A Prognostic Model for Critically Ill Children in Locations With Emerging Critical Care Capacity.

OBJECTIVES: To develop a clinical prediction model to risk stratify children admitted to PICUs in locations with limited resources, and compare performance of the model to nine existing pediatric severity scores. DESIGN: Retrospective, single-center, cohort study. SETTING: PICU of a pediatric hospital in Siem Reap, northern Cambodia. PATIENTS: Children between 28 days and 16 years old admitted nonelectively to the PICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Clinical and laboratory data recorded at the time of PICU admission were collected. The primary outcome was death during PICU admission. One thousand five hundred fifty consecutive nonelective PICU admissions were included, of which 97 died (6.3%). Most existing severity scores achieved comparable discrimination (area under the receiver operating characteristic curves [AUCs], 0.71-0.76) but only three scores demonstrated moderate diagnostic utility for triaging admissions into high- and low-risk groups (positive likelihood ratios [PLRs], 2.65-2.97 and negative likelihood ratios [NLRs], 0.40-0.46). The newly derived model outperformed all existing severity scores (AUC, 0.84; 95% CI, 0.80-0.88; p < 0.001). Using one particular threshold, the model classified 13.0% of admissions as high risk, among which probability of mortality was almost ten-fold greater than admissions triaged as low-risk (PLR, 5.75; 95% CI, 4.57-7.23 and NLR, 0.47; 95% CI, 0.37-0.59). Decision curve analyses indicated that the model would be superior to all existing severity scores and could provide utility across the range of clinically plausible decision thresholds. CONCLUSIONS: Existing pediatric severity scores have limited potential as risk stratification tools in resource-constrained PICUs. If validated, our prediction model would be a readily implementable mechanism to support triage of critically ill children at admission to PICU and could provide value across a variety of contexts where resource prioritization is important.

Saving babies' lives (SBL) - a programme to reduce neonatal mortality in rural Cambodia: study protocol for a stepped-wedge cluster-randomised trial.

BACKGROUND: Neonatal mortality remains unacceptably high. Many studies successful at reducing neonatal mortality have failed to realise similar gains at scale. Effective implementation and scale-up of interventions designed to tackle neonatal mortality is a global health priority. Multifaceted programmes targeting the continuum of neonatal care, with sustainability and scalability built into the design, can provide practical insights to solve this challenge. Cambodia has amongst the highest neonatal mortality rates in South-East Asia, with rural areas particularly affected. The primary objective of this study is the design, implementation, and assessment of the Saving Babies' Lives programme, a package of interventions designed to reduce neonatal mortality in rural Cambodia. METHODS: This study is a five-year stepped-wedge cluster-randomised trial conducted in a rural Cambodian province with an estimated annual delivery rate of 6615. The study is designed to implement and evaluate the Saving Babies' Lives programme, which is the intervention. The Saving Babies' Lives programme is an iterative package of neonatal interventions spanning the continuum of care and integrating into the existing health system. The Saving Babies' Lives programme comprises two major components: participatory learning and action with community health workers, and capacity building of primary care facilities involving facility-based mentorship. Standard government service continues in control arms. Data collection covering the whole study area includes surveillance of all pregnancies, verbal and social autopsies, and quality of care surveys. Mixed methods data collection supports iteration of the complex intervention, and facilitates impact, outcome, process and economic evaluation. DISCUSSION: Our study uses a robust study design to evaluate and develop a holistic, innovative, contextually relevant and sustainable programme that can be scaled-up to reduce neonatal mortality. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04663620 . Registered on 11th December 2020, retrospectively registered.

Leg edema quantification for heart failure patients via 3D imaging.

Heart failure is a common cardiac disease in elderly patients. After discharge, approximately 50% of all patients are readmitted to a hospital within six months. Recent studies show that home monitoring of heart failure patients can reduce the number of readmissions. Still, a large number of false positive alarms as well as underdiagnoses in other cases require more accurate alarm generation algorithms. New low-cost sensors for leg edema detection could be the missing link to help home monitoring to its breakthrough. We evaluated a 3D camera-based measurement setup in order to geometrically detect and quantify leg edemas. 3D images of legs were taken and geometric parameters were extracted semi-automatically from the images. Intra-subject variability for five healthy subjects was evaluated. Thereafter, correlation of 3D parameters with body weight and leg circumference was assessed during a clinical study at the Medical University of Graz. Strong correlation was found in between both reference values and instep height, while correlation in between curvature of the lower leg and references was very low. We conclude that 3D imaging might be a useful and cost-effective extension of home monitoring for heart failure patients, though further (prospective) studies are needed.

Quality evaluation, fatty acid analysis and untargeted profiling of volatiles in Cambodian rice.

This study provides the first investigation of the physical traits, pasting properties and volatile compounds of Cambodian rice cultivars, including traditional, improved, and improved traditional varieties, allowing for their differentiation as high and low quality rice. Analysis of the grain quality traits illustrates interesting features of traditional varieties and correlations between traits that assist with understanding texture. Untargeted profiling of volatile compounds shows that high quality fragrant varieties not only contain 2-acetyl-1-pyrroline but also several other compounds, including aldehydes, alcohols and 2-alkylfurans that contribute to overall aroma. Moreover, low odour threshold volatile compounds, which can be derived from the oxidation of unsaturated fatty acids, were more abundant in the fragrant varieties. The percentage area of both oleic and linoleic acid were found to be significantly different among the rice varieties tested. Such findings suggest that unsaturated fatty acids in milled rice contribute to rice fragrance, and thereby to overall quality.

Delving deeper into technological innovations to understand differences in rice quality.

Increasing demand for better quality rice varieties, which are also more suited to growth under sub-optimal cultivation conditions, is driving innovation in rice research. Here we have used a multi-disciplinary approach, involving SNP-based genotyping together with phenotyping based on yield analysis, metabolomic analysis of grain volatiles, and sensory panel analysis to determine differences between two contrasting rice varieties, Apo and IR64. Plants were grown under standard and drought-induced conditions. Results revealed important differences between the volatile profiles of the two rice varieties and we relate these differences to those perceived by the sensory panel. Apo, which is the more drought tolerant variety, was less affected by the drought condition concerning both sensory profile and yield; IR64, which has higher quality but is drought sensitive, showed greater differences in these characteristics in response to the two growth conditions. Metabolomics analyses using GCxGC-MS, followed by multivariate statistical analyses of the data, revealed a number of discriminatory compounds between the varieties, but also effects of the difference in cultivation conditions. Results indicate the complexity of rice volatile profile, even of non-aromatic varieties, and how metabolomics can be used to help link changes in aroma profile with the sensory phenotype. Our outcomes also suggest valuable multi-disciplinary approaches which can be used to help define the aroma profile in rice, and its underlying genetic background, in order to support breeders in the generation of improved rice varieties combining high yield with high quality, and tolerance of both these traits to climate change.