The role of sleep deprivation and fatigue in the perception of task difficulty and use of heuristics

Objectives: This study investigated the effects of sleep deprivation on perception of task difficulty and use of heuristics (mental shortcuts) compared to naturally-experienced sleep at home. Methods: Undergraduate students were screened and assigned through block-random assignment to Naturally-Experienced Sleep (NES; n=19) or Total Sleep Deprivation (TSD; n=20). The next morning, reported fatigue, perception of task difficulty, and use of “what-is-beautiful-is-good,” “greedy algorithm,” and “speed-accuracy trade-off ” heuristics were assessed. Results: NES slept for an average of 354.74 minutes (SD=72.84), or 5.91 hours. TSD rated a reading task as significantly more difficult and requiring more time than NES. TSD was significantly more likely to use the greedy algorithm heuristic by skipping instructions and the what-is-beautiful-is-good heuristic by rating an unattractive consumer item with a favorable review as poor quality. Those in Total Sleep Deprivation who chose more difficult math problems made this selection to finish the task more quickly in findings approaching significance, indicating use of the speed-accuracy trade-off heuristic. Collapsed across conditions, self-reported fatigue predicted greater perceived difficulty in both the reading task and a visuo-motor task, higher quality rating for the attractive consumer item, and lower quality rating for the unattractive consumer item. Conclusions: Findings indicate sleep deprivation and fatigue increase perceptions of task difficulty, promote skipping instructions, and impair systematic evaluation of unappealing stimuli compared to naturally-experienced sleep

Risk Model Development and Validation for Prediction of Coronary Artery Aneurysms in Kawasaki Disease in a North American Population.

Background Accurate prediction of coronary artery aneurysms ( CAAs ) in patients with Kawasaki disease remains challenging in North American cohorts. We sought to develop and validate a risk model for CAA prediction. Methods and Results A binary outcome of CAA was defined as left anterior descending or right coronary artery Z score ≥2.5 at 2 to 8 weeks after fever onset in a development cohort (n=903) and a validation cohort (n=185) of patients with Kawasaki disease. Associations of baseline clinical, laboratory, and echocardiographic variables with later CAA were assessed in the development cohort using logistic regression. Discrimination (c statistic) and calibration (Hosmer-Lemeshow) of the final model were evaluated. A practical risk score assigning points to each variable in the final model was created based on model coefficients from the development cohort. Predictors of CAAs at 2 to 8 weeks were baseline Z score of left anterior descending or right coronary artery ≥2.0, age <6 months, Asian race, and C-reactive protein ≥13 mg/ dL (c=0.82 in the development cohort, c=0.93 in the validation cohort). The CAA risk score assigned 2 points for baseline Z score of left anterior descending or right coronary artery ≥2.0 and 1 point for each of the other variables, with creation of low- (0-1), moderate- (2), and high- (3-5) risk groups. The odds of CAA s were 16-fold greater in the high- versus the low-risk groups in the development cohort (odds ratio, 16.4; 95% CI , 9.71-27.7 [ P<0.001]), and >40-fold greater in the validation cohort (odds ratio, 44.0; 95% CI, 10.8-180 [ P<0.001]). Conclusions Our risk model for CAA in Kawasaki disease consisting of baseline demographic, laboratory, and echocardiographic variables had excellent predictive utility and should undergo prospective testing

Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019

Background Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. Methods We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (USMR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. Findings Global U5MR decreased from 71.2 deaths per 1000 livebirths (95% uncertainty interval WI] 68.3-74-0) in 2000 to 37.1 (33.2-41.7) in 2019 while global NMR correspondingly declined more slowly from 28.0 deaths per 1000 live births (26.8-29-5) in 2000 to 17.9 (16.3-19-8) in 2019. In 2019,136 (67%) of 204 countries had a USMR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030,154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9.65 million (95% UI 9.05-10.30) in 2000 and 5.05 million (4.27-6.02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3.76 million 95% UI 3.53-4.021) in 2000 to 48% (2.42 million; 2.06-2.86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0.80 (95% UI 0.71-0.86) deaths per 1000 livebirths and U5MR to 1.44 (95% UI 1-27-1.58) deaths per 1000 livebirths, and in 2019, there were as many as 1.87 million (95% UI 1-35-2.58; 37% 95% UI 32-43]) of 5.05 million more deaths of children younger than 5 years than the survival potential frontier. Interpretation Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve USMR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

The effects of sleep loss on capacity and effort

AbstractSleep loss appears to affect the capacity for performance and access to energetic resources. This paper reviews research examining the physical substrates referred to as resource capacity, the role of sleep in protecting that capacity and the reaction of the system as it attempts to respond with effort to overcome the limitations on capacity caused by sleep loss. Effort is the extent to which an organism will exert itself beyond basic levels of functioning or attempt alternative strategies to maintain performance. The purpose of this review is to bring together research across sleep disciplines to clarify the substrates that constitute and influence capacity for performance, consider how the loss of sleep influences access to those resources, examine cortical, physiological, perceptual, behavioral and subjective effort responses and consider how these responses reflect a system reacting to changes in the resource environment. When sleep deprived, the ability to perform tasks that require additional energy is impaired and the ability of the system to overcome the deficiencies caused by sleep loss is limited. Taking on tasks that require effort including school work, meal preparation, pulling off the road to nap when driving drowsy appear to be more challenging during sleep loss. Sleep loss impacts the effort-related choices we make and those choices may influence our health and safety

Partnered decision support: Parental perspectives of completing a pre‐visit pediatric asthma questionnaire via the patient portal

BackgroundCollection of patient-reported data has been demonstrated to improve asthma outcomes. One method to collect information is through the electronic patient portal. In practice, patient portal use in pediatrics and, specifically for asthma management, has had low uptake.ObjectiveTo understand parental/caregiver experience of pediatric asthma care management, and perceptions of the use of patient portal questionnaires before the clinic visit.MethodsWe conducted semi-structured interviews with caregivers of children 5-11 years old with asthma in the University of California, Los Angeles (UCLA) Health System. We included patient portal "users" (n = 20) and "non-users" (n = 5). Interview questions were developed based on clinic visit workflow with a focus on perceived usefulness and ease of use to complete pediatric asthma questionnaires in the patient portal before the visit. Interviews were audio-recorded, transcribed, and codes were generated from themes using constant comparative analysis.ResultsWe identified eight themes related to caregiver-physician communication, perception of portal questionnaires, facilitators, and barriers to portal questionnaire use. A salient finding was that caregivers considered the portal questionnaire as a tool to be integrated into the visit to facilitate a conversation about their child's asthma. Caregiver portal-based questionnaire use was more likely if the ongoing data entered was accessible to caregivers to track and update, and if caregivers were reassured the clinicians would use questionnaire responses during the visit.ConclusionCaregivers of children with asthma are more likely to complete a patient portal intake questionnaire before the visit if they trust their responses will be used during the visit to inform care