Intranasal versus Intramuscular/Intravenous Naloxone for Pre-hospital Opioid Overdose: A Systematic Review and Meta-analysis

Context: The present systematic review and meta-analysis aims to perform an extensive search in databases to compare the efficacy of the intranasal administration of naloxone with its intramuscular/intravenous administration in the pre-hospital management of opioid overdose. Evidence acquisition: This meta-analysis included controlled trials conducted on the efficacy of naloxone administration in the pre-hospital management of opioid overdose. A search was carried out in electronic databases on relevant articles published by the end of 2018. After data collection, analyses were performed in STATA 14.0 software and the efficacy and side-effects of the two administration routes of naloxone, i.e. intranasal and intramuscular/intravenous, were compared. An overall effect size with 95% confidence interval (95% CI) was provided for each section. Results: Eventually, data from six studies were included in this meta-analysis. The success rate of the intranasal and intramuscular/intravenous administration of naloxone in the management of opioid overdose in pre-hospital settings was 82.54% (95% CI: 57.97 to 97.89%) and 80.39% (95% CI: 57.38 to 96.04%), respectively. There was no difference between injectable (intramuscular/intravenous) naloxone and intranasal naloxone in the pre-hospital management of opioid overdose (Odds Ratio=1.01; 95% CI: 0.42 to 2.43; P=0.98). The onset of action of intranasal naloxone, however, was slightly longer than injectable naloxone (Standardized Mean Difference=0.63; 95% CI: 0.07 to 1.19; P=0.03). Additionally, the odds of needing a rescue dose was 2.17 times higher for intranasal naloxone than intramuscular/intravenous naloxone (OR=2.17; 95% CI: 1.53 to 3.09; P<0.0001). The prevalence of major side-effects was non-significant for both intranasal (0.00%) and intramuscular/intravenous (0.05%) routes of naloxone administration and there was no difference in the prevalence of major (OR=1.18; 95% CI: 0.38 to 3.69; P=0.777) and minor (OR=0.64; 95% CI: 0.17 to 2.34; P=0.497) side-effects between the two routes. Conclusion: The present meta-analysis demonstrated that intranasal naloxone is as effective as injectable naloxone in the pre-hospital management of opioid overdose complications. Consequently, intranasal naloxone may be an appropriate alternative to injectable naloxone

Intranasal versus Intramuscular/Intravenous Naloxone for Pre-hospital Opioid Overdose: A Systematic Review and Meta-analysis

Context: The present systematic review and meta-analysis aims to perform an extensive search in databases to compare the efficacy of the intranasal administration of naloxone with its intramuscular/intravenous administration in the pre-hospital management of opioid overdose. Evidence acquisition: This meta-analysis included controlled trials conducted on the efficacy of naloxone administration in the pre-hospital management of opioid overdose. A search was carried out in electronic databases on relevant articles published by the end of 2018. After data collection, analyses were performed in STATA 14.0 software and the efficacy and side-effects of the two administration routes of naloxone, i.e. intranasal and intramuscular/intravenous, were compared. An overall effect size with 95% confidence interval (95% CI) was provided for each section. Results: Eventually, data from six studies were included in this meta-analysis. The success rate of the intranasal and intramuscular/intravenous administration of naloxone in the management of opioid overdose in pre-hospital settings was 82.54% (95% CI: 57.97 to 97.89%) and 80.39% (95% CI: 57.38 to 96.04%), respectively. There was no difference between injectable (intramuscular/intravenous) naloxone and intranasal naloxone in the pre-hospital management of opioid overdose (Odds Ratio=1.01; 95% CI: 0.42 to 2.43; P=0.98). The onset of action of intranasal naloxone, however, was slightly longer than injectable naloxone (Standardized Mean Difference=0.63; 95% CI: 0.07 to 1.19; P=0.03). Additionally, the odds of needing a rescue dose was 2.17 times higher for intranasal naloxone than intramuscular/intravenous naloxone (OR=2.17; 95% CI: 1.53 to 3.09; P<0.0001). The prevalence of major side-effects was non-significant for both intranasal (0.00%) and intramuscular/intravenous (0.05%) routes of naloxone administration and there was no difference in the prevalence of major (OR=1.18; 95% CI: 0.38 to 3.69; P=0.777) and minor (OR=0.64; 95% CI: 0.17 to 2.34; P=0.497) side-effects between the two routes. Conclusion: The present meta-analysis demonstrated that intranasal naloxone is as effective as injectable naloxone in the pre-hospital management of opioid overdose complications. Consequently, intranasal naloxone may be an appropriate alternative to injectable naloxone

Efficacy of Irisin on neurological and tissue-related outcomes in ischemic brain injuries; a scoping review

Background: Evidence indicates the protective role of Irisin on nervous tissue following ischemic events, by preventing the cascades of secondary damage. We conducted this scoping review to summarize what has been discovered so far on the neuroprotective effects of Irisin, with a focus on ischemic stroke. Methods: Search strategies were designed based on the keywords related to ischemic stroke and Irisin. Next, an extensive search in Medline, Embase, Scopus, and Web of Science was conducted by the end of April 2022. Two researchers independently reviewed the articles and performed the screening of the selected papers according to the inclusion criteria. Finally, the required data were extracted to a checklist designed based on the PRISMA guideline. The “meta” package was used for the meta-analysis, and heterogeneity between studies was assessed using the I2 test. Results: Pooled data analysis showed that the Irisin administration significantly improved the neurological function following cerebral ischemia / reperfusion injuries (SMD = 3.08; 95% CI: 1.10, 5.06; p<0.0001). Additionally, meta-regression demonstrated that the improvement in neurological function was directly related to the dose of administered Irisin (meta-regression coefficient = 0.03; p = 0.02). Moreover, Irisin administration significantly reduced the volume of infarcted lesions (SMD= -3.14; 95% CI: -4.23, -2.04; p<0.0001), the amount of edema in the brain (SMD= -2.30; 95% CI: -4.07, -0.53; p<0.0001), and the extend of neuronal-cell apoptosis rate (SMD= -4.67; 95% CI: -8.15, -1.19; p<0.0001). Conclusion: The present study demonstrates that the administration of Irisin in animal models of cerebral ischemia / reperfusion injuries is associated with a significant dose-dependent improvement in neurological function. Due to the limited number of articles, more research on the aim of finding the optimum Irisin dosage is in high demand

Intranasal versus Intramuscular/Intravenous naloxone for pre-hospital opioid overdose: a systematic review and meta-analysis.

Context: The present systematic review and meta-analysis aims to perform an extensive search in databases to compare the efficacy of the intranasal administration of naloxone with its intramuscular/intravenous administration in the pre-hospital management of opioid overdose. Evidence acquisition: This meta-analysis included controlled trials conducted on the efficacy of naloxone administration in the pre-hospital management of opioid overdose. A search was carried out in electronic databases on relevant articles published by the end of 2018. After data collection, analyses were performed in STATA 14.0 software and the efficacy and side-effects of the two administration routes of naloxone, i.e. intranasal and intramuscular/intravenous, were compared. An overall effect size with 95% confidence interval (95% CI) was provided for each section. Results: Eventually, data from six studies were included in this meta-analysis. The success rate of the intranasal and intramuscular/intravenous administration of naloxone in the management of opioid overdose in pre-hospital settings was 82.54% (95% CI: 57.97 to 97.89%) and 80.39% (95% CI: 57.38 to 96.04%), respectively. There was no difference between injectable (intramuscular/intravenous) naloxone and intranasal naloxone in the pre-hospital management of opioid overdose (Odds Ratio=1.01; 95% CI: 0.42 to 2.43; P=0.98). The onset of action of intranasal naloxone, however, was slightly longer than injectable naloxone (Standardized Mean Difference=0.63; 95% CI: 0.07 to 1.19; P=0.03). Additionally, the odds of needing a rescue dose was 2.17 times higher for intranasal naloxone than intramuscular/intravenous naloxone (OR=2.17; 95% CI: 1.53 to 3.09; P<0.0001). The prevalence of major side-effects was non-significant for both intranasal (0.00%) and intramuscular/intravenous (0.05%) routes of naloxone administration and there was no difference in the prevalence of major (OR=1.18; 95% CI: 0.38 to 3.69; P=0.777) and minor (OR=0.64; 95% CI: 0.17 to 2.34; P=0.497) side-effects between the two routes. Conclusion: The present meta-analysis demonstrated that intranasal naloxone is as effective as injectable naloxone in the pre-hospital management of opioid overdose complications. Consequently, intranasal naloxone may be an appropriate alternative to injectable naloxone

The value of predictive instruments in the screening of acute stroke: an umbrella review on previous systematic reviews

Objective: Although various predictive instruments have been introduced for early stroke diagnosis, there is no consensus on their performance. Therefore, we decided to assess the value of predictive instruments in the detection of stroke by conducting an umbrella review. Method: A search was performed in the Medline, Embase, Scopus and Web of Science databases by the end of August 2021 for systematic reviews and meta-analyses. Original articles included in the systematic reviews were retrieved, summarized and pooled sensitivity, specificity and diagnostic odds ratio were calculated. The level of evidence was divided into five groups: convincing (class I), highly suggestive (class II), suggestive (class III), weak (class IV) and non-significant. Results: The value of 33 predictive instruments was evaluated. The sample size included in these scoring systems’ assessments varied between 182 and 47072 patients. The level of evidence was class I in one tool, class II in 18 tools, class III in 2 tools, class IV in 11 tools, and non-significant in one tool. Apart from Med PACS, which had a low diagnostic value, other tools appeared to be able to detect a stroke. The optimum performance for diagnosis of stroke was for ROSIER, NIHSS, PASS, FAST, LAMS, RACE and CPSS. Conclusion: Convincing to suggestive evidence shows that ROSIER, NIHSS, PASS, FAST, LAMS, RACE and CPSS have the optimum performance in identifying stroke. Since ROSIER’s calculation is simple and has the highest sensitivity and specificity among those predictive instruments, it is recommended for stroke diagnosis in pre-hospital and in-hospital settings

Effects of Epothilone Administration on Locomotion Recovery after Spinal Cord Injury: A Systematic Review of Animal Studies

This is a systematic review and meta-analysis of existing evidence regarding the possible effects of epothilones on spinal cord injury (SCI). This study aimed to investigate the possible effects of epothilone administration on locomotion recovery in animal models of SCI. Despite increasing rates of SCI and its burden on populations, no consensus has been reached about the possible treatment modality for SCI. Meanwhile, low-dose epothilones have been reported to have positive effects on SCI outcomes. Electronic databases of Web of Science, Scopus, Embase, and Medline were searched using keywords related to epothilones and SCI until the end of 2020. Two researchers screened the articles, and extracted data were analyzed using STATA ver. 14.0. Final results are reported as a standardized mean difference (SMD) with a 95% confidence interval (CI). After the screening, five studies were included in the analysis. Rats were used in all the studies. Two types of epothilones were used via intraperitoneal injection and were shown to have positive effects on the motor outcomes of samples with SCI (SMD, 0.87; 95% CI, 0.51 to 1.23; p=0.71). Although a slightly better effect was observed when using epothilone B, the difference was not significant (coefficient, −0.50; 95% CI, −1.52 to 0.52; p=0.246). The results of this study suggest that epothilones have positive effects on the improvement of motor function in rats, when administered intraperitoneally until a maximum of 1 day after SCI. However, current evidence regarding the matter is still scarce

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundAccurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. MethodsTo estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. FindingsDuring the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. InterpretationFertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world. FundingBill & Melinda Gates Foundation

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundAccurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.MethodsTo estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.FindingsDuring the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.InterpretationFertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world.</p