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Spatial-temporal evolution of the allometric relationship between urban economic and health resources in the Yangtze River Delta urban agglomeration
The evolution of the spatiotemporal relationship between urban economic growth and health resources within the Yangtze River Delta urban agglomeration provides an important context for understanding the regional development dynamics in China. Previous studies focused on equity in health-resource allocation and service efficiency, often overlooking the allometric growth relationships between health resources and economic variables. This study employs an allometric growth model to elucidate the changing interactions between the number of medical beds, doctors, and urban economic indicators in the Yangtze River Delta region from 2009 to 2022. Employing Zipf’s law and allometric growth modeling, this study analyzed growth trends and revealed significant differences in resource allocation and size changes over time. The main findings suggest that, although resource centralization is a general trend, differences persist, especially in less economically developed regions. This study innovatively introduces an allometric growth model that offers a new perspective on understanding the mechanisms of regional health-resource growth and underscores the significant influence of economic factors on health-resource allocation. This study significantly contributes to the sustainability of urban health systems and provides theoretical support for policy formulations aimed at optimizing the allocation of health resources and strengthening regional economic strategies in the Yangtze River Delta region.
Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms
Background Stunting is a vital indicator of chronic undernutrition that reveals a failure to reach linear growth. Investigating growth and nutrition status during adolescence, in addition to infancy and childhood is very crucial. However, the available studies in Ethiopia have been usually focused in early childhood and they used the traditional stastical methods. Therefore, this study aimed to employ multiple machine learning algorithms to identify the most effective model for the prediction of stunting among adolescent girls in Ethiopia. Methods A total of 3156 weighted samples of adolescent girls aged 15–19 years were used from the 2016 Ethiopian Demographic and Health Survey dataset. The data was pre-processed, and 80% and 20% of the observations were used for training, and testing the model, respectively. Eight machine learning algorithms were included for consideration of model building and comparison. The performance of the predictive model was evaluated using evaluation metrics value through Python software. The synthetic minority oversampling technique was used for data balancing and Boruta algorithm was used to identify best features. Association rule mining using an Apriori algorithm was employed to generate the best rule for the association between the independent feature and the targeted feature using R software. Results The random forest classifier (sensitivity = 81%, accuracy = 77%, precision = 75%, f1-score = 78%, AUC = 85%) outperformed in predicting stunting compared to other ML algorithms considered in this study. Region, poor wealth index, no formal education, unimproved toilet facility, rural residence, not used contraceptive method, religion, age, no media exposure, occupation, and having one or more children were the top attributes to predict stunting. Association rule mining was identified the top seven best rules that most frequently associated with stunting among adolescent girls in Ethiopia. Conclusion The random forest classifier outperformed in predicting and identifying the relevant predictors of stunting. Results have shown that machine learning algorithms can accurately predict stunting, making them potentially valuable as decision-support tools for the relevant stakeholders and giving emphasis for the identified predictors could be an important intervention to halt stunting among adolescent girls.
Occurrence of virulence genes in multidrug-resistant Escherichia coli isolates from humans, animals, and the environment: One health perspective
Escherichia coli is one of the critical One Health pathogens due to its vast array of virulence and antimicrobial resistance genes. This study used multiplex PCR to determine the occurrence of virulence genes bfp, ompA, traT, eaeA, and stx1 among 50 multidrug-resistant (MDR) E. coli isolates from humans (n = 15), animals (n = 29), and the environment (n = 6) in Dar es Salaam, Tanzania. Their association with antimicrobial-resistant genes (ARGs) was determined using Principal Component Analysis (PCA). All 50/50 (100%) MDR E. coli isolates carried at least one virulence gene, with 19/50 (38%) carrying four genes, bfp + traT + eaeA + ompA. The findings showed a high occurrence of virulence genes bfp (82%), traT (82%), eaeA (78%), and ompA (72%); the study detected no stx1 in any of the isolates. In humans, the most detected virulence genes were bfp and traT 14/15 (93.3%); for poultry, it was eaeA 13/14 (92.9%); for pigs, was bfp and traT 13/15 (86.7%); while for river water, it was eaeA 6/6 (100%). The study observed no significant association between virulence genes and ARGs. PCA results show the genes ompA, traT, eaeA, and bfp contributed to the virulence of the isolates, and blaTEM, blaCTX-M, and qnrs contributed to ARGs. The PCA ellipses show that isolates from pigs had more virulence genes than those isolated from poultry, river water, and humans. The high frequency of numerous virulence genes in MDR E. coli isolates from humans, animals, and the environment indicates that these isolates have a very high potential to cause diseases that are difficult to treat because they are MDR.
RETRACTED: The green response of financial inclusion, infrastructure development and renewable energy to the environmental sustainability: A newly evidence from OECD economies
Recently, economic environmental degradation is being considered a leading chellenge in forefront of policy analysts. Thus, the present study introduces core environmental determinants such as infrastructure development, finacail inclusion, gross domestic product, population, and renewable energy consumption. Financial inclusion (FI) is crucial for attaining a environment. The present study selects the Organization for Economic Co-operation and Development (OECD) over period of 2004–2022. The results show that financial inclusin, infrastructure development(ID), and renewable energy (RE) play a vital influence in decreasing carbon emissions. The OECD nations should surge their investment in renewable energy and infrastructure development. Furthermore, to ensure long-term environmental sustainability, it is imperative to broaden the scope of FI. Thus, the inclusion of green infrastructure is essential in order to shift from the utilization of fossil fuels to RE sources. Similarly, policymakers should incorporate FI into climate actions at the local, national, and regional levels. However, it is crucial to promote the economic shift towards RE sources in order to mitigate the environmental impact from humn and economic activities. This study is conducive to the execution of the United Nations (UN) Sustainable Development Goals (SDG).
Determining patient activity goals and their fulfillment following total knee arthroplasty: Findings from the prospective, observational SuPeR Knee study
Background Dissatisfaction with Total Knee Arthroplasty (TKA) surgical outcomes remains between 10–20% and is associated with higher levels of societal costs. Expectations regarding post-surgical outcomes is considered as one of the major factors influencing satisfaction, however, there are no standardised methods for assessing patient’s expectations regarding activities to be achieved following surgery. Objectives The aims of this study were to identify patient expectations relating to activities of importance following TKA and to describe goal fulfillment at 3 months post-TKA. We hypothesised that activity expectation fulfillment would be associated with overall satisfaction with TKA outcomes. Methods This study comprised secondary data analysis of findings from the SuPeR Knee study. Using conventional content analysis, a classification system of activities specific to our TKA patient cohort was created. At 3 months following TKA, patients rated satisfaction with fulfilling activity goals and pain attenuation. The average level of satisfaction achieved was used as our measure of goal fulfillment. Overall satisfaction of the outcomes of surgery was rated using a 5-point Likert scale and the association between goal fulfillment and overall surgery satisfaction was compared by Spearman’s rank correlation. Results Data were collected from 861 TKA patients. Recreation and sporting pursuits were found to be important activity types (43% of all activities). At 3 months after surgery, less impactful activities were more commonly satisfied (67%), including domestic and vocational activities, low impact hobbies and leisure activities. Goal fulfillment and improvement in knee pain were both significantly positively correlated to, and significant predictors of, overall patient satisfaction (p≤0.001). Conclusions Our Australian cohort of TKA patients have a range of expectations for undertaking high-impact activities after surgery. However, at 3 months after surgery, higher rates of satisfaction were attained for lower-impact activities. Our findings support the importance of identifying activity expectations for each patient and that fulfillment of these goals contributes to overall satisfaction with the outcomes of TKA.
A study on the monitoring of LNAPL migration using ERT
This study employs electrical resistivity tomography (ERT) to experimentally investigate the migration characteristics of light non-aqueous phase liquids (LNAPL) under various groundwater conditions. Through cross-hole measurements and time-lapse inversion, the migration process of LNAPL under three scenarios—unsaturated conditions, constant groundwater levels, and declining water levels—was systematically analyzed. The results indicate that LNAPL migration behavior exhibits significant differences under different conditions. Under unsaturated conditions, the vertical migration rate of LNAPL gradually decreases over time, with an average rate of 1.06 cm/h, and is influenced by preferential migration pathways formed in coarse-grained regions. At constant water levels, the migration of LNAPL is significantly constrained by the groundwater level, spreading horizontally near the water table after reaching it, with an average rate of 0.51 cm/h. When the groundwater level declines, LNAPL migrates rapidly downward along preferential flow paths, with an average rate increasing to 1.45 cm/h. Miller Soil Box experiments further reveal the relationship between LNAPL content and electrical resistivity, showing that an increase in LNAPL can significantly alter soil resistivity, especially under low moisture conditions. Overall, this study confirms the monitoring advantages of ERT technology for LNAPL migration behavior under different conditions and provides important references for remediation strategies at contaminated sites.
Physical climate risk: Stock price reactions to the historically most extreme European and United States heat waves since 1979
Climate change has heightened the need to understand physical climate risks, such as the increasing frequency and severity of heat waves, for informed financial decision-making. This study investigates the financial implications of extreme heat waves on stock returns in Europe and the United States. Accordingly, the study combines meteorological and stock market data by integrating methodologies from both climate science and finance. The authors use meteorological data to ascertain the five strongest heat waves since 1979 in Europe and the United States, respectively, and event study analyses to capture their effects on stock prices across firms with varying levels of environmental performance. The findings reveal a marked increase in the frequency of heat waves in the 21st century, reflecting global warming trends, and that European heat waves generally have a higher intensity and longer duration than those in the United States. This study provides evidence that extreme heat waves reduce stock values in both regions, with portfolio declines of up to 3.1%. However, there are marked transnational differences in investor reactions. Stocks listed in the United States appear more affected by the most recent heat waves compared to those further in the past, whereas the effect on European stock prices is more closely tied to event intensity and duration. For the United States sample only, the analysis reveals a mitigating effect of high corporate environmental performance against heat risk. This study introduces an innovative interdisciplinary methodology, merging meteorological precision with financial analytics to provide deeper insights into climate-related risks.
Travel medicine training and experience among primary care physicians in Qatar
Background Travel medicine (TM) focuses on preventing and managing travel-related issues. Evidence has become more important than expert opinions in the development of TM standards. This study aimed to evaluate the training and experience of TM among Primary Care Physicians (PCPs) in Qatar and their associated factors. Methods A cross-sectional study design was employed. A structured questionnaire was utilized to gather data from all PCPs working in publicly funded primary health centers. Results The study involved 360 PCPs (response rate: 89.5%). Of these, 42.3% reported postgraduate training (15.1%) or experience (27.5%) in TM, with common training forms including workshops (67%), postgraduate programs (24%), and short courses (15%). About 81.8% expressed interest in TM training. Regarding confidence in practicing TM, 20% felt very confident, while 50% felt moderately confident. In practice, 25.8% conducted comprehensive pre-travel risk assessments, and 22.5% responded to traveler queries without formal consultations. Multivariable logistic regression analysis showed that PCPs who graduated from medical schools in Arab countries, conducting more than ten TM consultations per month, performing comprehensive pre-travel assessments, and those expressing high confidence were more likely to be associated with TM training or experience. Conclusion Many PCPs in Qatar lack prior training and experience in TM, raising concerns about their ability to provide adequate care to traveling patients. There is a significant need for targeted TM training for PCPs, especially since the majority express a keen interest in receiving such training.
Analysis of spatiotemporal distribution, variability, and trends of rainfall in Wollo area, Northeastern Ethiopia
Ethiopia’s agriculture is mostly dependent on rain, though the rainfall distribution and amount are varied in spatiotemporal context. The study was conducted to analyze the distribution, trends, and variability of monthly, seasonal, and annual rainfall data over the Wollo area from 1981 to 2022. To accomplish this, the study utilized the Climate Hazards Group Infrared Precipitation with Stations version two (CHIRPS-v2) data. Standard Rainfall Anomaly Index (SRA) and Coefficient of Variation (CV) were employed to examine rainfall variability and develop drought indices over southern Ethiopia. The Modified Mann Kendall (MMK) test, Sen’s slope estimator and the innovative trend analysis (ITA) were employed to detect temporal changes in rainfall trends over the study period. The study found that the area experienced considerable rainfall variability and change, resulting in extended drought and flood events within the study period. Results from SRA and CV revealed interannual and seasonal rainfall variability, with the proportions of years below and above the long-term mean being estimated at 56% and 44%, respectively. The MMK test showed that the annual rainfall during the Kiremt (summer-main rainy season) had an increasing trend. On the other hand, rainfall for the Belg (short rain season for the study area) season and the Bega (winter) season showed a significantly decreasing trend (p < 0.05). Results from the innovative trend analysis (ITA) also revealed that the annual and seasonal rainfall trends exhibited different trends in varied magnitude for different stations. On a spatial basis, the eastern and northeastern regions of the study area showed trends of increasing rainfall during the Kiremt (JJA). Decision-makers and development planners need to design strategies to mitigate the risks posed by changes in rainfall variability and distribution and enhance community adaptation and mitigation capacities in Wollo, Ethiopia.
Estimating the prevalence of adults at risk for advanced hepatic fibrosis using FIB-4 in a Swiss tertiary care hospital
Background & aims Chronic liver diseases pose a serious public health issue. Identifying patients at risk for advanced liver fibrosis is crucial for early intervention. The Fibrosis-4 score (FIB-4), a simple non-invasive test, classifies patients into three risk groups for advanced fibrosis. This study aimed to estimate the prevalence of patients at risk for advanced hepatic fibrosis at a Swiss tertiary care hospital by calculating the FIB-4 score in routine blood analysis. Methods A retrospective study was conducted using data from 36,360 patients who visited outpatient clinics at eight main clinics of the University Hospital Bern in Switzerland. The data collection period ran from January 1st to December 31st, 2022. Patients attending the hepatology outpatient clinic were excluded. We then calculated the overall and clinic-specific prevalence of patients falling into the high risk category for advanced fibrosis according to FIB-4. Results Among the 36,360 patients, 26,245 (72.2%) had a low risk of advanced fibrosis (FIB-4 <1.3), whereas 3913 (10.8%) and 2597 (7.1%) patients were flagged to have a high risk of advanced fibrosis (FIB-4 >2.67 and FIB-4 >3.25 respectively). Geriatrics and Cardiology had the highest proportions of patients at risk for advanced fibrosis over all clinics. Conclusions This study demonstrates a high prevalence of high FIB-4 score in a Swiss tertiary care hospital. The implementation of the automatically generated FIB-4 score in daily practice, not only in primary care, but also within tertiary care hospitals, could be crucial for early identification of outpatients at high risk of advanced liver fibrosis requiring further hepatological investigations.
Distribution and habitat of the painted tree rat (Callistomys pictus): Evaluating areas for future surveys and conservation efforts
Knowledge of the potential distribution and locations of poorly known threatened species is crucial for guiding conservation strategies and new field surveys. The painted tree-rat (Callistomys pictus) is a monospecific, rare, and endangered echimyid rodent endemic to the southern Bahia Atlantic Forest in Brazil. There have been no records of the species published in the last 20 years, and the region has experienced significant forest loss and degradation. According to the IUCN, only 13 specimens had been previously reported, with 12 found in the north of Ilhéus and adjacent municipalities, and one recorded approximately 200 km away from this region, suggesting that its distribution might be wider. We aimed to search for unpublished and more recent records of the C. pictus, by consulting the gray literature (including Environmental Impact Study (EIA) reports, Brazilian Red Lists, and management plans of protected areas), scientific collections, online databases, and mastozoologists working in the region. We estimated the species’ potential distribution using Ecological Niche Modeling to identify regions, municipalities, and protected areas most likely to support this species, based on factors such as climate suitability and forest cover. We reported three new sightings of the species, including the first within a protected area. We estimated suitable climate conditions across 23,151 km2, of which 9,225 km2 has a high potential for harboring the species. The area between Itacaré and Valença needs more extensive survey efforts as it has high habitat suitability and only one record has been confirmed there so far. Meanwhile, the region between Una and Ilhéus urgently requires habitat conservation initiatives. While the species may have a broader distribution than previously thought, its known occurrences are limited to a few locations, and suitable habitats are underrepresented in protected areas. Additionally, the rarity of sightings continues to indicate a concerning conservation status.
Hydraulic performance of a pre-aerated stilling basin: Experimental study
Spillway chutes are critical in dam flood control, particularly in high dams where high water heads and large discharge in narrow canyons amplify the demand for safe discharging. For large unit discharges in spillways, aeration protection is essential to prevent cavitation erosion, but challenges arise from air duct choking in the traditional spillway and nonaerated regions in the stepped spillway. This paper introduces a novel spillway called the pre-aerated stilling basin spillway (PSBS). The primary distinction between PSBS and conventional spillways lies in the placement of aeration facilities. Conventional spillways feature a curved transition section that directly connects to the spillway. In contrast, the PSBS is equipped with a WES crest weir and a vertical sill of the same width, which converts supercritical to subcritical flow. This process strongly entrains air through hydraulic jumps at spillway entrances, thereby preventing cavitation damage. The study aims to experimentally investigate the flow regime, energy dissipation within the PSB, and the near-wall air concentration to ensure effective mitigation of cavitation damage downstream. The findings highlight the impact of the PSB on changing the jump type and relative local energy loss, influenced by the incoming Froude number, sill height, and sill length. Influenced by these factors, the variation in air concentration is crucial for reducing cavitation damage, necessitating potential adjustments in prototype applications to account for scale effects. Under such a pre-aeration approach, the air concentration along the downstream spillway warrants further investigation for the continuous optimization of the PSB’s design and its integration with spillways.
Maize quality detection based on MConv-SwinT high-precision model
The traditional method of corn quality detection relies heavily on the subjective judgment of inspectors and suffers from a high error rate. To address these issues, this study employs the Swin Transformer as an enhanced base model, integrating machine vision and deep learning techniques for corn quality assessment. Initially, images of high-quality, moldy, and broken corn were collected. After preprocessing, a total of 20,152 valid images were obtained for the experimental samples. The network then extracts both shallow and deep features from these maize images, which are subsequently fused. Concurrently, the extracted features undergo further processing through a specially designed convolutional block. The fused features, combined with those processed by the convolutional module, are fed into an attention layer. This attention layer assigns weights to the features, facilitating accurate final classification. Experimental results demonstrate that the MC-Swin Transformer model proposed in this paper significantly outperforms traditional convolutional neural network models in key metrics such as accuracy, precision, recall, and F1 score, achieving a recognition accuracy rate of 99.89%. Thus, the network effectively and efficiently classifies different corn qualities. This study not only offers a novel perspective and technical approach to corn quality detection but also holds significant implications for the advancement of smart agriculture.
‘‘Mitigating cancer pain: What else matters?”—A qualitative study into the needs and concerns of cancer patients in Sri Lanka
Objectives In Sri Lanka, cancer is a significant contributor to both morbidity and mortality rates. In 2022, 33,243 new cancer cases were reported, resulting in an age- standardized incidence rate of 106.9 per 100,000 individuals. The overall experience of cancer pain reflects patients’ needs and concerns. Therefore, a thorough understanding of the patient’s needs and concerns is crucial to implementing satisfactory pain outcomes. This study aims to explore the needs and concerns of patients with cancer pain in Sri Lanka. Methods This study employed a descriptive qualitative approach among purposively selected patients with cancer and registered at the pain management unit. Participants recruited were 18 years or older with cancer-related pain. Noncancerous pain and those with psychological disorders, and brain metastases were excluded. Twenty-one semi-structured interviews were conducted until data saturation using a semi-structured interview guide, each lasting 30–60 minutes. Data were analyzed by Graneheim and Lundman’s content analysis method. Results The study primarily involved participants aged 51–60 Sinhalese Buddhists. It highlighted two main themes: ’Changes in normal lifestyle’ and ’Needs and expectations’. The ’Changes in normal lifestyle’ theme included subthemes like ’Functional limitations’, ’Emotional reactions’, ’altered interpersonal relationships’, and ’Socio-financial problems’. The ’Needs and expectations’ theme covered desires for a ’Pain-free life’, a return to a ’Normal lifestyle’, and the ’Need for a caregiver’. The findings emphasize that the most significant issue for cancer patients is the disruption to their normal lifestyle due to various challenges, while their primary need is to live without pain. Conclusions ‘Life without pain’ is a cancer sufferer’s greatest need while ’changes in normal lifestyle’ owing to bio-psycho-social-spiritual problems is their primary concern.
Anatomical description and digital reconstruction of the skull of Jeholosaurus shangyuanensis (Dinosauria, Ornithopoda) from China
Ornithopod dinosaurs appeared during the Middle Jurassic, but it was in the Lower Cretaceous they started their successful evolutionary history. Different phylogenies describing the evolutionary relationships of Ornithopoda are mostly based on cranial features, however there is a lack of well-preserved and complete skulls for the basal member of the clade, hampering our knowledge on the mode and tempo of these herbivorous dinosaurs. Here we describe YLSNHM 01942, a well-preserved skull of a juvenile neornithischian from the Liaoning Province of China. The specimen was scanned with a μCT scan, and all the elements were segmented and extrapolated for description. The specimen shows a ventral deformation due to the compression of the sediment, and a few rostral elements were artificially added. The specimen is attributed to the basal ornithopod Jeholosaurus shangyuanensis because of the presence of a large foramen in the quadratojugal, however it lacks the nodular ornamentation on the postorbital and jugal, herein interpreted as an ontogenetic feature. This, together with the disarticulation degree of the cranial elements, suggest YLSNHM 01942 represents a juvenile Jeholosaurus. The endosseous labyrinth is tentatively reconstructed, although the disarticulation of the neurocranial bones hampers its complete reconstruction. Thanks to the analysis of previously undescribed inner neurocranial bones (such as the prootics, the exoccipital/ophistotic, basioccipital, and basisphenoid), we improve the previous phylogenetical scoring for J. shangyuanensis, and perform a phylogenetical analysis adding the basal ornithopod Changmiania liaoningensis and the recently re-evaluated Ajkaceratops kozmai. The phylogenetical analysis reports a well-supported base of Ornithopoda, with C. liaoningensis as the most basal ornithopod, and a resolved topology for Nanosaurus agilis, Changchunsaurus parvus, Haya griva, Yandusaurus hongheensis and J. shangyuanensis.
Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal
This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using only self-reported survey data. Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. To train and test the model, we used data from 2,133 students attending schools in a Portuguese municipality. Poor oral health (the dependent variable) was defined as having a Decayed, Missing, and Filled Teeth index for deciduous teeth (dmft) or permanent teeth (DMFT) above expert-defined thresholds (dmft/DMFT ≥ 3 or 4). The survey provided information about the students’ oral health habits, knowledge, beliefs, and food and physical activity habits, which served as independent variables. Logistic regression models with variables selected through low-variance filtering and recursive feature elimination outperformed various others trained with complex machine learning algorithms based on precision@k metric, outperforming also random selection and expert rule-based models in identifying students with poor oral health. The proposed models are inherently explainable, broadly applicable, which given the context, could compensate their lower performance (Area Under the Curve = 0.64—0.70) compared to similar approaches and models. This study is one of the few in oral health care that includes bias auditing of classification models. The audit surfaced potential biases related to demographic factors such as age and social assistance status. Addressing these biases without significantly compromising model performance remains a challenge. The results confirm the feasibility of survey-based machine learning models for identifying individuals with poor oral health, but further validation of this approach and pilot testing in field trials are necessary.
Multi-scenario land use change simulation and spatial-temporal evolution of carbon storage in the Yangtze River Delta region based on the PLUS-InVEST model
Influenced by urban expansion, population growth, and various socio-economic activities, land use in the Yangtze River Delta (YRD) area has undergone prominent changes. Modifications in land use have resulted in adjustments to ecological structures, leading to subsequent fluctuations in carbon storage. This study focuses on YRD region and analyzes the characteristics of land use changes in the area using land use data from 2000 to 2020, with a 10-year interval. Utilizing InVEST Model’s Carbon Storage module in combination with PLUS model (patch-generating land use simulation), we simulated and projected future land use patterns and carbon storage across YRD region under five scenarios including natural development (ND), urban development (UD), ecological protection (EP), cropland protection (CP), and balanced development (BD). Upon comparing carbon storage levels predicted for 2030 under the five scenarios with those in 2020, carbon stocks decrease in the initial four scenarios and then increase in the fifth scenario. In the initial four declining scenarios, CP scenario had the least reduction in carbon storage, followed by EP scenario. The implementation of policies aimed at safeguarding cropland and preserving ecological integrity can efficaciously curtail the expansion of developed land into woodland and cropland, enhance the structure of land use, and mitigate the loss of carbon storage.
Treatment of refractory poly articular course juvenile idiopathic arthritis with tofacitinib: Extended experience from Bangladesh
Background Juvenile Idiopathic arthritis (JIA) is one of the most common chronic diseases in children. It still remains a challenge to treat refractory poly-articular course JIA patients, especially in Bangladesh, where patients from low socio-economic backgrounds are unable to manage biological agents. Tofacitinib is one of the alternative options to biological agents, which can be taken orally and is cost effective. The purpose of this prospective observational study was to evaluate the efficacy of tofacitinib in the treatment of refractory poly-articular course JIA cases. Materials and methods This study was carried out in the Department of Pediatrics, Bangabandhu Sheikh Mujib Medical University (BSMMU). A total number of 50 refractory polyarticular course JIA patients received JAK-2 inhibitor, tofacitinib along with other drugs according to the recommended doses. The disease activity level was measured by Juvenile Arthritis Disease Activity Score-27 (JADAS-27). All the cases were assessed at baseline, 6th, 12th and52nd week of tofacitinib therapy. The relevant statistical tests were applied for data analysis. Results After treating the refractory cases with tofacitinib, arthritis subsided, and laboratory parameters improved in all the cases. Overall JADAS-27 score improvement was 40.67%, 56.38% and 96% at 6th, 12th and 52nd week of follow-up respectively. It was also possible to taper the dose of steroid gradually and stopped it by 24 weeks. Tofacitinib was well tolerated with minimum side effects. Conclusions Tofacitinib was effective to all the children with poly-articular course JIA. It was well tolerated and had very few tolerable adverse effects.
High-flow nasal cannula for pre- and apneic oxygenation during rapid sequence induction intubation in emergency surgery: A systematic review and meta-analysis
Background Rapid sequence induction intubation (RSII) is commonly used in emergency surgeries for patients at high risk of aspiration. However, these patients are more susceptible to hypoxemia during the RSII process. High-flow nasal cannula (HFNC) oxygen therapy has emerged as a potential alternative to traditional face mask (FM) ventilation pre- and apneic oxygenation. This meta-analysis aimed to evaluate the efficacy of HFNC compared to FM during RSII in emergency surgeries. Methods We conducted a comprehensive literature search across PubMed-MEDLINE, EMBASE-OVID, Scopus, and Web of Science databases up to July 20, 2024. Randomized controlled trials comparing HFNC with FM during RSII for emergency surgery patients were included. The primary outcomes were post-intubation arterial partial pressures of oxygen (PaO2) and carbon dioxide (PaCO2). Secondary outcomes included post-intubation end-tidal carbon dioxide concentration (EtCO2), incidence of desaturation, apnea time, lowest peripheral oxygen saturation (Lowest SpO2), and occurrence of regurgitant aspiration. We used the GRADE approach to assess the certainty of evidence and the Cochrane Risk of Bias 2 (RoB 2) tool to evaluate risk of bias. Findings This meta-analysis encompassed six studies, involving a total of 703 patients. HFNC oxygen therapy demonstrated a significant increase in post-intubation arterial PaO2 compared to FM (mean difference = 63.02 mmHg, 95% CI: 8.99 to 117.05, p = 0.02), while no significant difference was observed in arterial PaCO2. Moreover, HFNC substantially prolonged apnea time (mean difference = 19.25 seconds, 95% CI: 1.69 to 36.82, p = 0.03). No statistically significant differences were found between HFNC and FM regarding EtCO2, incidence of desaturation, Lowest SpO2, or regurgitant aspiration. Conclusion This systematic review and meta-analysis indicates that HFNC may be superior to FM for pre-oxygenation and apneic oxygenation during RSII in emergency surgeries, particularly in improving oxygenation. While these findings are promising, further high-quality research is necessary to establish definitive guidelines for HFNC use in this context.