Search Results (345)

In densely populated and traffic-congested major cities, medical emergency rescue incidents occur frequently, making the use of drones for emergency medical supplies delivery a new emergency distribution method. However, establishing drone transportation networks in urban areas requires balancing spatiotemporal fluctuations in emergency needs, meeting hospitals’ mandatory constraints on response time, and addressing factors like airspace restrictions and weather impacts. By analyzing the spatiotemporal distribution characteristics of medical emergency logistics in large cities, this study constructs a drone base station location optimization model integrating dynamic and static factors. The model combines multi-source data including emergency needs, geographic information, and airspace limitations. It employs kernel density estimation to identify hotspot areas, uses DBSCAN clustering to detect long-term stable demand hotspots, and applies LSTM methods to predict short-term and sudden demand fluctuations. The model optimizes coverage rate, response time, and cost budget control for drone transportation networks through a multi-objective genetic algorithm. Using Guangzhou as a case study, the results demonstrate that through “dynamic-static” collaborative deployment and multi-model drone coordination, the network achieves 96.18% demand coverage with an average response time of 673.38 s, significantly outperforming traditional vehicle transportation. Sensitivity analysis and robustness testing further validate the model’s effectiveness in handling demand fluctuations, weather changes, and airspace restrictions. This research provides theoretical support and decision-making basis for scientific planning of urban medical emergency drone transportation networks, offering practical significance for enhancing urban emergency rescue capabilities. Full article

Background/Objectives: Aspiration pneumonia is among the most frequent medical complications after intracerebral hemorrhage (ICH), yet its role during the ultra-early emergency department (ED) phase remains poorly understood. This study aimed to identify clinical and neurological factors independently associated with radiologically confirmed aspiration pneumonia in patients presenting with acute spontaneous ICH and to evaluate its association with early clinical outcomes. Methods: A retrospective observational cohort study was conducted in the neuro-emergency department of a large tertiary university hospital. All consecutive adults with spontaneous ICH confirmed by neuroimaging between January 2020 and December 2023 were included. Univariable and multivariable logistic regression models were used to identify independent predictors of pneumonia. Results: A total of 184 patients were analyzed (median age 74 years; 46% female). Radiologically confirmed aspiration pneumonia occurred in 37 patients (22.0%). Pneumonia was significantly associated with lower GCS, higher National Institutes of Health Stroke Scale (NIHSS) and ICH scores, shorter ED stay, and more frequent endotracheal intubation (ETI). In multivariable analysis, ETI (OR 5.42, 95% CI 1.57–18.63, p = 0.007), higher NIHSS score (OR 1.09, 95% CI 1.01–1.20, p = 0.047), and shorter ED stay (OR 0.97, 95% CI 0.95–0.99, p = 0.035) were independently associated with pneumonia. Aspiration pneumonia was not independently associated with neurosurgical referral (p = 0.082) or low GCS at discharge (p = 0.650). Conclusions: In this neuro-emergency cohort, aspiration pneumonia was common and strongly associated with neurological severity, particularly with endotracheal intubation and higher NIHSS scores. Although it did not independently predict early neurological deterioration or neurosurgical transfer, it identifies a critical period in which preventive measures—such as dysphagia screening, oral hygiene, and careful airway management—should be systematically applied. Larger multicenter studies with longer follow-up are needed to better define its long-term clinical consequences after ICH. Full article

Background: Patients with colorectal cancer (CRC) have varying responses to 5-fluorouracil (5-FU) treatment, particularly reduced-dose regimens. Inflammatory and tumor-associated serum biomarkers, such as carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), and cancer antigen 125, may refine prognostic assessment. However, their combined performance in patients with CRC receiving reduced-dose 5-FU remains understudied. This retrospective study evaluated the prognostic value of multiple biomarkers in these patients, aiming to identify optimal combinations for personalized therapeutic strategies and improved clinical outcomes. Methods: Data (2017–2023) on patients’ clinicopathological characteristics and pretreatment serum biomarker levels were collected from a medical center in central Taiwan. Dose classification followed institutional standards. Reduced-dose chemotherapy was confirmed from patients’ medical records. Intergroup comparisons, receiver operating characteristic curve analysis, logistic regression, Cox proportional hazards modeling, and survival analysis were performed. Furthermore, a multivariate prognostic nomogram was constructed. Results: The study cohort comprised 95 patients receiving reduced-dose 5-FU. Univariate analyses highlighted cigarette smoking, advanced stage, poor tumor differentiation, and elevated pretreatment CEA level as significant predictors of mortality. Multivariate analysis indicated tumor differentiation grade and pretreatment CEA level as significant independent predictors. Cancer antigen 125, CEA, and CA19-9 exhibited robust discriminatory performance. The multivariate nomogram exhibited acceptable discrimination. Conclusions: Tumor differentiation, disease stage, and pretreatment CEA level emerged as independent predictors of overall survival in patients with CRC receiving reduced-dose 5-FU. Serum biomarkers, particularly CEA and CA19-9, may be included in comprehensive prognostic models alongside clinicopathological characteristics. The validated prognostic nomogram may support personalized risk stratification and individualized dose-adjusted chemotherapy. Full article

Building a sustainable and resilient humanitarian logistics system is essential for reducing disaster losses and supporting long-term socio-economic recovery. Following a major disaster, rapidly organizing casualty evacuation while maintaining system robustness is a fundamental component of sustainable emergency management. This study develops a two-stage robust optimization model for designing a sustainable humanitarian logistics network that simultaneously accounts for two critical post-disaster uncertainties: (i) interruption risks at temporary medical points and (ii) uncertain casualty demand. By explicitly differentiating deprivation costs between mild and serious injuries, the model quantifies human suffering in monetary terms, thereby integrating social and economic sustainability considerations into the optimization framework. A customized column-and-constraint generation (C&CG) algorithm with proven finite convergence is proposed to ensure tractability and practical applicability. Using the 2008 Wenchuan earthquake as a real-world case study, involving 10 affected areas and 10 candidate temporary medical points, the results demonstrate that the proposed approach yields evacuation plans that remain feasible under all tested worst-case realizations, substantially reducing deprivation costs compared with existing benchmarks. The findings highlight that strategically increasing the capacity of key temporary medical nodes enhances the sustainability and resilience of the emergency medical system, offering evidence-based insights for designing sustainable and robust disaster-response strategies. Full article

Background/Objectives: Biologic therapies have transformed the management of inflammatory bowel disease (IBD), but their high cost has prompted the introduction of biosimilars. Although switching from biologic originators to biosimilars is increasingly common, real-world evidence remains limited. We aimed to explore the safety and efficacy of switching between biologic originators and biosimilars. Methods: We conducted a retrospective chart review of patients with IBD between 2015 and 2025. Adult patients receiving adalimumab-adaz or adalimumab-atto were included. Patients who were non-medically switched once from adalimumab originator (Humira^®) to any biosimilar were classified as group A. Patients who also switched back to originator (multiple switches) were classified as group B. The outcomes of the study were safety and efficacy of the biosimilars. Logistic regression identified switching predictors. Results: A total of 237 patients were included in the study. The number of patients in group A and group B was 208 and 58 patients, respectively. Sustained clinical remission was achieved in 198 (95.4%) of group A and 54 (93.6%) of group B participants. Sustained normalization of inflammatory markers was also comparable, occurring in 190 (91.5%) of group A and 54 (92.3%) of group B participants. No treatment-emergent AEs, infections, or treatment discontinuations were reported in either group (0%). Regression analysis identified older age and prior immunomodulator use as significant predictors of switching. Conclusions: Multiple switches of adalimumab biosimilars can be safely undertaken without increasing the risk of adverse reactions or treatment failure. This study provides meaningful evidence to guide policy and physician confidence in biosimilar interchangeability as a sustainable IBD therapeutic strategy. Full article

The rapid growth of web-based applications has attracted increasing attention from cybercriminals, particularly within the expanding field of the internet of transportation things, which has diverse applications across industries such as healthcare. As internet of transportation things technologies are adopted more widely, significant challenges emerge, particularly regarding data and service security. Hackers are specifically targeting sensitive medical data during the transportation of health emergency services, with internet of transportation things devices utilized for remote patient monitoring, medical equipment tracking, and logistics optimization. This research aims to tackle these security concerns by evaluating the risks associated with maintaining data integrity in healthcare emergency services. The research also utilizes a symmetrical fuzzy decision-making methodology, Fuzzy ANP-TOPSIS, to evaluate diverse security concerns associated with the internet of transportation things, with an emphasis on healthcare applications. The case study of seven alternatives reveals that mediXcel electronic medical records are the most viable solution, whilst the Caresoft system for hospital information is considered the least effective. The findings provide critical insights for improving the security of internet of transportation things applications and assuring their seamless integration into healthcare, especially in emergency services, hence protecting patient data and fostering user confidence. Full article

Background: Adequate folate intake before and during early pregnancy is essential for neural tube defect (NTD) prevention. In 2023, the Polish Society of Gynecologists and Obstetricians updated national recommendations, emphasizing the use of L-5-methyltetrahydrofolate (5-MTHF). Evidence on women’s awareness of these guidelines is limited. Methods: This cross-sectional online survey (2025) included 188 Polish women aged 18–45 years who were currently pregnant or had been pregnant within the previous 12 months. Knowledge, attitudes, and supplementation practices were compared between women with (n = 94) and without infertility (n = 94). Group differences were assessed using χ² tests, and predictors of 5-MTHF use were examined with multivariable logistic regression. Results: General awareness of folate recommendations was high (98.9%). However, detailed knowledge varied substantially. Women with infertility more frequently recognized different folate forms (87.2% vs. 72.3%; p = 0.018), knew the role of the MTHFR gene (77.7% vs. 39.4%; p < 0.001), and initiated supplementation ≥3 months before conception (88.3% vs. 47.9%; p < 0.001). Overall, 66% reported using 5-MTHF. Independent predictors of choosing 5-MTHF included awareness of folate forms, MTHFR knowledge, and awareness of emerging considerations related to folic acid metabolism. Infertility status was not an independent predictor. Conclusions: Although folate supplementation was nearly universal in this selective sample, more advanced knowledge—particularly regarding folate forms and genetic aspects of folate metabolism—remained limited. Higher awareness among women with infertility likely reflects greater exposure to medical supervision rather than inherent differences between groups. These findings may represent early signals of how the 2023 Polish recommendations are disseminating among women who are more engaged with health information, highlighting the need for continued public and professional education to support informed use of folate supplements. Full article

Background: Patients presenting to the Emergency Department (ED) with amphetamine-type stimulant (ATS) use can exhibit a wide range of symptoms, ranging from mild agitation to life-threatening dysrhythmias. Early identification of patients at risk for more severe medical complications after ATS use is a key challenge in emergency care. Objective: To identify clinical and demographic predictors associated with a medical condition among patients presenting to the ED after ATS use. Methods: Retrospective cohort study of patients who presented to the ED with suspected ATS use at a large academic community hospital in Ontario from 1 September 2016 to 31 August 2017. Patients were screened using ICD-10 codes and included if they had a positive drug screen and clinical suspicion for ATS use. Our primary outcome was a composite of recognized complications of ATS toxicity. Predictor variables included age, sex, employment status, mental illness or substance use history, ED administration of benzodiazepines, antipsychotics, or physical restraints. Multivariable logistic regression was used to assess associations. Results: Of 1591 charts reviewed, 128 (8%) met the inclusion criteria. The median age was 29.5 years (interquartile range [IQR]: 23–36), and 50.8% were female. In adjusted analyses, benzodiazepine administration was significantly associated with a medical condition (Odds Ratio [OR] 3.33; 95% CI: 1.31–8.45; p = 0.011) as was employment status (OR 9.30; 95% CI: 1.00–86.03; p = 0.019). Conclusions: Benzodiazepine administration and unemployment were strong predictors of a medical condition among patients presenting to the ED after ATS use. These patients should undergo thorough physical examination and diagnostic testing to identify and manage potentially life-threatening conditions. Full article

Background/Objectives: Sarcopenia may be influenced by lifestyle and dietary factors. Emerging evidence suggests that certain foods such as sea vegetables and fruits contain bioactive compounds may help protect against muscle loss. This study investigated the association between sea vegetable and fruit intake and the risk of sarcopenia and physical performance in older adults in Taiwan. Methods: We conducted a cross-sectional study of 588 individuals aged ≥65 years recruited from three hospitals (outpatient and home-care settings) in southern Taiwan (2018–2020). Questionnaire, medical chart, and laboratory data were used to examine the associations between demographic characteristics, dietary intake, and nutritional status and sarcopenia, defined as low muscle mass plus reduced strength or poor physical performance. Sarcopenia was diagnosed using Asian Working Group for Sarcopenia 2019 criteria. The performance variables we measured were grip strength, gait speed, and chair stand time. Logistic regression was used to identify associated factors, and linear regression was used to assess the contributions of these factors to performance measures. Results: Sarcopenia was identified in 159 (27.0%) of the 588 participants. Those with sarcopenia had lower education levels, poorer nutritional status, weaker grip strength, and slower mobility. Daily intakes of sea vegetables (adjusted OR = 0.38, 95% CI: 0.20–0.74) and fresh fruits (adjusted OR = 0.28, 95% CI: 0.16–0.49) were independently associated with reduced risk of sarcopenia. Sea vegetable intake was positively associated with grip strength, while fruit intake was inversely associated with chair stand time. Conclusions: Dietary factors and nutritional status were significantly associated with sarcopenia risk and physical performance. Sarcopenia prevention strategies might want to include promoting the consumption of sea vegetables and fruits. Full article

Background: High-chloride solutions such as 0.9% saline are widely used for medication dilution in intensive care units (ICUs) and are an underrecognized source of hyperchloremia and acid–base disturbances. Excess chloride reduces the strong ion difference (SID), contributing to hyperchloremic metabolic acidosis and worse clinical outcomes. This study evaluated the impact of replacing isotonic saline with 5% dextrose as a diluent on ICU outcomes in mechanically ventilated patients. Methods: In this retrospective cohort study, 4347 adult ICU patients requiring ≥12 h of mechanical ventilation were analyzed across two periods with different diluent strategies (2015–2018: saline-based; 2019–2025: chloride-sparing, dextrose-based). Demographics, comorbidities, illness severity (APACHE II, SOFA), fluid exposure, SID, and laboratory values over the first 48 h were compared. Predictors of mortality were identified using multivariate logistic regression. Results: Mortality decreased from 44.6% to 39.2% after adoption of chloride-sparing diluents (absolute reduction 5.4%, p = 0.003), despite similar renal function across periods. The later cohort demonstrated significantly higher SID (median 39 vs. 38 mmol/L; p < 0.001), lower chloride levels, and more favorable acid–base profiles. In 2015–2018, chloride showed a strong association with mortality (~12–13% increased odds per mmol/L), while in 2019–2025 the association persisted but was attenuated (~2% per mmol/L). SID emerged as a significant marker of improved acid–base balance after the diluent transition. pH remained the most powerful predictor of mortality in both periods. Mean glucose levels increased by ~30–40 mg/dL after switching to dextrose diluents, although insulin requirements did not change. Conclusions: Transitioning from chloride-rich to chloride-sparing diluents was associated with reduced ICU mortality and improved acid–base balance, without changes in renal function. However, modestly increased glucose levels highlight the need for strict glycemic monitoring. These findings support chloride-sparing strategies with robust glycemic monitoring in critical care. Full article

ST-segment elevation myocardial infarction (STEMI) represents a time-critical medical emergency where complete coronary artery occlusion initiates progressive myocardial necrosis. The fundamental principle of modern STEMI care—“Time is Muscle”—establishes that ischemic duration directly determines infarct size and clinical outcomes. Each minute of delay correlates with increased mortality, larger infarcts, and a higher risk of heart failure development. Total ischemic time encompasses both patient-mediated delays (often the largest component) and system-related delays, each influenced by distinct factors requiring targeted interventions. This comprehensive review analyzes the components of total ischemic time, quantifies the clinical consequences of delay, and evaluates evidence-based mitigation strategies. We examine the evolution from fibrinolysis to primary percutaneous coronary intervention and the resulting logistical challenges. System-level interventions—including public awareness campaigns, regionalized STEMI networks, pre-hospital ECG acquisition, and standardized hospital protocols—have dramatically reduced treatment times. However, persistent disparities based on geography, presentation timing, sex, race, and age remain problematic. Emerging technologies, particularly artificial intelligence for ECG interpretation, offer promise for further time reduction. Full article

Background and Objectives: External ventricular drain (EVD)-associated infections are a serious complication in subarachnoid hemorrhage (SAH) patients, with reported incidence rates of 1–45%. Existing prediction models show limited performance and focus on the static risk factors assessed at insertion, failing to examine how infection risk changes over time. We sought to identify the independent predictors of EVD infections in SAH patients and develop a practical clinical prediction model. Materials and Methods: We retrospectively analyzed 198 SAH patients with EVDs treated at our center between January 2022 and April 2025, collecting 4757 laboratory observations throughout their hospital stay. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors and develop a clinical prediction model. Results: Of 198 patients undergoing EVD insertion for SAH, 49 developed associated infections (24.7%). Univariate analysis identified several significant risk factors, including EVD duration (Cohen’s d = 1.00, p < 0.001), EVD revisions (d = 1.11, p < 0.001), Hunt & Hess grade ≥ 4 (p = 0.011), and peak laboratory values, including CSF lactate (d = 0.53, AUC = 0.79), CSF protein (d = 0.52, AUC = 0.74), CSF glucose (d = 0.63, AUC = 0.73), and procalcitonin (d = 0.58, AUC = 0.75). However, multivariate analysis revealed that only EVD duration retained statistical significance (adjusted OR = 3.50 per continuous day; 95% CI: 2.11–5.78; p < 0.000001); note that continuous daily scale modeling implies exponential risk escalation (3.5-fold increase per single day). For clinical interpretation, categorical duration analysis provides more conservative estimates: 8–14 days versus ≤7-day reference OR = 1.92 (p = 0.013), and >14 days versus ≤7-day reference OR = 3.70 (p < 0.001). All other variables lost statistical independence after mutual adjustment. Infection rates demonstrated a dose–response relationship with EVD duration: 11.1% for ≤7 days, 19.3% for 8–14 days, and 31.6% for >14 days. The final prediction model achieved good discrimination (AUC = 0.737). Conclusions: EVD duration emerged as the dominant predictor of infection risk in SAH patients, which is a traditional factor. These findings support clinical protocols that prioritize minimizing drain duration whenever medically appropriate, shifting focus from complex risk scoring to time-based management strategies. Full article

Background: Emergency contraception (EC), also known as postcoital contraception, is a method used to prevent an unintended pregnancy following unprotected or inadequately protected sexual intercourse. The available options include emergency contraceptive pills or the insertion of an intrauterine device (IUD). Emergency contraception pills contain either levonorgestrel (a single 1.5 mg dose, effective within 72 h) or ulipristal acetate (a single 30 mg dose, effective within 120 h), both of which are most effective when taken as soon as possible after unprotected intercourse. Another highly effective option is the insertion of a copper or levonorgestrel-releasing intrauterine device, although IUDs are not registered for EC use in all countries. The aims of this cross-sectional, comparative, observational study were to collect data on the emergency contraception methods used by adolescent girls and young women to examine their association with various factors, such as religious beliefs, and to evaluate the effectiveness of different emergency contraception methods, including hormonal options and intrauterine devices. Methods: Data were collected from 240 women who attended our Family Planning Clinic using a structured questionnaire that included items on their demographic characteristics, religious beliefs, medical history, lifestyle factors, contraceptive use and side effects, prior use of emergency contraception, method selected, and reasons for seeking emergency contraception. Descriptive statistics were used to summarize the data, comparisons between religious groups were conducted using chi-square tests, and factors related to the timing of emergency contraceptive use were investigated using multinomial logistic regression analysis. Results: Most of the reasons for emergency contraception use did not differ significantly between Christian and Muslim participants. However, Christians were significantly more likely to use emergency contraception due to missed contraceptive doses (20.9% vs. 6.7%, p = 0.004) or the failure to take a progesterone-only pill (19.1% vs. 3.3%, p = 0.001). Levonorgestrel was the most frequently used method in both groups (48.9% of Christians vs. 60% of Muslims, p = 0.132), followed by ulipristal acetate (30.9% vs. 40%, p = 0.180). Notably, 18.5% of Christian participants used an intrauterine device (IUD) for emergency contraception, while no Muslim participants reported IUD use (p < 0.001), indicating a significant difference potentially influenced by cultural or religious factors. Conclusions: Both religious and individual sociodemographic factors affect not only the choice of emergency contraception but also the urgency with which the emergency contraception is used. Interventions aimed at improving contraception education, addressing partner-related challenges, and promoting timely access could improve reproductive health outcomes. Full article

Background/Objectives: Research on the association of adverse social determinants of health (SDOH) with severe pediatric coronavirus disease (COVID-19) is limited. We examined associations between SDOH patterns and COVID-19 severity in children. Methods: We conducted a prospective, observational study of children (<18 years) with symptomatic SARS-CoV-2 infection evaluated in an urban pediatric emergency department (March 2021–April 2022) in Detroit, Michigan. Caregivers completed a 34-item survey based on the Healthy People 2030 framework. Severe disease was defined as the occurrence of respiratory/cardiac failure or death within four weeks of diagnosis. Continuous and categorical variables were described using medians and percentages, respectively. Associations between disease severity and risk factors were determined using chi-square tests. Association rule mining was used for feature selection, followed by multivariate logistic regression. Results: We analyzed data from 354 children [6–12 years: 31.1%, Female: 51.1%, Black: 59%, not Hispanic: 84.7%, public insurance: 77.1%, chronic condition: 27.4%]. Of the total, 113 children had severe disease. Most caregivers were 30–44 years old (53.1%), had less than a college degree (70.4%), and income < USD 50,000 (75.2%). Adverse SDOH reported included food/housing insecurity (24.6%), no support (64.7%), unmet childcare needs (35.9%), and lack of transportation (12.7%). After controlling for age, sex, medical history, income, and obesity, severe disease was associated with caregiver use of drugs/alcohol (OR:5.92, p < 0.001) and social discrimination/lack of support (OR: 1.74, p = 0.030). Conclusions: Two SDOH patterns (caregiver use of drugs/alcohol and social discrimination/lack of support) were associated with severe COVID-19. Further studies are needed to confirm findings and develop interventions. Full article

Neurosymbolic AI is an emerging paradigm that combines neural network learning capabilities with the structured reasoning capacity of symbolic systems. Although machine learning has achieved cutting-edge outcomes in diverse fields, including healthcare, agriculture, and environmental science, it has potential limitations. Machine learning and neural models excel at identifying intricate data patterns, yet they often lack transparency, depend on large labelled datasets, and face challenges with logical reasoning and tasks that require explainability. These challenges reduce their reliability in high-stakes applications such as healthcare. To address these limitations, we propose a hybrid framework that integrates symbolic knowledge expressed in First-Order Logic into neural learning via a Logic Tensor Network (LTN). In this framework, expert-defined medical rules are embedded as logical axioms with learnable thresholds. As a result, the model gains predictive power, interpretability, and explainability through reasoning over the logical rules. We have utilized this neurosymbolic method for predicting diabetes by employing the Pima Indians Diabetes Dataset. Our experimental setup evaluates the LTN-based model against several conventional methods, including Support Vector Machines (SVM), Logistic Regression (LR), K-Nearest Neighbors (K-NN), Random Forest Classifiers (RF), Naive Bayes (NB), and a Standalone Neural Network (NN). The findings demonstrate that the neurosymbolic framework not only surpasses traditional models in predictive accuracy but also offers improved explainability and robustness. Notably, the LTN-based neurosymbolic framework achieves an excellent balance between recall and precision, along with a higher AUC-ROC score. These results underscore its potential for trustworthy medical diagnostics. This work highlights how integrating symbolic reasoning with data-driven models can bridge the gap between explainability, interpretability, and performance, offering a promising direction for AI systems in domains where both accuracy and explainability are critical. Full article