Stakeholder engagement to introduce a standardised register for improved inpatient care of newborns and sick children in Bangladesh.

Background: Despite a global decrease of 59% in under-five mortality rates from 1990 to 2021, child survival remains a pressing issue. This holds true for Bangladesh, as well. In response, the Government of Bangladesh introduced a standardised register for strengthening the inpatient management of newborns and sick children in 2021. Methods: We employed a comprehensive four-phase stakeholder engagement process to implement an inpatient register for newborns and sick children. The first stage included identifying and prioritising potential stakeholders at the national and district levels. We identified eight organisations involved in newborn and child health and selected 24 participants from various other sectors for workshops aimed at raising awareness about the register's introduction. These stakeholders also participated in the register's design, development strategies planning, and implementation phases. These phases were led by the 'National Newborn Health and IMCI programme' with support from various partners. A technical working group reviewed existing registers and helped prepare training materials. Feedback from each workshop was crucial in finalising the register. Results: The Government of Bangladesh has recognised the need for an indoor register for newborns and sick children, which was to be established in collaboration with development partners. This initiative can enhance the quality of care for sick children and increase service provider accountability. Due to its successful implementation, it will continue to be used in the Kushtia and Dinajpur districts, with plans for a nationwide scale-up. The Government has allocated funds in the next health sector programme for orientation and register printing. A strengths, weaknesses, opportunities, and threats (SWOT) analysis of the stakeholder engagement process highlighted strengths such as a context-specific approach and collaborative engagement, as well as challenges such as time resource requirements. Conclusions: Implementing an inpatient register for newborns and sick children through stakeholder engagement can effectively improve child health care services. Aside from challenges such as resource intensiveness and stakeholder commitments, success depended on the organising authority's expertise in relationship building, budget allocation, time management, and workforce dedication. Therefore, strategic planning, staff recruitment, networking, and budgeting are crucial for successful stakeholder engagement and health care initiatives.

Introducing a standardised register for strengthening the inpatient management of newborns and sick children: Implementation research in selected health facilities of Bangladesh.

Background: It is imperative to maintain accurate documentation of clinical interventions aimed at enhancing the quality of care for newborns and sick children. The National Newborn Health and IMCI programme of Bangladesh led the development of a standardised register for managing newborns and sick children under five years of age during inpatient care through stakeholder engagement. We aimed to assess the implementation outcomes of the standardised register in the inpatient department. Methods: We conducted implementation research in two district hospitals and two sub-district hospitals of Kushtia and Dinajpur districts from November 2022 to January 2023 to assess the implementation outcomes of the standardised register. We assessed the following World Health Organization implementation outcome variables: usability, acceptability, adoption (actual use), fidelity (completeness and accuracy), and utility (quality of care) of the register against preset benchmarks. We collected data through structured interviews with health care providers; participant enrolment; and data extraction from inpatient registers and case record forms. Results: The average usability and acceptability scores among health care providers were 73 (standard deviation (SD) = 14) and 82 (SD = 14) out of 100, respectively. The inpatient register recorded 96% (95% confidence interval (CI) = 95-97) of under-five children who were admitted to the inpatient department (adoption - actual use). The proportions of completed data elements in the inpatient register were above the preset benchmark of 70% for all the assessed data elements except 'investigation done' (24%; 95% CI = 23-26) (fidelity - completeness). The percentage agreements between government-appointed nurses posted and study-appointed nurses were above the preset benchmark of 70% for all the reported variables (fidelity - accuracy). The kappa coefficient for the overall level of agreement between these two groups regarding reported variables indicated moderate to substantial agreement. The proportion of newborns with sepsis receiving injectable antibiotics was 62% (95% CI = 47-75) (utility - quality of care). We observed some variability in the completeness and accuracy of the inpatient register by district and facility type. Conclusions: The inpatient register was positively received by health care providers, with evaluations of implementation outcome variables showing encouraging results. Our findings could inform evidence-based decision-making on the implementation and scale-up of the inpatient register in Bangladesh, as well as other low- and middle-income countries.

Prebiotic diet normalizes aberrant immune and behavioral phenotypes in a mouse model of autism spectrum disorder.

Autism spectrum disorder (ASD) is a cluster of neurodevelopmental disorders characterized by deficits in communication and behavior. Increasing evidence suggests that the microbiota-gut-brain axis and the likely related immune imbalance may play a role in the development of this disorder. Gastrointestinal deficits and gut microbiota dysfunction have been linked to the development or severity of autistic behavior. Therefore, treatments that focus on specific diets may improve gastrointestinal function and aberrant behavior in individuals with ASD. In this study, we investigated whether a diet containing specific prebiotic fibers, namely, 3% galacto-oligosaccharide/fructo-oligosaccharide (GOS/FOS; 9:1), can mitigate the adverse effects of in utero exposure to valproic acid (VPA) in mice. Pregnant BALB/cByJ dams were injected with VPA (600 mg/kg, sc.) or phosphate-buffered saline (PBS) on gestational day 11 (G11). Male offspring were divided into four groups: (1) in utero PBS-exposed with a control diet, (2) in utero PBS-exposed with GOS/FOS diet, (3) in utero VPA-exposed with a control diet, and (4) in utero VPA-exposed with GOS/FOS diet. Dietary intervention started from birth and continued throughout the duration of the experiment. We showed that the prebiotic diet normalized VPA-induced alterations in male offspring, including restoration of key microbial taxa, intestinal permeability, peripheral immune homeostasis, reduction of neuroinflammation in the cerebellum, and impairments in social behavior and cognition in mice. Overall, our research provides valuable insights into the gut-brain axis involvement in ASD development. In addition, dietary interventions might correct the disbalance in gut microbiota and immune responses and, ultimately, might improve detrimental behavioral outcomes in ASD.

ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application.

Chronic kidney diseases (CKDs) are a significant public health issue with potential for severe complications such as hypertension, anemia, and renal failure. Timely diagnosis is crucial for effective management. Leveraging machine learning within healthcare offers promising advancements in predictive diagnostics. In this paper, we developed a machine learning-based kidney diseases prediction (ML-CKDP) model with dual objectives: to enhance dataset preprocessing for CKD classification and to develop a web-based application for CKD prediction. The proposed model involves a comprehensive data preprocessing protocol, converting categorical variables to numerical values, imputing missing data, and normalizing via Min-Max scaling. Feature selection is executed using a variety of techniques including Correlation, Chi-Square, Variance Threshold, Recursive Feature Elimination, Sequential Forward Selection, Lasso Regression, and Ridge Regression to refine the datasets. The model employs seven classifiers: Random Forest (RF), AdaBoost (AdaB), Gradient Boosting (GB), XgBoost (XgB), Naive Bayes (NB), Support Vector Machine (SVM), and Decision Tree (DT), to predict CKDs. The effectiveness of the models is assessed by measuring their accuracy, analyzing confusion matrix statistics, and calculating the Area Under the Curve (AUC) specifically for the classification of positive cases. Random Forest (RF) and AdaBoost (AdaB) achieve a 100% accuracy rate, evident across various validation methods including data splits of 70:30, 80:20, and K-Fold set to 10 and 15. RF and AdaB consistently reach perfect AUC scores of 100% across multiple datasets, under different splitting ratios. Moreover, Naive Bayes (NB) stands out for its efficiency, recording the lowest training and testing times across all datasets and split ratios. Additionally, we present a real-time web-based application to operationalize the model, enhancing accessibility for healthcare practitioners and stakeholders. Web app link: https://rajib-research-kedney-diseases-prediction.onrender.com/.

Evaluation of THz wave transmission performance in TOPAS-based heptagonal photonic crystal fiber (He-PCF).

PCF denotes photonic crystal fiber which is utilized for terahertz (THz) waveguides and cladding in the shape of a hexagon with two elliptical air apertures (AHs), which are discussed. Such differentiation is made: When the frequency is 1 THz, effective material loss (EML) to a minimum of 0.028 cm-1 has been achieved. Making use of the heptagonal photonic crystal fiber (He-PCF) architecture, every simulation result utilizing COMSOL Multiphysics software implements the perfectly match layer (PML) and finite element method (FEM) boundary conditions. The He-PCF fiber demonstrates an effective mode loss (EML) of 0.028 cm-1 that is negligible, a substantial effective area (EA) measuring 7.31 × 10-8 m2 and an 80 % power concentration encompassing the central area at 1 THz frequency. Furthermore, regarding crucial optical guiding aspects like confinement loss, dispersion, and modality, a small study with respect to power fraction along with effective mode area (EMA) has again been conducted. Here, He-PCF THz waveguide is anticipated to provide a notable improvement in the current design for the communication field. Moreover, our suggested the PCF demonstrates perception by a solitary mode, as indicated through the utilization of the V-parameter, across a range in frequency spanning among 0.80 and 3 THz. Thus, it is anticipated that the layout of He-PCF fibers will facilitate efficient transmission of terahertz (THz) signals in a variety of communication applications.

Nutritional characteristics and antiradical activity of turmeric (Curcuma longa L.), beetroot (Beta vulgaris L.), and carrot (Daucus carota L.) grown in Bangladesh.

Curcuma longa L. (turmeric), Beta vulgaris L. (beetroot), and Daucus carota L. (carrot) grown in Bangladesh were analyzed for nutritional and phytochemical contents to reveal their comparative nutritional compositions and antiradical properties. Ash, protein, and carbohydrate content were significantly preeminent in beetroot as compared to others. Whereas fat content was found to be high in turmeric, carrots contained a great percentage of crude fiber. Beetroot was shown to have much greater potassium, calcium, and iron levels than others. Regarding amino acids, glutamic acid was found to be greater in beetroot and carrot whereas turmeric had significantly high aspartic acid content. Leucine had the highest concentration among essential amino acids in these three samples. Total antioxidant activity, total flavonoids, and phenolic contents in the methanolic extract of turmeric were found to be substantially higher than in beetroot and carrot. Furthermore, the extract of turmeric (IC50 value: 13.46 µg/mL) scavenged 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) free radicals considerably to a greater extent than beetroot (IC50 value: 380.61 µg/mL) and carrot (IC50 value: 1252.85 µg/mL). A positive correlation was found between the phytochemical contents and antiradical activity. The information from this study will help to find the potential ingredients from these plants for functional food.

Animal Models for Studying Protein-Bound Uremic Toxin Removal-A Systematic Review.

Protein-bound uremic toxins (PBUTs) are associated with the progression of chronic kidney disease (CKD) and its associated morbidity and mortality. The conventional dialysis techniques are unable to efficiently remove PBUTs due to their plasma protein binding. Therefore, novel approaches are being developed, but these require validation in animals before clinical trials can begin. We conducted a systematic review to document PBUT concentrations in various models and species. The search strategy returned 1163 results for which abstracts were screened, resulting in 65 full-text papers for data extraction (rats (n = 41), mice (n = 17), dogs (n = 3), cats (n = 4), goats (n = 1), and pigs (n = 1)). We performed descriptive and comparative analyses on indoxyl sulfate (IS) concentrations in rats and mice. The data on large animals and on other PBUTs were too heterogeneous for pooled analysis. Most rodent studies reported mean uremic concentrations of plasma IS close to or within the range of those during kidney failure in humans, with the highest in tubular injury models in rats. Compared to nephron loss models in rats, a greater rise in plasma IS compared to creatinine was found in tubular injury models, suggesting tubular secretion was more affected than glomerular filtration. In summary, tubular injury rat models may be most relevant for the in vivo validation of novel PBUT-lowering strategies for kidney failure in humans.

Integrated gene expression profiling and functional enrichment analyses to discover biomarkers and pathways associated with Guillain-Barré syndrome and autism spectrum disorder to identify new therapeutic targets.

Guillain-Barré syndrome (GBS) is one of the most prominent and acute immune-mediated peripheral neuropathy, while autism spectrum disorders (ASD) are a group of heterogeneous neurodevelopmental disorders. The complete mechanism regarding the neuropathophysiology of these disorders is still ambiguous. Even after recent breakthroughs in molecular biology, the link between GBS and ASD remains a mystery. Therefore, we have implemented well-established bioinformatic techniques to identify potential biomarkers and drug candidates for GBS and ASD. 17 common differentially expressed genes (DEGs) were identified for these two disorders, which later guided the rest of the research. Common genes identified the protein-protein interaction (PPI) network and pathways associated with both disorders. Based on the PPI network, the constructed hub gene and module analysis network determined two common DEGs, namely CXCL9 and CXCL10, which are vital in predicting the top drug candidates. Furthermore, coregulatory networks of TF-gene and TF-miRNA were built to detect the regulatory biomolecules. Among drug candidates, imatinib had the highest docking and MM-GBSA score with the well-known chemokine receptor CXCR3 and remained stable during the 100 ns molecular dynamics simulation validated by the principal component analysis and the dynamic cross-correlation map. This study predicted the gene-based disease network for GBS and ASD and suggested prospective drug candidates. However, more in-depth research is required for clinical validation.Communicated by Ramaswamy H. Sarma.

17 common differentially expressed genes (DEGs) were identified from 693 DEGs of the GBS dataset (GSE72748) and 365 DEGs of the ASD dataset (GSE113834), which is the preliminary part of this investigation.From the PPI network analysis, a total of 10 hub genes were identified and two common DEGs named CXCL9 and CXCL10 were found in both the hub gene and essential module analysis.The identified leading pathways and GO pathways, TF-gene interaction, and TF-miRNAs network has made the process more relevant and appropriate for suggesting probable drug candidates.Among the drug candidates, imatinib was suggested as the main drug candidate due to its interaction with the hub gene CXCL9 and CXCL10 and lower p value than the other candidates. It showed the highest binding affinity score and remained stable with the CXCR3 chemokine receptor.

Bioengineered Kidney Tubules Efficiently Clear Uremic Toxins in Experimental Dialysis Conditions.

Patients with end-stage kidney disease (ESKD) suffer from high levels of protein-bound uremic toxins (PBUTs) that contribute to various comorbidities. Conventional dialysis methods are ineffective in removing these PBUTs. A potential solution could be offered by a bioartificial kidney (BAK) composed of porous membranes covered by proximal tubule epithelial cells (PTECs) that actively secrete PBUTs. However, BAK development is currently being hampered by a lack of knowledge regarding the cytocompatibility of the dialysis fluid (DF) that comes in contact with the PTECs. Here, we conducted a comprehensive functional assessment of the DF on human conditionally immortalized PTECs (ciPTECs) cultured as monolayers in well plates, on Transwell® inserts, or on hollow fiber membranes (HFMs) that form functional units of a BAK. We evaluated cell viability markers, monolayer integrity, and PBUT clearance. Our results show that exposure to DF did not affect ciPTECs' viability, membrane integrity, or function. Seven anionic PBUTs were efficiently cleared from the perfusion fluid containing a PBUTs cocktail or uremic plasma, an effect which was enhanced in the presence of albumin. Overall, our findings support that the DF is cytocompatible and does not compromise ciPTECs function, paving the way for further advancements in BAK development and its potential clinical application.

Infection prevention and control for COVID-19 response in the Rohingya refugee camps in Bangladesh: an intra-action review.

BACKGROUND: Infection Prevention and Control (IPC) is critical in controlling the COVID-19 pandemic and is one of the pillars of the WHO COVID-19 Strategic Preparedness and Response Plan 2020. We conducted an Intra-Action Review (IAR) of IPC response efforts to the COVID-19 pandemic in Cox's Bazar, Bangladesh, to identify best practices, challenges, and recommendations for improvement of the current and future responses. METHODS: We conducted two meetings with 54 participants purposively selected from different organizations and agencies involved in the frontline implementation of IPC in Cox's Bazar district, Bangladesh. We used the IPC trigger questions from the WHO country COVID-19 IAR: trigger question database to guide the discussions. Meeting notes and transcripts were then analyzed manually using content analysis, and results were presented in text and quotes. RESULTS: Best practices included: assessments, a response plan, a working group, trainings, early case identification and isolation, hand hygiene in Health Facilities (HFs), monitoring and feedback, general masking in HFs, supportive supervision, design, infrastructure and environmental controls in Severe Acute Respiratory Infection Isolation and Treatment Centers (SARI ITCs) and HFs and waste management. Challenges included: frequent breakdown of incinerators, limited PPE supply, inconsistent adherence to IPC, lack of availability of uniforms for health workers, in particular cultural and gender appropriate uniforms and Personal Protective Equipment (PPE). Recommendations from the IAR were: (1) to promote the institutionalization of IPC, programs in HFs (2) establishment of IPC monitoring mechanisms in all HCFs, (3) strengthening IPC education and training in health care facilities, and (4) strengthen public health and social measures in communities. CONCLUSION: Establishing IPC programmes that include monitoring and continuous training are critical in promoting consistent and adaptive IPC practices. Response to a pandemic crisis combined with concurrent emergencies, such as protracted displacement of populations with many diverse actors, can only be successful with highly coordinated planning, leadership, resource mobilization, and close supervision.

Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning.

The immense growth of the population generates a polluted environment that must be managed to ensure environmental sustainability, versatility and efficiency in our everyday lives. Particularly, the municipality is unable to cope with the increase in garbage, and many urban areas are becoming increasingly difficult to manage. The advancement of technology allows researchers to transmit data from municipal bins using smart IoT (Internet of Things) devices. These bin data can contribute to a compelling analysis of waste management instead of depending on the historical dataset. Thus, this study proposes forecasting models comprising of 1D CNN (Convolutional Neural Networks) long short-term memory (LSTM), gated recurrent units (GRU) and bidirectional long short-term memory (Bi-LSTM) for time series prediction of public bins. The execution of the models is evaluated by Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Coefficient determination (R2) and Root Mean Squared Error (RMSE). For different numbers of epochs, hidden layers, dense layers, and different units in hidden layers, the RSME values measured for 1D CNN, LSTM, GRU and Bi-LSTM models are 1.12, 1.57, 1.69 and 1.54, respectively. The best MAPE value is 1.855, which is found for the LSTM model. Therefore, our findings indicate that LSTM can be used for bin emptiness or fullness prediction for improved planning and management due to its proven resilience and increased forecast accuracy.

The Autism Spectrum Disorder-Associated Bacterial Metabolite p-Cresol Derails the Neuroimmune Response of Microglial Cells Partially via Reduction of ADAM17 and ADAM10.

The bacterial metabolite 4-methylphenol (para-cresol or p-cresol) and its derivative p-cresyl sulfate (pCS) are elevated in the urine and feces of children with autism spectrum disorder (ASD). It has been shown that p-cresol administration induces social behavior deficits and repetitive behavior in mice. However, the mechanisms of p-cresol, specifically its metabolite pCS that can reach the brain, in ASD remain to be investigated. The pCS has been shown to inhibit LPS-stimulated inflammatory response. A Disintegrin And Metalloprotease 10 (ADAM10) and A Disintegrin And Metalloprotease 17 (ADAM17) are thought to regulate microglial immune response by cleaving membrane-bound proteins. In the present study, a neuroinflammation model of LPS-activated BV2 microglia has been used to unveil the potential molecular mechanism of pCS in ASD pathogenesis. In microglial cells pCS treatment decreases the expression or maturation of ADAM10 and ADAM17. In addition, pCS treatment attenuates TNF-α and IL-6 releases as well as phagocytosis activity of microglia. In in vitro ADAM10/17 inhibition experiments, either ADAM10 or ADAM17 inhibition reduces constitutive and LPS-activated release of TNF-α, TNFR-1 and IL-6R by microglial cells, while it increases constitutive and LPS-activated microglial phagocytotic activity. The in vivo results further confirm the involvement of ADAM10 and ADAM17 in ASD pathogenesis. In in utero VPA-exposed male mice, elevated concentration in serum of p-cresol-associated metabolites pCS and p-cresyl glucuronide (pCG) is associated with a VPA-induced increased ADAM10 maturation, and a decreased ADAM17 maturation that is related with attenuated levels of soluble TNF-α and TGF-ß1 in the mice brain. Overall, the present study demonstrates a partial role of ADAM10 and ADAM17 in the derailed innate immune response of microglial cells associated with pCS-induced ASD pathogenesis.

A Uremic Pig Model for Peritoneal Dialysis.

With increasing interest in home dialysis, there is a need for a translational uremic large animal model to evaluate technical innovations in peritoneal dialysis (PD). To this end, we developed a porcine model with kidney failure. Stable chronic kidney injury was induced by bilateral subtotal renal artery embolization. Before applying PD, temporary aggravation of uremia was induced by administration of gentamicin (10 mg/kg i.v. twice daily for 7 days), to obtain uremic solute levels within the range of those of dialysis patients. Peritoneal transport was assessed using a standard peritoneal permeability assessment (SPA). After embolization, urea and creatinine concentrations transiently increased from 1.6 ± 0.3 to 7.5 ± 1.2 mM and from 103 ± 14 to 338 ± 67 µM, respectively, followed by stabilization within 1-2 weeks to 2.5 ± 1.1 mM and 174 ± 28 µM, respectively. Gentamicin induced temporary acute-on-chronic kidney injury with peak urea and creatinine concentrations of 16.7 ± 5.3 mM and 932 ± 470 µM respectively. PD was successfully applied, although frequently complicated by peritonitis. SPA showed a low transport status (D/P creatinine at 4 h of 0.41 (0.36-0.53)) with a mass transfer area coefficient of 9.6 ± 3.1, 4.6 ± 2.6, 3.4 ± 2.3 mL/min for urea, creatinine, and phosphate respectively. In conclusion, this porcine model with on-demand aggravation of uremia is suitable for PD albeit with peritoneal transport characterized by a low transport status.

Molecular Docking and Dynamics Simulation of Natural Compounds from Betel Leaves (Piper betle L.) for Investigating the Potential Inhibition of Alpha-Amylase and Alpha-Glucosidase of Type 2 Diabetes.

Piper betle L. is widely distributed and commonly used medicinally important herb. It can also be used as a medication for type 2 diabetes patients. In this study, compounds of P. betle were screened to investigate the inhibitory action of alpha-amylase and alpha-glucosidase against type 2 diabetes through molecular docking, molecular dynamics simulation, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The molecule apigenin-7-O-glucoside showed the highest binding affinity among 123 (one hundred twenty-three) tested compounds. This compound simultaneously bound with the two-target proteins alpha-amylase and alpha-glucosidase, with high molecular mechanics-generalized born surface area (MM/GBSA) values (ΔG Bind = -45.02 kcal mol-1 for alpha-amylase and -38.288 for alpha-glucosidase) compared with control inhibitor acarbose, which had binding affinities of -36.796 kcal mol-1 for alpha-amylase and -29.622 kcal mol-1 for alpha-glucosidase. The apigenin-7-O-glucoside was revealed to be the most stable molecule with the highest binding free energy through molecular dynamics simulation, indicating that it could compete with the inhibitors' native ligand. Based on ADMET analysis, this phytochemical exhibited a wide range of physicochemical, pharmacokinetic, and drug-like qualities and had no significant side effects, making them prospective drug candidates for type 2 diabetes. Additional in vitro, in vivo, and clinical investigations are needed to determine the precise efficacy of drugs.

Green synthesis of silver nanoparticles using Cinnamomum tamala (Tejpata) leaf and their potential application to control multidrug resistant Pseudomonas aeruginosa isolated from hospital drainage water.

Green Synthesis of Metal Nanoparticles is becoming a more common method for producing nanoparticles with a diameter of 1-100 nm that may be employed in a variety of medical applications. The antibacterial efficacy of silver nanoparticles (AgNPs) derived from Cinnamomum tamala (Tejpata) leaf extract against antibiotic-resistant Pseudomonas aeruginosa is investigated in this study. Green AgNP synthesis is safe, cost-effective, and ecologically friendly. The biosynthesized AgNPs were studied using UV-Visible spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), Dynamic Light Scattering (DLS), X-ray Diffraction (XRD), and Transmission Electron Microscopy (TEM). The AgNPs were virtually spherical, with an average size of 25-30 nm, according to TEM observations. Biochemical and molecular identification were used to isolate multidrug-resistant P. aeruginosa from the hospital's drainage water. The antibacterial potential of AgNPs against P. aeruginosa is determined using the agar diffusion method. Silver nanoparticles produced from Cinnamomum tamala (Tejpata) leaf extract were shown to be effective in inhibiting four strains of P. aeruginosa. According to the agar disc diffusion method, AgNPs had the largest inhibition zone of 17.67 ± 0.577 mm, while aqueous extract had 5.67 ± 0.5777 mm, indicating that AgNPs had antibacterial activity. This study on AgNPs might assist with managing multidrug resistant pathogenic bacteria and be a possible source of medicinal application due to its potential antibacterial effect.

Introducing pulse oximetry for outpatient management of childhood pneumonia: An implementation research adopting a district implementation model in selected rural facilities in Bangladesh.

Background: Pulse oximetry has potential for identifying hypoxaemic pneumonia and substantially reducing under-five deaths in low- and middle-income countries (LMICs) setting. However, there are few examples of introducing pulse oximetry in resource-constrained paediatric outpatient settings, such as Integrated Management of Childhood Illness (IMCI) services. Methods: The National IMCI-programme of Bangladesh designed and developed a district implementation model for introducing pulse oximetry in routine IMCI services through stakeholder engagement and demonstrated the model in Kushtia district adopting a health system strengthening approach. Between December 2020 and June 2021, two rounds of assessment were conducted based on WHO's implementation research framework and outcome variables, involving 22 IMCI service-providers and 1680 children presenting with cough/difficulty-in-breathing in 12 health facilities. The data collection procedures included structured-observations, re-assessments, interviews, and data-extraction by trained study personnel. Findings: We observed that IMCI service-providers conducted pulse oximetry assessments on all eligible children in routine outpatient settings, of which 99% of assessments were successful; 85% (95% CI 83,87) in one attempt, and 69% (95% CI 67,71) within one minute. The adherence to standard operating procedure related to pulse oximetry was 92% (95% CI 91,93), and agreement regarding identifying hypoxaemia was 97% (95% CI 96,98). The median performance-time was 36 seconds (IQR 20,75), which was longer among younger children (2-11 months: 44s, IQR 22,78; 12-59 months: 30s, IQR 18,53, p < 0.01) and among those classified as pneumonia/severe-pneumonia than as no-pneumonia (41s, IQR 22,70; 32s, IQR 20,62, p < 0.01). We observed improvements in almost all indicators in round-2. IMCI service-providers and caregivers showed positive attitudes towards using this novel technology for assessing their children. Interpretation: This implementation research study suggested the adoption, feasibility, fidelity, appropriateness, acceptability, and sustainability of pulse oximetry introduction in routine IMCI services in resource-poor settings. The learning may inform the evidence-based scale-up of pulse oximetry linked with an oxygen delivery system in Bangladesh and other LMICs. Funding: This research was funded by the UK National Institute for Health Research (NIHR) (Global Health Research Unit on Respiratory Health (RESPIRE); 16/136/109) using UK aid from the UK Government to support global health research.

Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor.

Human Activity Recognition (HAR) systems are devised for continuously observing human behavior - primarily in the fields of environmental compatibility, sports injury detection, senior care, rehabilitation, entertainment, and the surveillance in intelligent home settings. Inertial sensors, e.g., accelerometers, linear acceleration, and gyroscopes are frequently employed for this purpose, which are now compacted into smart devices, e.g., smartphones. Since the use of smartphones is so widespread now-a-days, activity data acquisition for the HAR systems is a pressing need. In this article, we have conducted the smartphone sensor-based raw data collection, namely H-Activity, using an Android-OS-based application for accelerometer, gyroscope, and linear acceleration. Furthermore, a hybrid deep learning model is proposed, coupling convolutional neural network and long-short term memory network (CNN-LSTM), empowered by the self-attention algorithm to enhance the predictive capabilities of the system. In addition to our collected dataset (H-Activity), the model has been evaluated with some benchmark datasets, e.g., MHEALTH, and UCI-HAR to demonstrate the comparative performance of our model. When compared to other models, the proposed model has an accuracy of 99.93% using our collected H-Activity data, and 98.76% and 93.11% using data from MHEALTH and UCI-HAR databases respectively, indicating its efficacy in recognizing human activity recognition. We hope that our developed model could be applicable in the clinical settings and collected data could be useful for further research.

Success and time implications of SpO2 measurement through pulse oximetry among hospitalised children in rural Bangladesh: Variability by various device-, provider- and patient-related factors.

Background: Hypoxaemia is one of the strongest predictors of mortality among children with pneumonia. It can be identified through pulse oximetry instantaneously, which is a non-invasive procedure but can be influenced by factors related to the specific measuring device, health provider and patient. Following WHO's global recommendation in 2014, Bangladesh decided to introduce pulse oximetry in paediatric outpatient services, ie, the Integrated Management of Childhood Illness (IMCI) services in 2019. A national committee updated the existing IMCI implementation package and decided to test it by assessing the pulse oximetry performance of different types of assessors in real-life inpatient settings. Methods: We adopted an observational design and conducted a technology assessment among children admitted to a rural district hospital. Eleven nurses and seven paramedics received one-day training on pulse oximetry as assessors. Each assessor performed at least 30 pulse oximetry measurements on children with two types of handheld devices. The primary outcome of interest was obtaining a successful measurement of SpO2, defined as observing a stable (±1%) reading for at least 10 seconds. Performance time, ie, time taken to obtain a successful measurement of SpO2 was considered the secondary outcome of interest. In addition, we used Generalized Estimating Equation to assess the effect of different factors on the pulse oximetry performance. Results: The assessors obtained successful measurements of SpO2 in all attempts (n = 1478) except one. The median time taken was 30 (interquartile range (IQR) = 22-42) seconds, and within 60 seconds, 92% of attempts were successful. The odds of obtaining a successful measurement within 60 seconds were 7.3 (95% confidence interval (CI) = 3.7-14.2) times higher with a Masimo device than a Lifebox device. Similarly, assessors aged >25 years were 4.8 (95% CI = 1.2, 18.6) times more likely to obtain a successful measurement within 60 seconds. The odds of obtaining a successful measurement was 2.6 (95% CI = 1.6, 4.2) times higher among children aged 12-59 months compared to 2-11 months. Conclusions: Our study indicated that assessors could achieve the necessary skills to perform pulse oximetry successfully in real-life inpatient settings through a short training module, with some effect of device-, provider- and patient-related factors. The National IMCI Programme of Bangladesh can use these findings for finalising the national IMCI training modules and implementation package incorporating the recommendation of using pulse oximetry for childhood pneumonia assessment.

Introducing pulse oximetry in routine IMCI services in Bangladesh: A context-driven approach to influence policy and programme through stakeholder engagement.

Background: Pneumonia is the leading cause of under-five child deaths globally and in Bangladesh. Hypoxaemia or low (<90%) oxygen concentration in the arterial blood is one of the strongest predictors of child mortality from pneumonia and other acute respiratory infections. Since 2014, the World Health Organization recommends using pulse oximetry devices in Integrated Management of Childhood Illness (IMCI) services (outpatient child health services), but it was not routinely used in most health facilities in Bangladesh until 2018. This paper describes the stakeholder engagement process embedded in an implementation research study to influence national policy and programmes to introduce pulse oximetry in routine IMCI services in Bangladesh. Methods: Based on literature review and expert consultations, we developed a conceptual framework, which guided the planning and implementation of a 4-step stakeholder engagement process. Desk review, key informant interviews, consultative workshops and onsite demonstration were the key methods to involve and engage a wide range of stakeholders. In the first step, a comprehensive desk review and key informant interviews were conducted to identify stakeholder organisations and scored them based on their power and interest levels regarding IMCI implementation in Bangladesh. In the second step, two national level, two district level and five sub-district level sensitisation workshops were organised to orient all stakeholder organisations having high power or high interest regarding the importance of using pulse oximetry for pneumonia assessment and classification. In the third step, national and district level high power-high interest stakeholder organisations were involved in developing a joint action plan for introducing pulse oximetry in routine IMCI services. In the fourth step, led by a formal working group under the leadership of the Ministry of Health, we updated the national IMCI implementation package, including all guidelines, training manuals, services registers and referral forms in English and Bangla. Subsequently, we demonstrated its use in real-life settings involving various levels of (national, district and sub-district) stakeholders and worked alongside the government leaders towards carefully resuming activities despite the COVID-19 pandemic. Results: Our engagement process contributed to the national decision to introduce pulse oximetry in routine child health services and update the national IMCI implementation package demonstrating country ownership, government leadership and multi-partner involvement, which are steppingstones towards scalability and sustainability. However, our experience clearly delineates that stakeholder engagement is a context-driven, time-consuming, resource-intensive, iterative, mercurial process that demands meticulous planning, prioritisation, inclusiveness, and adaptability. It is also influenced by the expertise, experience and positionality of the facilitating organization. Conclusions: Our experience has demonstrated the value and potential of the approach that we adopted for stakeholder engagement. However, the approach needs to be conceptualised coupled with the allocation of adequate resources and time commitment to implement it effectively.

An Observational Study of Paediatric Preoperative Transfusion Practice in a Resource-Limited Setting.

BACKGROUND: Paediatric anaemia is highly prevalent in low-middle-income countries and can negatively impact postoperative outcomes. Currently, there are no guidelines for the management of paediatric preoperative anaemia. To ensure optimal care in resource-limited settings: balancing the risks of anaemia and using resources such as blood transfusion, we first need to understand current practices. To address this, a joint UK-Bangladesh team conducted an observational study at a paediatric surgical centre in Bangladesh. METHODS: A total of 464 patients ≤16 years who underwent elective and emergency surgery were categorised into major (351/464), moderate (92/464) and minor (21/464) surgery groups according to anticipated blood loss. Preoperative anaemia testing and transfusion was assessed retrospectively through patient notes. RESULTS: Median age was 4 years and 73% were male. 32.5% (151/464) patients had preoperative blood testing for anaemia. 17.5% (81/464) children were transfused preoperatively. Of those children transfused, 40.7% (33/81) underwent transfusion solely based on visible signs of anaemia on clinical examination. Seventy-five percentage (36/48) of children who underwent transfusion after blood testing had haemoglobin ≥80 g/L. Major surgery category had the highest proportion of children who were transfused and tested for anaemia. CONCLUSION: A liberal transfusion approach is evident here. Discussion with local clinicians revealed that this was due to limitations in obtaining timely blood results and reduction in laboratory costs incurred by families when clinical suspicion of anaemia was high. Further research is needed to analyse the potential of using bedside haemoglobin testers in conjunction with patient blood management strategies to limit blood transfusions and its associated risks.