This research identified the key determinants and designed a novel Bayesian three-dimension convolution neural network (3D-CNN) for COVID-19 mass casualty incidents (MCI) triage recommendation.

109 articles between 2019 and 2022 were archived from MEDLINE databases. An empirical review and content analysis were done to find out the triage determinants and a Bayesian 3-D CNN model was designed for triage recommendation.

35 out of 109 articles were used. The severity of infection (signs and symptoms of coronavirus), likelihood of spreading (attitudes of pandemic spreading, personal behaviors, and government policy), and available resources (physician and medication availability, hospital vacancy, and evacuation assets) were the identified determinants. The likelihoods of having COVID-19 were calculated with a Bayesian network based on the parameters of the three determinants, and were pre-processed for training the 3D-CNN model with the COVID19 test result, recover history, and medication outcome for “immediate (hospital admission with immediate medical care)”, “delayed (quarantine center and observation)”, “minimal (home quarantine with medication)”, “semi-minimal (home quarantine without medication)”, or “no priority (no therapeutic resources)” triage recommendation.

The determinants and AI model classify patients to an optimal healthcare facility for reducing disaster medicine risk. The model verification and validation were undergoing.

To elucidate the association between financial challenges, healthcare needs, and their subsequent impact on individuals’ mental health, physical well-being, and quality of life.

ChiKobi Health conducted a market research survey consisting of twenty questions. 25 participants responded, providing insights into their emotional states due to health or financial situations, daily energy levels, mental health associations with financial and healthcare situations, overall quality of life, experiences with chronic pain, physical functioning, and interests in healthcare management services and holistic products.

Key findings indicate: 88% of respondents occasionally to often felt emotionally drained due to health or financial situations. 80% rated their overall quality of life as good to excellent, but 40% have experienced chronic pain that interfered with daily activities. 48% felt their physical health was occasionally to always hindered by financial or healthcare limitations. 60% expressed interest in personalized healthcare manager services and 84% in holistic medical products for preventative health needs.

Financial strain and healthcare challenges are significantly intertwined with individuals’ emotional and physical well-being. Given the current global challenges and climate change effects leading to more health-related crises, understanding these interrelationships is paramount for disaster medicine and public health efforts, particularly for vulnerable populations.

Each year, disasters impact over 50 million, and conflicts are indirectly related to 1,000,000 deaths. Traditionally, humanitarians help in two ways: Deployment: sending healthcare workers to provide direct care, and Development: training local healthcare workers. But these routes limit who can be reached and how quickly. We envision a scalable solution that moves beyond traditional humanitarian avenues to empower the public to save lives and reduce suffering through equitable, open-access education.

Provide the justification for just in time digital education.

Provide various examples of JIT education.

Summarize current JIT domestic and global initiatives.

In the field of cancer, many cancer patient associations (CPAs) have been established in Türkiye to support individuals living with cancer (ILCs) throughout the diagnosis and treatment processes. The presence of CPAs for ILCs became more significant after the major earthquakes in southeastern Türkiye in February 2023. The aim of this study is to identify the challenges of ILCs after the earthquakes from the perspective of CPA members.

This study employed a qualitative approach. The data collection method was in-depth interviews. Semi-structured, open-ended interviews were conducted with 15 volunteers who work with ILCs, selected through purposeful sampling. The data were analyzed by using inductive thematic analysis. This study was conducted between April and May 2023.

Three main themes (problems of ILCs caused by earthquakes, access to health care, future concerns) and 11 subthemes were extracted through analyzing interviews.

ILCs experienced diverse difficulties after earthquakes. Members of CPAs observed that acute interventions to injured people and humanitarian aid activities had the first-place importance after the earthquake, while cancer-related care took the second place, anticipating devastating outcomes for the future of their care. CPAs should be supported by the public, local governments, and central government in their endeavors for ILCs.

Kawasaki disease is an acute febrile disease causing systemic vasculitis that is common in infants and young children. This study was conducted to explore the relationships of the rs1412125, and rs2249825 single nucleotide polymorphisms of the high mobility group box 1 gene to Kawasaki disease and its complication of coronary artery injury.

In total, 200 children with Kawasaki disease (49 with coronary artery injury) and 200 healthy controls were enrolled in this study. Polymerase chain reaction was used to amplify the target gene, and direct sequencing was performed to determine distributions at the rs1412125 T/C and rs2249825 C/G loci in the HMGB1 gene. The chi-squared test was used to compare data between groups. Linkage disequilibrium coefficients and single nucleotide polymorphism haplotype analysis were conducted, and a false-positive report probability analysis was used to assess significant associations. Expression quantitative trait loci analysis was performed to determine if single nucleotide polymorphisms affected mRNA levels via the GTEx portal.

Significant differences in the genotype TT, TC, and CC distributions (χ2 = 7.918, P = 0.019) and allele T and C frequencies (χ2 = 6.125, P = 0.013) of rs1412125 T/C locus were found between the Kawasaki disease and healthy control groups. The genotype CC was associated with a greater Kawasaki disease risk [odds ratio = 3.205, 95% confidence interval = 1.352–7.595, χ2 = 7.560, P = 0.006]. C allele carriers had a higher Kawasaki disease risk than did T allele carriers (odds ratio = 1.469, 95% confidence interval = 1.083–1.993, χ2 = 6.125, P = 0.013). The rs1412125 genotype T/C distribution (χ2 = 10.906, P = 0.004) and allele frequencies (χ2 = 8.813, P = 0.003) differed significantly between patients with and without coronary artery injury. In the dominant model, the coronary artery injury risk was 3.006 times greater for patients with the TT genotype than for those with the other genotypes (odds ratio = 3.006, 95% confidence interval = 1.540–5.867, χ2 = 10.875, P = 0.001). No significant difference in the rs2249825 genotype C/G distribution or allele frequencies was found between the Kawasaki disease and control groups, or between the coronary artery injury and without coronary artery injury groups.

The rs1412125 polymorphism of the HMGB1 gene is associated with Kawasaki disease and its coronary artery injury complication. The CC genotype may be a risk factor for Kawasaki disease onset, and the TT genotype may be a risk factor for coronary artery injury in Kawasaki disease.

Cardiac intensive care providers require a comprehensive understanding of cardiac output and oxygen delivery. The estimation of cardiac output in clinical practice often relies on thermodilution and the Fick principle. Central venous saturation and lactate levels are commonly used indicators for cardiac output assessment. However, the relationship between venous lactate levels and venous oxygen saturation in paediatric cardiac intensive care patients remains unclear.

This is a single-centre retrospective pilot study aimed to investigate the correlation between venous lactate and venous oxygen saturation in paediatric patients. Data collected included venous saturation, heart rate, mean arterial blood pressure, arterial saturation by pulse oximetry, cerebral and renal near-infra-red spectroscopy values, and the presence of a functionally univentricular heart. Statistical analyses included Bayesian Pearson correlation and regression analyses.

A total of 203 data points from 37 unique patients were included in the analysis. There was no significant correlation between serum lactate and venous saturation (correlation coefficient = –0.01; Bayes factor 10 = 0.06). Serum lactate also did not correlate with other haemodynamic metrics. Venous saturation showed correlations with arterial saturation and cerebral and renal near-infra-red spectroscopy. Regression analysis revealed that parallel circulation, arterial saturation, and cerebral near-infra-red spectroscopy were predictive of venous saturation. The following equation resulted from the regression analysis: 68.0 – (12.7 x parallel circulation) – (0.8 x arterial saturation) + (0.3 x cerebral near-infra-red spectroscopy). This model had a Bayes factor 10 of 0.03 and adjusted R-squared was 0.29.

In paediatric cardiac intensive care patients, there is no significant correlation between venous lactate and venous saturation, suggesting that lactate may not be a reliable marker for assessing the adequacy of oxygen delivery in this population. Only a weak correlation could be identified once the venous saturation was 70% or lower. Additional research is needed to explore alternative markers for monitoring oxygen delivery in critically ill paediatric patients.