Rescue Time Research Articles

Enhancing urban emergency response: A Euclidean distance-based framework for optimizing rescue facility layouts

This study presents a Euclidean distance-based framework for optimizing the layout of urban emergency rescue facilities. Traditional precinct-based (Type 1) and dynamic time-based (Type 2) models are compared with the proposed Euclidean distance-based (Type 3) model. The analysis uses geospatial and statistical methods to evaluate accessibility, variability, and fairness across different times of the day. The results indicate that the Euclidean distance-based model enhances rescue response efficiency and maintains a more equitable service distribution relative to traditional models. The study identifies a “threshold effect” in rescue times, emphasizing the critical distance beyond which rescue efficiency declines. By leveraging real-time traffic data and integrating Euclidean distance principles, the proposed framework offers a robust and practical approach for urban planners to improve emergency response capabilities and urban resilience. This research underscores the importance of considering both geometric proximity and dynamic traffic conditions in the strategic placement of rescue facilities, providing valuable insights for future urban emergency management and planning.

Study on Propeller Positioning and Trajectory Control of Underwater Robots Based on Bayesian Inference and Multi-Objective Optimization

In ocean exploration, the positioning and trajectory optimization of underwater vehicles are critical research areas that directly impact the success of ocean resource exploration, environmental monitoring, and search and rescue missions. However, the complex and uncertain marine environment poses significant challenges. This study first determines the three-dimensional spatial position of the underwater vehicle, calculates the vehicle's speed in the marine environment through mechanistic analysis, traversing the initial position, velocity, acceleration, angular velocity and angular acceleration of the submersible, fits the motion trajectory using a random walk, and uses Bayesian inference to estimate maximum probability positions of submersibles and select the optimal initial deployment point. To better cope with real-world scenarios involving ocean currents and the diverse motion modes of underwater vehicles, this study further used an improved genetic algorithm to divide the motion trajectory of the submersible into a series of discrete path points, and constructed a multi-objective optimization model with the shortest search and rescue time and the maximum probability of successful search and rescue as the objective function to realize the precise positioning of the lost underwater vehicle.

Pre-occurrence location-allocation-configuration of maritime emergency resources considering shipborne unmanned aerial vehicle (UAV)

Demand for maritime transportation has constantly increased throughout recent years due to its high capacity, extensive coverage, high safety, and so on. However, the growth has also contributed to a rise in maritime accidents, highlighting the need for developing maritime emergency management strategies. In maritime emergency management, resource location-allocation-configuration is the most important and inseparable preparedness action before disasters, directly deciding the quality of emergency rescue operations. Traditional ship-only rescue is frequently both cost-intensive and time-consuming, seriously affecting rescue performance. This study introduces an innovative shipborne UAV operation system to address these limitations. Firstly, a multi-objective mixed-integer nonlinear programming model is established to minimize total rescue time and cost by considering the uncertain maritime environment, continuous docking placements of ships, UAV flight distance, rescue station capacity, etc. Secondly, to efficiently obtain an execution plan, a two-stage algorithm is proposed to facilitate our mission optimization model. Large-scale simulated instances and a real case study demonstrate that (i) the proposed algorithm can solve the model efficiently. (ii) the application of shipborne UAV operation system in maritime emergencies shows a significant improvement in time and cost compared to ship-only system. (iii) it is necessary to consider the uncertain maritime environment when solving emergency management problems. Moreover, extensive parameter sensitivity analysis provides managerial insights into the impact of various factors on the optimization outcomes. We also explore deeper insights that may benefit maritime administration's decision support.

Collaborative Scheduling of Mass Rescue Operations at Sea

The continued growth of the global cruise market has posed a major challenge to maritime search and rescue, as available rescue resources are limited compared to the scale of passenger ship disasters. To bridge the gap between the number of passengers in distress and the availability of rescue resources, this paper develops a two-stage Mass Rescue Operation (MRO) decision support model (MRO model) to fully utilize the available multiple rescue resources. Based on the combinatorial optimization theory, in the MRO model we consider the rescue capacity of multiple rescue resources and the synergy between them, the accident types and the marine environment conditions to optimize two objectives (rescue time and number of rescue resources dispatched) in two stages. In the first stage, the objective is to minimize the rescue time by Classical Selection Sort Algorithm. In the second stage, the rescue time and the number of rescue resources are simultaneously optimized by Simulated Annealing Arithmetic (SAA) integrated with Genetic Algorithm (GA). Furthermore, considering the actual role of helicopters in MROs, the MRO model is enhanced to schedule helicopters mandatorily or non-mandatorily. Finally, the MRO model was verified by simulating accidents in the Taiwan Strait. The simulation results show that compared with the first stage, the rescue time in the second stage model is saved by up to 16.18% and the number of rescue resources is reduced by up to 45.16%.

Hemodynamic analysis on the flow characteristics around abdominal aortic hemorrhage site

The hemodynamic characteristics of blood flow around the site of abdominal aortic hemorrhage can serve as a valuable indicator for identifying the location of hemorrhage. In this research, we conducted numerical simulations to analyze the flow fields in the patient-specific abdominal aorta with and without hemorrhage. We quantitatively compared differences in flow field patterns, blood loss, and branch vessel perfusion between hemorrhagic and non-hemorrhagic cases. Our numerical results demonstrate that there is a distinct hemodynamic characteristic observed around the hemorrhage site, characterized by continuous abnormal high-velocity (>0.7 m/s) and high-Rortex (>200) zone. Additionally, we evaluated the amount of blood loss and time to moderate shock for different cases of abdominal aortic hemorrhage, while statistically analyzing variations in branch vessel perfusion along the abdominal aorta. These findings provide quantitative estimations for blood loss, branch perfusion, and potential indicators to assess rescue time window as well as evaluate the extent of distal tissue damage and organ injury.

Analysis of the Emergency Rescue Nursing Intervention Effect and Rescue Success Rate for Patients with Traumatic Hemorrhagic Shock

Objective: To analyze the value of emergency rescue nursing intervention in the care of patients with traumatic hemorrhagic shock and its impact on the success rate of rescue efforts. Methods: A total of 80 patients with traumatic hemorrhagic shock were selected as samples, with the timeframe from July 2022 to July 2023. The patients were randomly divided into two groups using a random number table method. Group A received emergency rescue nursing, while Group B received routine nursing care. The success rate of rescue, rescue indicators, complication rates, and family satisfaction with nursing care were compared between the two groups. Results: The rescue success rate in Group A was higher than in Group B (P < 0.05); the total blood loss in Group A was less, and the rescue time, full transportation time, and hospitalization time were shorter than in Group B (P < 0.05); the complication rate of patients with traumatic hemorrhagic shock in Group A was lower than in Group B (P < 0.05); the family satisfaction with emergency nursing care in Group A was higher than in Group B (P < 0.05). Conclusion: Emergency rescue interventions for patients with traumatic hemorrhagic shock can reduce blood loss, shorten rescue times, and improve the success rate of shock rescue, providing a safe and effective approach.

Multi-period emergency facility location-routing problems under uncertainty and risk aversion

This paper addresses a multi-period emergency facility location-routing problem, in which the uncertainties in material demands and transportation time, as well as dynamic inventory replenishment and carryover are incorporated in the design of multi-level emergency logistics networks. To measure the risks stemming from uncertain transportation time, mean-CVaR method is used. Then, a risk-averse stochastic programming model for the presented problem is formulated to minimize the total rescue time of the network. Moreover, a genetic algorithm is developed to solve the proposed model. Extensive numerical experiments including the randomly generated instances and a case study on the Wenchuan earthquake in China are conducted to verify the effectiveness of the presented model and algorithm. Experimental results show that the genetic algorithm significantly performs better than the Gurobi solver in terms of both solution quality and solution time.

Avalanche Survival Rates in Switzerland, 1981-2020.

Survival probability among individuals critically buried by avalanche is highly time dependent, which was demonstrated 30 years ago. However, it remains unclear whether avalanche survival probability has changed over time. To assess the avalanche survival rate and probability as well as the rescue probability over the past 4 decades. In this cohort study, avalanche data from Switzerland that were collected by the WSL Institute for Snow and Avalanche Research (SLF) in Davos were analyzed from the winter beginning in 1981 to that beginning in 2020 and compared with data from the period 1981 to 1990. Data were analyzed from January to April 2024. Critical avalanche burial (ie, burial involving the head and chest). Survival rate among individuals critically buried by avalanche, survival probability, and rescue probability in relation to time buried under the avalanche. The study included 1643 individuals critically buried by avalanche (mean [SD] age, 37 [13.7] years; 1090 of 1342 with known sex [81.2%] were male) among 3805 avalanches involving 7059 persons. Compared with the period from 1981 to 1990, the total survival rate over the full study period increased from 43.5% (95% CI, 38.8%-48.3%) to 53.4% (95% CI, 51.0%-55.8%). Survival probability remained high at 91% (95% CI, 80%-100%) for rescue during the first 10 minutes but then decreased to 31% (95% CI, 11%-51%) for rescue between 10 and 30 minutes. The survival rate among those buried long term (>130 minutes) increased from 2.6% (95% CI, 0.7%-6.9%) to 7.3% (95% CI, 4.8%-10.7%). The median rescue time decreased from 45 (IQR, 15-148) minutes to 25 (IQR, 10-85) minutes. Survival rates among individuals rescued from avalanche by organized rescue teams increased from 14.0% (28 of 200) to 22.9% (161 of 704). This cohort study of 1643 individuals critically buried by avalanche found that over the past 4 decades, total survival rates considerably increased and rescue times decreased. Survival rates among those buried long term (>130 minutes) also increased. These findings are likely attributable to collaborative efforts among stakeholders to enhance avalanche search-and-rescue techniques and medical interventions.

The correlation between embryo rescue and hormonal changes in seedless grapes.

After normal pollination and fertilization of pseudoparthenocarpic seedless grapes, their embryos often stop developing due to certain developmental factors, resulting in embryo abortion. Hybrid breeding using seedless grapes as the maternal parent requires embryo rescue breeding technology. This technology plays a crucial role in seedless grape breeding. Although previous studies have extensively explored this technology, knowledge regarding its impact on embryo abortion and the effectiveness of rescue techniques remains limited. This study aimed to investigate the correlation between embryo rescue and hormonal changes in seedless grapes. Four Eurasian seedless grape cultivars, "Thompson Seedless," "Flame Seedless," "Heshi Seedless," and "Ruby Seedless," were selected for examination. We investigated endogenous hormone levels, including indole-3-acetic acid (IAA), gibberellic acid (GA3), and abscisic acid (ABA), in both berries and in vitro ovules during the most suitable embryo rescue time for these cultivars. Based on the observed fluctuations in endogenous hormone levels and previous research findings, appropriate doses of exogenous hormones, such as IAA, GA3, and ABA, were applied during seedless grape embryo rescue. The results indicated significant differences in endogenous hormone levels between berries with varying ovule counts of the same cultivar and ovules cultured in vitro, suggesting a hormonal influence on ovule abortion and embryo development in seedless grapes. Further research has identified effective ratios of exogenous hormones: 30 mg·L-1 IAA + 30 mg·L-1 ABA for berry ovule development, 1.0 mg·L-1 IAA + 2.0mg·L-1 6-benzylaminopurine (6-BA) + 1.0 mg·L-1 GA3 + 1.0 mg·L-1 ABA for in vitro ovule development, and 1.0 mg·L-1 IAA + 2.0 mg·L-1 6-BA + 1.0 mg·L-1 GA3 for embryo germination and seedling formation. In summary, hormonal changes significantly influence ovule and embryo development and are closely related to seedless grape embryo rescue breeding. This study deepened our understanding of the correlation between seedless grape embryo rescue and hormonal changes. It also resulted in the successful production of a batch of embryo rescue seedlings, further improving embryo rescue breeding technology and providing new germplasm materials for developing new seedless grape cultivars.

Challenges and Clinical Impact of Medical Search and Rescue Efforts Following the Kahramanmaraş Earthquake.

This study assesses the operational challenges and clinical outcomes encountered by a university-based Emergency Medical Team (EMT) during the medical search and rescue (mSAR) response to the February 2023 earthquakes in Kahramanmaraş, Turkey. In this observational study, data were retrospectively collected from 42 individuals who received mSAR services post-earthquake. The challenges were categorized as environmental, logistical, or medical, with detailed documentation of rescue times, patient demographics, injury types, and medical interventions. In this mSAR study, 42 patients from 30 operations were analyzed and divided into environmental (26.2%), logistical (52.4%), and medical (21.4%) challenge groups. Median rescue times were 29 (IQR 28-30), 36.5 (IQR 33.75-77.75), and 30.5 (IQR 29.5-35.5) hours for each group, respectively (P = .002). Age distribution did not significantly differ across groups (P = .067). Hypothermia affected 18.2%, 45.5%, and 66.7% in the respective groups. Extremity injuries were most common in the medical group (88.9%). Intravenous access was highest in the medical group (88.9%), while splinting was more frequent in the medical (55.6%) and logistical (18.2%) groups. Hypothermia was most prevalent in the medical group (66.7%), followed by the logistical group (45.5%). Ambulance transport post-rescue was utilized for a minority in all groups. The study concludes that logistical challenges, more than environmental or medical challenges, significantly prolong the duration of mSAR operations and exacerbate clinical outcomes like hypothermia, informing future enhancements in disaster response planning and execution.

Association of reductions in rescue medication requirements with vagus nerve stimulation: Results of long-term community collected data from a seizure diary app

ObjectiveTo assess the impact of vagus nerve stimulation (VNS) on quality of life contributors such as rescue medications. MethodsUsing the seizure diary application SeizureTracker™ database, we examined trends in rescue administration frequency before and after the first recorded VNS magnet swipe in patients with drug-resistant epilepsy who had 1) At least one VNS magnet swipe recorded in the diary, and 2) Recorded usage of a benzodiazepine rescue medication (RM) within 90 days prior to the first swipe. A paired Wilcoxon rank-sum test was used to assess changes in RM usage frequency between 30-, 60-, 90-, 180- and 360-day intervals beginning 30 days after first magnet swipe. Longitudinal changes in RM usage frequency were assessed with a generalized estimating equation model. ResultsWe analyzed data of 95 patients who met the inclusion criteria. Median baseline seizure frequency was 8.3 seizures per month, with median baseline rescue medication usage frequency of 2.1 administrations per month (SD 3.3). Significant reductions in rescue medication usage were observed in the 91 to 180 day interval after first VNS magnet swipe, and at 181 to 360 days and at 361 to 720 days, with the magnitude of reduction increasing over time. Decreases in rescue medication usage were sustained when controlling for patients who did not record rescue medication use after the first VNS magnet swipe (N=91). Significant predictors of reductions in rescue medication included baseline frequency of rescue medication usage and time after first VNS magnet swipe. SignificanceThis retrospective analysis suggests that usage of rescue medications is reduced following the start of VNS treatment in patients with epilepsy, and that the magnitude of reduction may progressively increase over time.

Optimization of embryo rescue technique for development of hybrid plants in stenospermic grapes

The development of seedless cultivars is a primary goal in grapevine breeding. Since grapes are stenospermic and tend to abort their embryos before development, traditional breeding methods often yield seedless cultivars at a low frequency. Therefore, embryo rescue has emerged as a promising approach for creating seedless grape cultivars. This study aimed to optimize the ideal sampling time and protocol for efficient embryo rescue in grapes. Ovules from immature berries collected at various days after pollination (20DAP, 30DAP, 40DAP, and 50DAP) were cultured on Nitsch and Nitsch (NN) medium with different concentrations of Benzyl aminopurine (BAP) (0.1, 0.2, and 0.5 mg/L) and Activated Charcoal (AC) (1.5, 2, and 2.5 g/L). Several parameters were assessed, including maximum ovule growth, the percentage of enlarged ovules, percentage of collapsed ovules, callus formation percentage, and embryo germination percentage. The study’s results indicated that berries collected at 40 DAP yielded the best outcomes across all parameters. Regarding treatments, the most favorable results were achieved when ovules were cultured on NN medium supplemented with 0.5 mg/L BAP and 2 g/L AC. In conclusion, the study underscores the significance of choosing the right sampling time and treatments to ensure efficient embryo rescue in grapes. The protocol standardized from this research is recommended for effectively rescuing embryos and developing seedless hybrids.

Location method for emergency rescue node on expressways based on spatio-temporal characteristics of vehicle operation

Expressway networks are continuously developing and emergency rescue demand is increasing proportionately. The location of expressway emergency rescue nodes needs refinement to meet changing requirements. In this study, the expressway was modeled as an expressway network. The differences in the origin destination (OD) distribution matrices for working days and major holidays were used as the bases for determining the need for temporary emergency rescue nodes. Overlapping and non-overlapping community detection algorithms were used to extract the distribution characteristics of OD during both day categories. These distributions were used to determine permanent and temporary emergency rescue sites. In this study, we considered the differences in traffic volume, distance, and impact of four vehicle types on traffic accidents to select the location of emergency rescue nodes, and allocate emergency resources. An emergency rescue node selection model for an expressway network was established based on spatio-temporal characteristics. The results based on a regional example determined that 22 permanent and 25 temporary emergency rescue nodes were appropriate. The average rescue time for traffic accidents during working days and major holidays compared to the P-center location model, was reduced by approximately 27.08% and 6.70%, respectively. The coefficient of variation of emergency rescue time was reduced by approximately 28.22% and 21.41%, respectively. The results indicated that the model satisfied the expressway emergency rescue demand requirements, and improved the rationality of the rescue center node layout.

Risk assessment of hazmat road transportation accidents before, during, and after the accident using Bayesian network

Risk exists in the whole process of before, during and after the accident of hazardous materials (hazmat) transportation, which usually lead to serious consequences. Risk assessment is a significant way to identify hidden dangers and their interactions, which can curb accidents happen. The purpose of this study is to analyze the risk factors of hazmat road transportation accidents through entire process risk assessment and propose management strategies. Considering nodes dependency, i.e. accident type and rescue time, this study applies the concept of Tree Augmented Naive Bayes (TAN) and built a hazmat road transportation Bayesian network (HRT-BN). Mutual information and model validation are carried on to better facilitate convenient inference and diagnosis of risk nodes and their interactions. Results show that in causal inference with single factors, human risk factors are more significant, which are likely to lead to leakage accident with slight consequences and short rescue time (s2). Meanwhile, with coupling effect of multiple factors, accident types become more diverse with serious consequence. In diagnostic inference, the rescue time is linked to seasonal and regional factors, e.g., the rescue time in summer is longer. Based on these analysis, targeted recommendations have been proposed at the end. This study provides a whole angle of view to assess risks in hazmat transportation, which has significant practical feasibility for risk management and planning of hazmat road transportation.

Descriptive Study of Earthquake-Related Spinal Cord Injury in Türkiye-Kahramanmaraş

Objective: We aimed to review the epidemiological data of patients who were rescued from under the rubble in the Kahramanmaraş earthquakes on February 6 and developed earthquake-related spinal vertebral fractures. Materials and Methods: Our study included 69 patients with spinal vertebral fractures and/or spinal cord injuries (SCIs) who were admitted to the Physical Medicine and Rehabilitation Clinic of Adana City Training and Research Hospital after the 6 February Kahramanmaraş Pazarcık and Elbistan earthquakes. Patients with peripheral nerve damage or loss of muscle strength due to pelvic and extremity fractures were not included in the study. Results: The mean age of the patients was 40.43±15.24 years (min=8-max=72). The median time of rescue from under the rubble was 15 (1-106) hours. The median visual analogue scale (VAS) pain score was 7 (0-10). 69.6% of the patients were female. Among the patients with a vertebral spinal injury, 72.5% had an incomplete SCI and 27.5% had a complete SCI. 84.5% of the patients underwent surgery, and posterior spinal instrumentation was performed in 56.5% of them. Conclusion: There has been a significant increase in the number of SCI cases after the Kahramanmaraş earthquakes. Rehabilitation centers should be established, patients' access to these centers should be facilitated, and complications should thus be prevented or optimized. Injured people should be helped to return to their social lives. Keywords: February 6th Kahramanmaraş, Earthquake, Spinal Cord Injury

Emergency logistics siting-path question for engineering construction projects based on quantum particle swarm algorithm

Emergency material security is the key to post-disaster emergency relief in complex environment engineering construction projects. Aiming at the emergency logistics center site path planning problem, the uncertain parameters of congestion time and maximum rescue time are described using trapezoidal fuzzy numbers, and the emergency logistics site path model of the two-phase engineering construction project is established. A quantum particle swarm optimization model is designed to avoid premature population convergence and maintain population diversity. The particle swarm algorithm uses the quantum spin gate’s rotation angle update to represent the particle velocity update. Taking the engineering construction project in the western mountainous area as an example, the validity and applicability of the model are verified through model comparison and sensitivity analysis. The results of the example show that in the complex environment, the quantum particle swarm algorithm takes 29.35 s in convergence time, and the particle swarm algorithm takes 40.12 s, which is 36.69% higher than the efficiency of PSO. In total cost, the quantum particle swarm algorithm has a total cost of 46,632.40 RMB, and the particle swarm algorithm has a total cost of 48,319.51 RMB, which is 3.62% lower than the cost of PSO. The quantum particle swarm algorithm’s total distance is 550.57 km, and the particle swarm algorithm’s total distance is 579.35 km, 5.23% lower than the total distance of PSO. The model established in this study can scientifically select the location of emergency facilities and formulate the emergency rescue path, reduce the response time of emergency rescue and storage costs, and provide decision support for the scheduling of emergency supplies for engineering construction projects in complex and dangerous areas.

Accident black spot clustering oriented maritime search and rescue resource allocation and optimization

Efficient and rapid deployment of maritime search and rescue(MSAR) resources is a prerequisite for maritime emergency search and rescue, in order to improve the efficiency and accuracy of MSAR. This paper proposes an integrated approach for emergency resource allocation. The approach encompasses three main steps: identifying accident black spots, assessing high-risk areas, and optimizing the outcomes through a synergistic combination of an optimization algorithm and reinforcement learning. In the initial step, the paper introduces the iterative self-organizing data analysis technology (ISODATA) for identifying accident spots at sea. A comparative analysis is conducted with other clustering algorithms, highlighting the superiority of ISODATA in effectively conducting dense clustering. This can effectively carry out dense clustering, instead of the situation where the data spots are too dispersed or obvious anomalies that affect the clustering. Furthermore, this approach incorporates entropy weighting to reassess the significance of accident spots by considering both the distance and the frequency of accidents. This integrated approach enhances the allocation of search and rescue forces, ensuring more efficient resource utilization. To address the MSAR vessel scheduling problem at sea, the paper employs the non-dominated sorting genetic algorithm II combined with reinforcement learning (NSGAII-RL). Comparative evaluations against other optimization algorithms reveal that the proposed approach can save a minimum of 7% in search and rescue time, leading to enhanced stability and improved efficiency in large-scale MSAR operations. Overall, the integrated approach presented in this paper offers a robust solution to the ship scheduling problem in maritime search and rescue operations. Its effectiveness is demonstrated through improved resource allocation, enhanced timeliness, and higher efficiency in responding to maritime accidents.

2023 catastrophic Turkey earthquake: clinical outcomes of pediatric patients rescued under the rubble

ABSTRACT Objectives Children are the most vulnerable population affected by the earthquake. We aimed to examine the characteristics, morbidity, mortality, and the factors affecting these pediatric earthquake victims to guide the follow-up of pediatric patients who were rescued under the rubble in possible future disasters. Methods This is a retrospective observational study. The files of pediatric earthquake victims aged 0–18 years who were admitted to Adana City Training and Research Hospital between 6 February-30 April 2023 were analyzed. 318 patients were included in the study. Results Of all patients 48.7% (n = 155) were female and 51.3% (n = 163) were male. The mean age of the patients was 114.8 months. 65.4% (n = 208) of the patients were discharged from our hospital, eighteen patients (5.7%) died. Information on the hour when the patients were rescued under the rubble could be reached in 117 (36.8%) patients. The mean rescue time of these patients was 50.5 hours. 62 (53%) victims were rescued in the first 24 hours after the earthquake. There were 111 patients (34.9%) with fractures. There were 118 patients (37.1%) who underwent fasciotomy surgery. The total number of patients with amputation was 48 (15.1%). There were 36 patients (11.3%) with one limb amputated, 12 patients (%3.7) with more than one limb amputation. Internal organ injury was present in 30.5% (n = 97) of the patients. Of these patients, 85.6% (n = 83) had single organ trauma and 14.4% (n = 14) had multiple organ trauma. There were 58 patients (18.2%) with acute renal failure in follow-up. The mean rescue time for patients with amputation was 83.65 ± 62.9 hours, and for patients without amputation was 36.44 ± 50.6 hours. This difference was statistically significant (p = 0.001). No statistically significant difference was found when the ages of the patients were compared to fasciotomy, amputation, and fracture status. Conclusion While evaluating earthquake-induced trauma, pediatric patients should be approached carefully.

Advances in the Use of Prone Cardiopulmonary Resuscitation During Spinal Surgery in the Prone Position

Spinal surgery is usually performed in the prone position, which is a longer and more difficult procedure and is prone to complications such as circulatory dysfunction and stress injuries. Among them, stress injury is the main complication of prone spine surgery, but the reasons for stress injury in prone spine surgery are not clear, and whether prone cardiopulmonary resuscitation (CPR) can be used needs to be further verified. Supine cardiopulmonary resuscitation is commonly used in posterior spinal surgery, retroperitoneal surgery, and so on, which can effectively improve the patient’s hypoxemia. Such surgeries require a high level of anesthetic management, and cardiopulmonary resuscitation is necessary if a patient in a prone position experiences cardiac arrest. In the process of cardiopulmonary resuscitation, supine cardiopulmonary resuscitation is often used, especially for some obese patients, if they are immediately changed to the supine position, it takes up more time, there may be wound infection, and there is a possibility of missing the optimal rescue and resuscitation time. Based on this, this paper reviews the use of prone-position cardiopulmonary resuscitation for spinal surgery in the prone position.

X-ray Image Recognition of Pneumonia Based on Three Different Neural Networks

With the outbreak of new coronary pneumonia, a variety of pneumonia diseases are emerging, doctors often have misdiagnoses and omissions. To assist doctors in better clinical diagnosis, a variety of high-performance neural network structures have been applied to the X-ray recognition of pneumonia, and the X-ray image recognition accuracy will be improved, will effectively improve the efficiency of the hospital detection, at the same time, can also avoid the patient to miss the best rescue time. To this end, this paper compares and analyses the recognition performance of the three currently used neural network structures in the recognition of pneumonia X-ray images, uses some publicly available datasets and a mixed set composed of different datasets to conduct experiments, and summarises the advantages of the models and the direction of possible improvement. The three neural network models are presented, compared, and analysed to suggest useful references for the recognition of pneumonia X-ray images. Finally, an analysis and outlook for future neural network models for pneumonia x-ray image recognition is presented.