Using artificial intelligence for exercise prescription in personalised health promotion: A critical evaluation of OpenAI’s GPT-4 model

The rise of artificial intelligence (AI) applications in healthcare provides new possibilities for personalized health management. AI-based fitness applications are becoming more common, facilitating the opportunity for individualised exercise prescription. However, the use of AI carries the risk of inadequate expert supervision, and the efficacy and validity of such applications have not been thoroughly investigated, particularly in the context of diverse health conditions. The aim of the study was to critically assess the efficacy of exercise prescriptions generated by OpenAI’s Generative Pre-Trained Transformer 4 (GPT-4) model for five example patient profiles with diverse health conditions and fitness goals. Our focus was to assess the model’s ability to generate exercise prescriptions based on a singular, initial interaction, akin to a typical user experience. The evaluation was conducted by leading experts in the field of exercise prescription. Five distinct scenarios were formulated, each representing a hypothetical individual with a specific health condition and fitness objective. Upon receiving details of each individual, the GPT-4 model was tasked with generating a 30-day exercise program. These AI-derived exercise programs were subsequently subjected to a thorough evaluation by experts in exercise prescription. The evaluation encompassed adherence to established principles of frequency, intensity, time, and exercise type; integration of perceived exertion levels; consideration for medication intake and the respective medical condition; and the extent of program individualization tailored to each hypothetical profile. The AI model could create general safety-conscious exercise programs for various scenarios. However, the AI-generated exercise prescriptions lacked precision in addressing individual health conditions and goals, often prioritizing excessive safety over the effectiveness of training. The AI-based approach aimed to ensure patient improvement through gradual increases in training load and intensity, but the model’s potential to fine-tune its recommendations through ongoing interaction was not fully satisfying. AI technologies, in their current state, can serve as supplemental tools in exercise prescription, particularly in enhancing accessibility for individuals unable to access, often costly, professional advice. However, AI technologies are not yet recommended as a substitute for personalized, progressive, and health condition specific prescriptions provided by healthcare and fitness professionals. Further research is needed to explore more interactive use of AI models and integration of real-time physiological feedback

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Efficacy of different local anaesthetic volumes during erector spinae block for postoperative pain management in patients undergoing open nephrectomy operations. A randomized controlled study

ABSTRACTBackground Pain control after surgery is of highest priority. Erector spinae plane block [ESPB] was reported to be a successful method to reduce pain scores and consumption of postoperative opioids. However, hardly any investigation has looked at the ideal volume of bupivacaine for ESPB. So, this work tried to fill this gap of literature in patients undergoing simple nephrectomy.Methods In this randomized double blinded control study, 100 cases undergoing simple nephrectomy were randomized into 4 groups with 25 patients per group. Group E1, 2, and 3 received ESPB with 2.5, 3.4, and 6.6 ml/segment of 0.25% bupivacaine, respectively, whereas there was no block given to the control group. Intraoperative fentanyl consumption, heart rate [HR] and the blood pressure [BP], Postoperative morphine consumption, time passed to first analgesic request, numerical rating score [NRS] of pain, the complications, HR and BP were documented for 24 hours after the operation.Results The reduction in intraoperative fentanyl consumption, postoperative morphine consumption and NRS were a significantly different between the block groups and control. Group E3 had significant difference from other groups with the longest time to first analgesia request. A lower HR was shown in block groups but within normal range. BP showed insignificant difference between groups. There were no reported complications in all study groups.Conclusions The volume of 6.6 ml/level was associated with the best pain control, without significant hemodynamic changes or adverse events as compared to other groups. This suggests that this volume may be the optimal for ESPB in patients undergoing simple nephrectomy

Performance Enhancement of an Islanded Microgrid with the Support of Electrical Vehicle and STATCOM Systems

Modern electrical power systems now require the spread of microgrids (MG), where they would be operating in either islanded mode or grid-connected mode. An inherent mismatch between loads and sources is introduced by changeable high renewable share in an islanded MG system with stochastic load demands. The system frequency is directly impacted by this mismatch, which can be alleviated by incorporating cutting-edge energy storage technologies and FACTS tools. The investigated islanded MG system components are wind farm, solar PV, Electric vehicles (EVs), loads, DSTATCOM, and diesel power generator. An aggregated EVs model is connected to the MG during uncertain periods of the generation of renewable energy (PV and wind) to support the performance of MGs. The ability to support ancillary services from the EVs is checked. DSTATCOM is used to provide voltage stability for the MG during congestion situations. The MG is studied in three scenarios: the first scenario MG without EVs and DSTATCOM, the second scenario MG without DSTATCOM, and the third scenario MG with all components. These scenarios are addressed to show the role of EVs and DSTATCOM, and the results in the third scenario are the best. The system voltage and frequency profile is the best in the last scenario and is entirely satisfactory and under the range of the IEEE standard. The obtained results show that both EVs and DSTATCOM are important units for improving the stability of modern power grids. The Matlab/Simulink program is considered for checking and validating the dynamic performance of the proposed configuration

Performance Enhancement of an Islanded Microgrid with the Support of Electrical Vehicle and STATCOM Systems

Modern electrical power systems now require the spread of microgrids (MG), where they would be operating in either islanded mode or grid-connected mode. An inherent mismatch between loads and sources is introduced by changeable high renewable share in an islanded MG system with stochastic load demands. The system frequency is directly impacted by this mismatch, which can be alleviated by incorporating cutting-edge energy storage technologies and FACTS tools. The investigated islanded MG system components are wind farm, solar PV, Electric vehicles (EVs), loads, DSTATCOM, and diesel power generator. An aggregated EVs model is connected to the MG during uncertain periods of the generation of renewable energy (PV and wind) to support the performance of MGs. The ability to support ancillary services from the EVs is checked. DSTATCOM is used to provide voltage stability for the MG during congestion situations. The MG is studied in three scenarios: the first scenario MG without EVs and DSTATCOM, the second scenario MG without DSTATCOM, and the third scenario MG with all components. These scenarios are addressed to show the role of EVs and DSTATCOM, and the results in the third scenario are the best. The system voltage and frequency profile is the best in the last scenario and is entirely satisfactory and under the range of the IEEE standard. The obtained results show that both EVs and DSTATCOM are important units for improving the stability of modern power grids. The Matlab/Simulink program is considered for checking and validating the dynamic performance of the proposed configuration

Efficacy of Kinesio Taping Compared to Other Treatment Modalities in Musculoskeletal Disorders: A Systematic Review and Meta-Analysis

Kinesio taping is widely used in musculoskeletal conditions. We performed a systematic review and meta-analysis on the efficacy of kinesio taping in musculoskeletal disorders compared to other interventions. Twelve electronic databases were used for systemic search and data relevant to pain and disability were extracted. The protocol was registered in PROSPERO (CRD42018087606). Meta-analysis was performed to compare the efficacy of kinesio taping to other modalities of musculoskeletal disorders. As a result, 36 studies were included in the quantitative analysis. Kinesio taping was found to provide an improvement of both pain and disability when applied to any region of the body. In the first five days of application, kinesio taping significantly reduced the pain in all body regions (SMD = −0.63, 95%CI: −0.87, −0.39). This was also noted after four-to-six weeks of application (SMD = −0.76, 95%CI: −1.07, −0.45). When kinesio taping was used for disability in low back pain patients, it significantly reduced the disability within five days of application (SMD = −0.70, 95%CI: −1.29, −0.11). Finally, kinesio taping has shown an improvement of the disability in all body regions after four-to-six weeks of application (SMD = −0.59, 95%CI: −0.96, −0.22). Our findings support kinesio taping as an adjuvant to other treatments for musculoskeletal disorders.Research in Sports Medicine, 31(4), pp.416-439; 202

Factors associated with successful publication for systematic review protocol registration: an analysis of 397 registered protocols

Abstract Background Meta-analyses are on top of the evidence-based medicine pyramid, yet many of them are not completed after they are begun. Many factors impacting the publication of meta-analysis works have been discussed, and their association with publication likelihood has been investigated. These factors include the type of systematic review, journal metrics, h-index of the corresponding author, country of the corresponding author, funding sources, and duration of publication. In our current review, we aim to investigate these various factors and their impact on the likelihood of publication. A comprehensive review of 397 registered protocols retrieved from five databases was performed to investigate the different factors that might affect the likelihood of publication. These factors include the type of systematic review, journal metrics, h-index of the corresponding author, country of the corresponding author, funding sources, and duration of publication. Results We found that corresponding authors in developed countries and English-speaking countries had higher likelihoods of publication: 206/320 (p = 0.018) and 158/236 (p = 0.006), respectively. Factors affecting publications are the countries of corresponding author (p = 0.033), whether they are from developed countries (OR: 1.9, 95% CI: 1.2–3.1, p = 0.016), from English-speaking countries (OR: 1.8, 95% CI: 1.2–2.7, p = 0.005), update status of the protocol (OR: 1.6, 95% CI: 1.0–2.6, p = 0.033), and external funding (OR: 1.7, 95% CI: 1.1–2.7, p = 0.025). Multivariable regression retains three variables as significant predictors for the publication of a systematic review: whether it is the corresponding author from developed countries (p = 0.013), update status of the protocol (p = 0.014), and external funding (p = 0.047). Conclusion Being on top of the evidence hierarchy, systematic review and meta-analysis are the keys to informed clinical decision-making. Updating protocol status and external funding are significant influences on their publications. More attentions should be paid to the methodological quality of this type of publication

Association between pet ownership and cardiovascular risks and mortality: a systematic review and meta-analysis

The aim of the study was to determine the association between pet ownership and cardiovascular risk factors and mortality. Electronic search was conducted through nine databases including PubMed for relevant publications reporting cardiovascular events and mortality among pet owners. Meta-analysis was used to pool the results. Of a total of 2818 reports screened, 26 studies were included in our systematic review and meta-analysis. Higher survival rate was observed in the pet owners group after pooling nonadjusted and adjusted hazard ratios for cardiovascular mortality at 0.73 [95% confidence interval (CI) 0.62–0.86] and 0.81 (0.68–0.97), respectively. A similar trend was observed for the pooled nonadjusted hazard ratio for overall mortality 0.73 (0.62–0.87) but not the adjusted hazard ratio 0.40 (0.04–3.78). Cat owners have a reduction in cardiovascular mortality but not overall mortality after pooling the adjusted hazard ratio 0.79 (0.63–0.99) and 1.04 (0.90–1.21), respectively. However, no significant association between dog owners and survival rate was observed for overall and cardiovascular-specific mortality. Pet owners had significantly lower heart rate (mean difference 95% CI: −2.32 (−3.07 to −1.57), mean arterial pressure −2.60 (−4.25 to −0.95) and SBP −1.69 (−3.06 to −0.31) but not DBP −0.23 (−1.05 to 0.60). No significant difference was observed between pet owners and nonpet owners in prevalence of hypertension. Our study draws attention to the beneficial effects of the human--pet bond; therefore, we recommend pet acquisition for better cardiovascular outcomes after controlling for zoonotics and pet-induced allergies

KAP-COVIDGLOBAL: a multinational survey of the levels and determinants of public knowledge, attitudes and practices towards COVID-19

Objective The adherence to public health recommendations to control COVID-19 spread is influenced by public knowledge, attitudes and practices (KAP). We performed this cross-sectional study to assess the levels and determinants of public KAP towards COVID-19 in a large, multinational sample.Design Cross-sectional study (survey).Setting The questionnaire was distributed to potential respondents via online platforms.Participants 71 890 individuals from 22 countries.Methods We formulated a four-section questionnaire in English, followed by validation and translation into seven languages. The questionnaire was distributed (May to June 2020) and each participant received a score for each KAP section.Results Overall, the participants had fair knowledge (mean score: 19.24±3.59) and attitudes (3.72±2.31) and good practices (12.12±1.83) regarding COVID-19. About 92% reported moderate to high compliance with national lockdown. However, significant gaps were observed: only 68.2% knew that infected individuals may be asymptomatic; 45.4% believed that antibiotics are an effective treatment; and 55.4% stated that a vaccine has been developed (at the time of data collection). 71.9% believed or were uncertain that COVID-19 is a global conspiracy; 36.8% and 51% were afraid of contacting doctors and Chinese people, respectively. Further, 66.4% reported the pandemic had moderate to high negative effects on their mental health. Female gender, higher education and urban residents had significantly (p≤0.001) higher knowledge and practice scores. Further, we observed significant correlations between all KAP scores.Conclusions Although the public have fair/good knowledge and practices regarding COVID-19, significant gaps should be addressed. Future awareness efforts should target less advantaged groups and future studies should develop new strategies to tackle COVID-19 negative mental health effects

Relationships between social spending and childhood obesity in OECD countries: an ecological study

Objectives The burden of childhood obesity is clustered among children in low-socioeconomic groups. Social spending on children—public welfare expenditure on families and education—may curb childhood obesity by reducing socioeconomic disadvantages. The objective of this study was to examine the relationship between social spending on children and childhood obesity across the Organisation for Economic Cooperation and Development (OECD) countries.Design Ecological study.Setting Data on social spending on children were obtained from the OECD Social Expenditure Database and the OECD educational finance indicators dataset during 2000–2015. Data on childhood obesity were obtained from the NCD Risk Factor Collaboration database.Participants Aggregated statistics on obesity among children aged 5–19 years, estimated for OECD 35 countries based on the measured height and weight on 31.5 million children.Outcome measures Country-level prevalence of obesity among children aged 5–19 years.Results In cross-sectional analyses in 2015, social spending on children was inversely associated with the prevalence of childhood obesity after adjusting for potential confounders (the gross domestic product per capita, unemployment rate, poverty rate, percentage of children aged <20 years and prevalence of childhood obesity in 2000). In addition, when we focused on changes from 2000 to 2015, an average annual increase of US$100 in social spending per child was associated with a decrease in childhood obesity by 0.6 percentage points for girls (p=0.007) and 0.7 percentage points for boys (p=0.04) between 2000 and 2015, after adjusting for the potential confounders. The dimensions of social spending that contributed to these associations between the changes in social spending on children and childhood obesity were early childhood education and care (ECEC) and school education for girls and ECEC for boys.Conclusion Countries that increase social spending on children tend to experience smaller increases in childhood obesity