increasing ATLAS scores mirrored disease worsening. Logistic regression revealed albumin values \u3c 20 g/L (odds ratio [OR] 3.91) and ATLAS scores ≥ 6 (OR 5.03) to predict critical illness in hypotensive persons. Conclusion Median WBC counts, albumin values, and ATLAS scores differed in patients separated by CDI severity. A notable variance in albumin values and ATLAS scores between fluid responsive fulminant disease and critical illness was moreover seen. The finding suggests hypoalbuminemia and high ATLAS scores in hypotensive CDI patients may herald shock, ileus, or megacolon

Combining community wastewater genomic surveillance with state clinical surveillance: A framework for SARS-CoV-2 public health practice

Study objective: To garner a framework for combining community wastewater surveillance with state clinical surveillance that influence confirmation of SARS-CoV-2 variants within the community, and recommend how the flow of such research evidence could be expanded and employed for public health response. Design, setting, and participants: This work involved analyzing wastewater samples collected weekly from 17 geographically resolved locations in Louisville/Jefferson County, Kentucky from February 10 to November 29, 2021. Genomic surveillance and RT-qPCR platforms were used as screening to identify SARS-CoV-2 in wastewater, and state clinical surveillance was used for confirmation. Main results: The results demonstrate increased epidemiological value of combining community wastewater genomic surveillance and RT-qPCR with conventional case auditing methods. The spatial scale and temporal frequency of wastewater sampling provides promising sensitivity and specificity to be useful to gain public health screening insights about community emergence, seeding, and spread. Conclusions: Better national surveillance systems are needed for future pathogens and variants, and wastewater-based genomic surveillance represents opportune coupling. This paper presents current evidence that complementary wastewater and clinical testing is enhanced cost-effectively when linked; making a strong case for a joint public health framework. The findings suggest significant potential for rapid progress to be made in extending this work to consider pathogens of interest as a whole within wastewater, which could be examined in either a targeted fashion as we currently do with SARS-CoV-2 or in terms of a global monitoring of all pathogens found, and developing evidence based public health practice to best support community health

Quality assurance plan for a vaccine preventable diseases surveillance program

Public health surveillance programs for vaccine preventable diseases (VPD) need functional quality assurance (QA) in order to operate with high quality activities to prevent preventable communicable diseases from spreading in the community. Having a functional QA plan can assure the performance and quality of a program without putting excessive stress on the resources. A functional QA plan acts as a check on the quality of day-to-day activities performed by the VPD surveillance program while also providing data that would be useful for evaluating the program. This study developed a QA plan that involves collection, collation, analysis and reporting of information based on standardized (predetermined) formats and indicators as an integral part of routine work for the vaccine preventable disease surveillance program at the City of Houston Department of Health and Human Services. The QA plan also provides sampling and analysis plans for assessing various QA indicators, as well as recommendations to the Houston Department of Health and Humans Services for implementation of the QA plan. The QA plan developed for VPD surveillance in the City of Houston is intended to be a low cost system that could serve as a template for QA plans as part of other public health programs not only in the city or the nation, but could be adapted for use anywhere across the globe. Having a QA plan for VPD surveillance in the City of Houston would serve well for the funding agencies like the CDC by assuring that the resources are being expended efficiently, while achieving the real goal of positively impacting the health and lives of the recipient/target population

A novel approach to improve newborn screening for congenital hypothyroidism by integrating covariate-adjusted results of different tests into CLIR customized interpretive tools

Newborn screening for congenital hypothyroidism remains challenging decades after broad implementation worldwide. Testing protocols are not uniform in terms of targets (TSH and/or T4) and protocols (parallel vs. sequential testing; one or two specimen collection times), and specificity (with or without collection of a second specimen) is overall poor. The purpose of this retrospective study is to investigate the potential impact of multivariate pattern recognition software (CLIR) to improve the post-analytical interpretation of screening results. Seven programs contributed reference data (N = 1,970,536) and two sets of true (TP, N = 1369 combined) and false (FP, N = 15,201) positive cases for validation and verification purposes, respectively. Data were adjusted for age at collection, birth weight, and location using polynomial regression models of the fifth degree to create three-dimensional regression surfaces. Customized Single Condition Tools and Dual Scatter Plots were created using CLIR to optimize the differential diagnosis between TP and FP cases in the validation set. Verification testing correctly identified 446/454 (98%) of the TP cases, and could have prevented 1931/5447 (35%) of the FP cases, with variable impact among locations (range 4% to 50%). CLIR tools either as made here or preferably standardized to the recommended uniform screening panel could improve performance of newborn screening for congenital hypothyroidism

Genetic studies of body mass index yield new insights for obesity biology

Note: A full list of authors and affiliations appears at the end of the article. Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.</p