Diagnostic Accuracy of Procalcitonin in Differentiating Sepsis from Noninfectious SIRS in Adult Patients with Subarachnoid Hemorrhage

Background: Subarachnoid hemorrhage (SAH) is a frequent diagnosis in the neuro-intensive care unit (NICU) that can result in the development of systemic inflammatory response syndrome (SIRS) and fever. The differentiation between central fever and infectious fever is paramount in order to prevent superfluous diagnostic testing and overuse of empiric antibiotics. Methods: A prospective chart review study conducted in the NICU between December 2012 and September 2015. Patients with SAH, fever (≥101.0°F) and/or who were SIRS positive and had PCT levels measured were included. The primary outcome was clinical infection defined as any positive culture or infiltrate on chest X-ray within three days of onset of fever. Results: Out of 129 patients, 54 were positive for any culture: 14 with PCT ≤0.2, 12 with PCT \u3e0.2 and ≤0.5, and 28 with PCT \u3e0.5. Using multiple logistic regression, PCT between 0.2-0.5 had an odds ratio of 2.99 (95% CI 1.12-8.00) while PCT \u3e0.5 had an odds ratio of 29.11 (CI 8.49-99.83) and p-value of \u3c0.001. All other predictors were not statistically significant. For procalcitonin \u3e0.5, specificity is 94.7%, sensitivity 51.9%, positive predictive value 87.5%, and negative predictive value 73.2%. ROC Curve area: 79.3%. Conclusion: PCT of 0.5 ng/mL or greater was useful for distinguishing infectious from central fever in SAH patients, with PCT values between 0.2-0.5 as somewhat predictive of infection. The test has high specificity and a reasonably high negative predictive value, so it can be a valuable tool to rule out infectious fever in patients with SAH

Prevalence, years lived with disability, and trends in anaemia burden by severity and cause, 1990-2021: findings from the Global Burden of Disease Study 2021

Background Anaemia is a major health problem worldwide. Global estimates of anaemia burden are crucial for developing appropriate interventions to meet current international targets for disease mitigation. We describe the prevalence, years lived with disability, and trends of anaemia and its underlying causes in 204 countries and territories. Methods We estimated population-level distributions of haemoglobin concentration by age and sex for each location from 1990 to 2021. We then calculated anaemia burden by severity and associated years lived with disability (YLDs). With data on prevalence of the causes of anaemia and associated cause-specific shifts in haemoglobin concentrations, we modelled the proportion of anaemia attributed to 37 underlying causes for all locations, years, and demographics in the Global Burden of Disease Study 2021. Findings In 2021, the global prevalence of anaemia across all ages was 24·3% (95% uncertainty interval [UI] 23·9–24·7), corresponding to 1·92 billion (1·89–1·95) prevalent cases, compared with a prevalence of 28·2% (27·8–28·5) and 1·50 billion (1·48–1·52) prevalent cases in 1990. Large variations were observed in anaemia burden by age, sex, and geography, with children younger than 5 years, women, and countries in sub-Saharan Africa and south Asia being particularly affected. Anaemia caused 52·0 million (35·1–75·1) YLDs in 2021, and the YLD rate due to anaemia declined with increasing Socio-demographic Index. The most common causes of anaemia YLDs in 2021 were dietary iron deficiency (cause-specific anaemia YLD rate per 100 000 population: 422·4 [95% UI 286·1–612·9]), haemoglobinopathies and haemolytic anaemias (89·0 [58·2–123·7]), and other neglected tropical diseases (36·3 [24·4–52·8]), collectively accounting for 84·7% (84·1–85·2) of anaemia YLDs. Interpretation Anaemia remains a substantial global health challenge, with persistent disparities according to age, sex, and geography. Estimates of cause-specific anaemia burden can be used to design locally relevant health interventions aimed at improving anaemia management and prevention. Funding Bill & Melinda Gates Foundation

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

A Review of Machine Learning Algorithms for Cloud Computing Security

Cloud computing (CC) is on-demand accessibility of network resources, especially data storage and processing power, without special and direct management by the users. CC recently has emerged as a set of public and private datacenters that offers the client a single platform across the Internet. Edge computing is an evolving computing paradigm that brings computation and information storage nearer to the end-users to improve response times and spare transmission capacity. Mobile CC (MCC) uses distributed computing to convey applications to cell phones. However, CC and edge computing have security challenges, including vulnerability for clients and association acknowledgment, that delay the rapid adoption of computing models. Machine learning (ML) is the investigation of computer algorithms that improve naturally through experience. In this review paper, we present an analysis of CC security threats, issues, and solutions that utilized one or several ML algorithms. We review different ML algorithms that are used to overcome the cloud security issues including supervised, unsupervised, semi-supervised, and reinforcement learning. Then, we compare the performance of each technique based on their features, advantages, and disadvantages. Moreover, we enlist future research directions to secure CC models

Energy Demand of the Road Transport Sector of Saudi Arabia—Application of a Causality-Based Machine Learning Model to Ensure Sustainable Environment

The road transportation sector in Saudi Arabia has been observing a surging growth of demand trends for the last couple of decades. The main objective of this article is to extract insightful information for the country’s policymakers through a comprehensive investigation of the rising energy trends. In the first phase, it employs econometric analysis to provide the causal relationship between the energy demand of the road transportation sector and different socio-economic elements, including the gross domestic product (GDP), number of registered vehicles, total population, the population in the urban agglomeration, and fuel price. Then, it estimates future energy demand for the sector using two machine-learning models, i.e., artificial neural network (ANN) and support vector regression (SVR). The core features of the future demand model include: (i) removal of the linear trend, (ii) input data projection using a double exponential smoothing technique, and (iii) energy demand prediction using the machine learning models. The findings of the study show that the GDP and urban population have a significant causal relationship with energy demand in the road transportation sector in both the short and long run. The greenhouse gas emissions from the road transportation in Saudi Arabia are directly proportional to energy consumption because the demand is solely met by fossil fuels. Therefore, appropriate policy measures should be taken to reduce energy intensity without compromising the country’s development. In addition, the SVR model outperformed the ANN model in predicting the future energy demand of the sector based on the achieved performance indices. For instance, the correlation coefficients of the SVR and the ANN models were 0.8932 and 0.9925, respectively, for the test datasets. The results show that the SVR is better for predicting energy consumption than the ANN. It is expected that the findings of the study will assist the decision-makers of the country in achieving environmental sustainability goals by initiating appropriate policies

Global, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990–2021 : a systematic analysis from the Global Burden of Disease Study 2021

Background Lower respiratory infections (LRIs) are a major global contributor to morbidity and mortality. In 2020–21, non-pharmaceutical interventions associated with the COVID-19 pandemic reduced not only the transmission of SARS-CoV-2, but also the transmission of other LRI pathogens. Tracking LRI incidence and mortality, as well as the pathogens responsible, can guide health-system responses and funding priorities to reduce future burden. We present estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 of the burden of non-COVID-19 LRIs and corresponding aetiologies from 1990 to 2021, inclusive of pandemic effects on the incidence and mortality of select respiratory viruses, globally, regionally, and for 204 countries and territories. Methods We estimated mortality, incidence, and aetiology attribution for LRI, defined by the GBD as pneumonia or bronchiolitis, not inclusive of COVID-19. We analysed 26 259 site-years of mortality data using the Cause of Death Ensemble model to estimate LRI mortality rates. We analysed all available age-specific and sex-specific data sources, including published literature identified by a systematic review, as well as household surveys, hospital admissions, health insurance claims, and LRI mortality estimates, to generate internally consistent estimates of incidence and prevalence using DisMod-MR 2.1. For aetiology estimation, we analysed multiple causes of death, vital registration, hospital discharge, microbial laboratory, and literature data using a network analysis model to produce the proportion of LRI deaths and episodes attributable to the following pathogens: Acinetobacter baumannii, Chlamydia spp, Enterobacter spp, Escherichia coli, fungi, group B streptococcus, Haemophilus influenzae, influenza viruses, Klebsiella pneumoniae, Legionella spp, Mycoplasma spp, polymicrobial infections, Pseudomonas aeruginosa, respiratory syncytial virus (RSV), Staphylococcus aureus, Streptococcus pneumoniae, and other viruses (ie, the aggregate of all viruses studied except influenza and RSV), as well as a residual category of other bacterial pathogens. Findings Globally, in 2021, we estimated 344 million (95% uncertainty interval [UI] 325–364) incident episodes of LRI, or 4350 episodes (4120–4610) per 100 000 population, and 2·18 million deaths (1·98–2·36), or 27·7 deaths (25·1–29·9) per 100 000. 502 000 deaths (406 000–611 000) were in children younger than 5 years, among which 254 000 deaths (197 000–320 000) occurred in countries with a low Socio-demographic Index. Of the 18 modelled pathogen categories in 2021, S pneumoniae was responsible for the highest proportions of LRI episodes and deaths, with an estimated 97·9 million (92·1–104·0) episodes and 505 000 deaths (454 000–555 000) globally. The pathogens responsible for the second and third highest episode counts globally were other viral aetiologies (46·4 million [43·6–49·3] episodes) and Mycoplasma spp (25·3 million [23·5–27·2]), while those responsible for the second and third highest death counts were S aureus (424 000 [380 000–459 000]) and K pneumoniae (176 000 [158 000–194 000]). From 1990 to 2019, the global all-age non-COVID-19 LRI mortality rate declined by 41·7% (35·9–46·9), from 56·5 deaths (51·3–61·9) to 32·9 deaths (29·9–35·4) per 100 000. From 2019 to 2021, during the COVID-19 pandemic and implementation of associated non-pharmaceutical interventions, we estimated a 16·0% (13·1–18·6) decline in the global all-age non-COVID-19 LRI mortality rate, largely accounted for by a 71·8% (63·8–78·9) decline in the number of influenza deaths and a 66·7% (56·6–75·3) decline in the number of RSV deaths. Interpretation Substantial progress has been made in reducing LRI mortality, but the burden remains high, especially in low-income and middle-income countries. During the COVID-19 pandemic, with its associated non-pharmaceutical interventions, global incident LRI cases and mortality attributable to influenza and RSV declined substantially. Expanding access to health-care services and vaccines, including S pneumoniae, H influenzae type B, and novel RSV vaccines, along with new low-cost interventions against S aureus, could mitigate the LRI burden and prevent transmission of LRI-causing pathogens. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care (UK)

Prevalence, years lived with disability, and trends in anaemia burden by severity and cause, 1990–2021: findings from the Global Burden of Disease Study 2021

Background: Anaemia is a major health problem worldwide. Global estimates of anaemia burden are crucial for developing appropriate interventions to meet current international targets for disease mitigation. We describe the prevalence, years lived with disability, and trends of anaemia and its underlying causes in 204 countries and territories. Methods: We estimated population-level distributions of haemoglobin concentration by age and sex for each location from 1990 to 2021. We then calculated anaemia burden by severity and associated years lived with disability (YLDs). With data on prevalence of the causes of anaemia and associated cause-specific shifts in haemoglobin concentrations, we modelled the proportion of anaemia attributed to 37 underlying causes for all locations, years, and demographics in the Global Burden of Disease Study 2021. Findings: In 2021, the global prevalence of anaemia across all ages was 24·3% (95% uncertainty interval [UI] 23·9–24·7), corresponding to 1·92 billion (1·89–1·95) prevalent cases, compared with a prevalence of 28·2% (27·8–28·5) and 1·50 billion (1·48–1·52) prevalent cases in 1990. Large variations were observed in anaemia burden by age, sex, and geography, with children younger than 5 years, women, and countries in sub-Saharan Africa and south Asia being particularly affected. Anaemia caused 52·0 million (35·1–75·1) YLDs in 2021, and the YLD rate due to anaemia declined with increasing Socio-demographic Index. The most common causes of anaemia YLDs in 2021 were dietary iron deficiency (cause-specific anaemia YLD rate per 100 000 population: 422·4 [95% UI 286·1–612·9]), haemoglobinopathies and haemolytic anaemias (89·0 [58·2–123·7]), and other neglected tropical diseases (36·3 [24·4–52·8]), collectively accounting for 84·7% (84·1–85·2) of anaemia YLDs. Interpretation: Anaemia remains a substantial global health challenge, with persistent disparities according to age, sex, and geography. Estimates of cause-specific anaemia burden can be used to design locally relevant health interventions aimed at improving anaemia management and prevention. Funding: Bill & Melinda Gates Foundation