Reduced level of arousal and increased mortality in adult acute medical admissions: a systematic review and meta-analysis

Abstract Background Reduced level of arousal is commonly observed in medical admissions and may predict in-hospital mortality. Delirium and reduced level of arousal are closely related. We systematically reviewed and conducted a meta-analysis of studies in adult acute medical patients of the relationship between reduced level of arousal on admission and in-hospital mortality. Methods We conducted a systematic review (PROSPERO: CRD42016022048), searching MEDLINE and EMBASE. We included studies of adult patients admitted with acute medical illness with level of arousal assessed on admission and mortality rates reported. We performed meta-analysis using a random effects model. Results From 23,941 studies we included 21 with 14 included in the meta-analysis. Mean age range was 33.4 - 83.8 years. Studies considered unselected general medical admissions (8 studies, n=13,039) or specific medical conditions (13 studies, n=38,882). Methods of evaluating level of arousal varied. The prevalence of reduced level of arousal was 3.1%-76.9% (median 13.5%). Mortality rates were 1.7%-58% (median 15.9%). Reduced level of arousal was associated with higher in-hospital mortality (pooled OR 5.71; 95% CI 4.21-7.74; low quality evidence: high risk of bias, clinical heterogeneity and possible publication bias). Conclusions Reduced level of arousal on hospital admission may be a strong predictor of in-hospital mortality. Most evidence was of low quality. Reduced level of arousal is highly specific to delirium, better formal detection of hypoactive delirium and implementation of care pathways may improve outcomes. Future studies to assess the impact of interventions on in-hospital mortality should use validated assessments of both level of arousal and delirium

A digital dashboard for reporting mental, neurological and substance use disorders in Nairobi, Kenya: Implementing an open source data technology for improving data capture

The availability of quality and timely data for routine monitoring of mental, neurological and substance use (MNS) disorders is a challenge, particularly in Africa. We assessed the feasibility of using an open-source data science technology (R Shiny) to improve health data reporting in Nairobi City County, Kenya. Based on a previously used manual tool, in June 2022, we developed a digital online data capture and reporting tool using the open-source Kobo toolbox. Primary mental health care providers (nurses and physicians) working in primary healthcare facilities in Nairobi were trained to use the tool to report cases of MNS disorders diagnosed in their facilities in real-time. The digital tool covered MNS disorders listed in the World Health Organization’s (WHO) Mental Health Gap Action Program Intervention Guide (mhGAP-IG). In the digital system, data were disaggregated as new or repeat visits. We linked the data to a live dynamic reproducible dashboard created using R Shiny, summarising the data in tables and figures. Between January and August 2023, 9064 cases of MNS disorders (4454 newly diagnosed, 4591 revisits and 19 referrals) were reported using the digital system compared to 5321 using the manual system in a similar period in 2022. Reporting in the digital system was real-time compared to the manual system, where reports were aggregated and submitted monthly. The system improved data quality by providing timely and complete reports. Open-source applications to report health data is feasible and acceptable to primary health care providers. The technology improved real-time data capture, reporting, and monitoring, providing invaluable information on the burden of MNS disorders and which services can be planned and used for advocacy. The fast and efficient system can be scaled up and integrated with national and sub-national health information systems to reduce manual data reporting and decrease the likelihood of errors and inconsistencies

Does a standardised scoring system of clinical signs reduce variability between doctors’ assessments of the potentially dehydrated child?

Aims: Clinical assessment of dehydration in children is often inaccurate. We aimed to determine if a scoring system based on standardised clinical signs would reduce the variability between doctors' assessment of dehydration. Methods: A clinical scoring system was developed using seven physiological variables based on previously published research. Estimated percentage dehydration and severity scores were recorded for 100 children presenting to a Paediatric Emergency Department with symptoms of gastroenteritis and dehydration by three doctors of different seniority (resident medical officer, registrar and consultant). Agreement was measured using intra-class correlation coefficient (ICC) for percentage ratings and total clinical scores and kappa for individual characteristics. Results: Estimated percentage dehydration ranged from 0-9%, mean 2.96%, across the three groups. Total clinical scores from 0-10, mean 2.20. There was moderate agreement amongst clinicians for the percentage dehydration (ICC 0.40). The level of agreement on the clinical scoring system was identical (ICC 0.40). Consultants gave statistically lower scores than the other two groups (Consultant (Con) vs. Resident P = 0.001, Con vs. Registrar P = 0.013). There was a marked difference in agreement across characteristics comprising the scoring system, from kappa 0.02 for capillary refill time to 0.42 for neurological status. Conclusion: The clinical scoring system used did not reduce the variability of assessment of dehydration compared to doctors' conventional methods. In order to reduce variability improving education may be more important than production of a scoring system as experience appears to be a key determinant in the assessment of a potentially dehydrated child