Role of hemogram-derived ratios in predicting intensive care unit admission in COVID-19 patients: a multicenter study.

Purpose: As hyperinflammation is recognized as a driver of severe COVID-19 disease, checking markers of inflammation is gaining more attention. Our study aimed to evaluate the utility of cost-effective hemogram-derived ratios in predicting intensive care unit (ICU) admission in COVID-19 patients. Methods: This multicenter retrospective study included hospitalized COVID-19 patients from four dedicated COVID-19 hospitals in Sylhet, Bangladesh. Data on demographics, clinical characteristics, laboratory parameters and survival outcomes were analyzed. Logistic regression analysis was used to identify the significance of each hemogram-derived ratio in predicting ICU admission. Results: Of 442 included patients, 98 (22.17%) required ICU admission. At the time of admission, patients requiring ICU had a higher neutrophil count and lower lymphocyte and platelet counts than patients not requiring ICU. Peripheral capillary oxygen saturation at admission was significantly lower in those who subsequently required ICU admission. Neutrophil-to-lymphocyte ratio, derived neutrophil-to-lymphocyte ratio, neutrophil-to-platelet ratio, and systemic immune-inflammation index were significant predictors of ICU admission. Conclusion: Hemogram-derived ratios can be an effective tool in facilitating the early categorization of at-risk patients, enabling timely measures to be taken early in the disease course.

Asthma in paediatric intensive care in England residents: observational study.

Despite high prevalence of asthma in children in the UK, there were no prior report on asthma admissions in paediatric intensive care units (PICU). We investigated the epidemiology and healthcare resource utilisation in children with asthma presenting to PICUs in England. PICANet, a UK national PICU database, was queried for asthma as the primary reason for admission, of children resident in England from April 2006 until March 2013. There were 2195 admissions to PICU for a median stay of 1.4 days. 59% were males and 51% aged 0-4 years. The fourth and fifth most deprived quintiles represented 61% (1329) admissions and 73% (11) of the 15 deaths. Deaths were most frequent in 10-14 years age (n = 11, 73%), with no deaths in less than 5 years age. 38% of admissions (828/2193) received invasive ventilation, which was more frequent with increasing deprivation (13% (108/828) in least deprived to 31% (260/828) in most deprived) and with decreasing age (0-4-year-olds: 49%, 409/828). This first multi-centre PICU study in England found that children from more deprived neighbourhoods represented the majority of asthma admissions, invasive ventilation and deaths in PICU. Children experiencing socioeconomic deprivation could benefit from enhanced asthma support in the community.

Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: a systematic review.

BACKGROUND: Statistical models are increasingly being used to estimate and project the prevalence and burden of asthma. Given substantial variations in these estimates, there is a need to critically assess the properties of these models and assess their transparency and reproducibility. We aimed to critically appraise the strengths, limitations and reproducibility of existing models for estimating and projecting the global, regional and national prevalence and burden of asthma. METHODS: We undertook a systematic review, which involved searching Medline, Embase, World Health Organization Library and Information Services (WHOLIS) and Web of Science from 1980 to 2017 for modelling studies. Two reviewers independently assessed the eligibility of studies for inclusion and then assessed their strengths, limitations and reproducibility using pre-defined quality criteria. Data were descriptively and narratively synthesised. RESULTS: We identified 108 eligible studies, which employed a total of 51 models: 42 models were used to derive national level estimates, two models for regional estimates, four models for global and regional estimates and three models for global, regional and national estimates. Ten models were used to estimate the prevalence of asthma, 27 models estimated the burden of asthma - including, health care service utilisation, disability-adjusted life years, mortality and direct and indirect costs of asthma - and 14 models estimated both the prevalence and burden of asthma. Logistic and linear regression models were most widely used for national estimates. Different versions of the DisMod-MR- Bayesian meta-regression models and Cause Of Death Ensemble model (CODEm) were predominantly used for global, regional and national estimates. Most models suffered from a number of methodological limitations - in particular, poor reporting, insufficient quality and lack of reproducibility. CONCLUSIONS: Whilst global, regional and national estimates of asthma prevalence and burden continue to inform health policy and investment decisions on asthma, most models used to derive these estimates lack the required reproducibility. There is a need for better-constructed models for estimating and projecting the prevalence and disease burden of asthma and a related need for better reporting of models, and making data and code available to facilitate replication.

Models for estimating and projecting global, regional and national prevalence and disease burden of asthma: protocol for a systematic review.

INTRODUCTION: Models that have so far been used to estimate and project the prevalence and disease burden of asthma are in most cases inadequately described and irreproducible. We aim systematically to describe and critique the existing models in relation to their strengths, limitations and reproducibility, and to determine the appropriate models for estimating and projecting the prevalence and disease burden of asthma. METHODS: We will search the following electronic databases to identify relevant literature published from 1980 to 2017: Medline, Embase, WHO Library and Information Services and Web of Science Core Collection. We will identify additional studies by searching the reference list of all the retrieved papers and contacting experts. We will include observational studies that used models for estimating and/or projecting prevalence and disease burden of asthma regarding human population of any age and sex. Two independent reviewers will assess the studies for inclusion and extract data from included papers. Data items will include authors' names, publication year, study aims, data source and time period, study population, asthma outcomes, study methodology, model type, model settings, study variables, methods of model derivation, methods of parameter estimation and/or projection, model fit information, key findings and identified research gaps. A detailed critical narrative synthesis of the models will be undertaken in relation to their strengths, limitations and reproducibility. A quality assessment checklist and scoring framework will be used to determine the appropriate models for estimating and projecting the prevalence anddiseaseburden of asthma. ETHICS AND DISSEMINATION: We will not collect any primary data for this review, and hence there is no need for formal National Health Services Research Ethics Committee approval. We will present our findings at scientific conferences and publish the findings in the peer-reviewed scientific journal.