The 2024 think tank on prevention of sudden cardiac death in the young: Pathway to survival. A report from the Cardiac Safety Research Consortium

Sudden cardiac arrest and death in the young is a critical public health issue. It occurs in children of any age, sex, racial or ethnic demographic, or socioeconomic status. Importantly, it can affect any individual-athlete and nonathlete alike. Prevention of sudden death in the young is of high importance not only because of the loss of a young life but also because of the substantial impact to families and to society at large. This White Paper summarizes the proceedings of a third national Think Tank on prevention of sudden cardiac death in the young. The Think Tank, which convened on January 11 to 12, 2024 at Duke University in Durham, NC, was organized and conducted by the Cardiac Safety Research Consortium in collaboration with a broad panel of US and international stakeholders including representatives from the United States Food and Drug Administration, medicine, academia, industry, the military, parents and sudden cardiac arrest/death prevention advocates, and the public. Primary and secondary prevention of sudden cardiac death in youth were discussed in depth with a goal of developing consensus on uniform approaches which could be applied nationally.

Implementing ultrasound in emergency medical services: assessing physician proficiency and training requirements

BACKGROUND

Bedside ultrasound plays an important role in diagnostics and monitoring, especially in emergency medicine. Modern technology makes ultrasound available in a mobile and portable form, so it can be used even in prehospital emergency care with several interventional and diagnostic applications. This also raises the question of what kind of education and training is necessary for EMS (emergency medical services) physicians to be able to use Point-of-Care Ultrasound (POCUS) in the prehospital setting.

AIMS

This observational study investigates the use of prehospital POCUS in a rural EMS area. It focuses the question of what level of competence is needed for EMS physicians to use POCUS adequately in the prehospital emergency setting for correct application and interpretation of the findings.

METHOD

This was a quality assurance measure designed as a prospective cohort study. We investigated POCUS examinations performed by EMS physicians in the EMS Service Area of Nuremberg City, Germany between June 2021 and July 2022. Patients transported to three specific hospitals in Nuremberg city after care were followed up and the prehospital findings were compared with the in-hospital radiological results. The number of correct findings was correlated with the level of competence in POCUS examinations of the performing EMS physicians. Various classifications of competence were used to assess the influence of training and education on the safe application of prehospital POCUS.

RESULTS

Two hundred fifty-eight prehospital POCUS examinations were documented, with 108 followed up, including 268 sonographic findings. There was a wide range of indications for POCUS use. In 79.5% of cases the prehospital findings correspond with those in-hospital. By correlating the correct findings with the participants level of competence, there was no significant difference between POCUS-experienced and -inexperienced EMS physicians, even when divided into different categories.

CONCLUSION

POCUS can be used in prehospital emergency care for a wide range of indications safely, with a high number of correct diagnoses and findings. Our results suggest that emergency POCUS is easy to learn and EMS physicians do not need intensive training to perform POCUS adequately in the prehospital setting.

TAKE HOME MESSAGES

Mobile ultrasound appears to be useful in the prehospital setting It can be used by EMS physicians even without extensive prior experience and expertise POCUS is able to find important findings for prehospital patient's care with a high level of certainty.

Emerging antibiotic resistance in bacterial bloodstream infections: a clinical study at the Holy Family Hospital, Nkawkaw, Ghana

BACKGROUND

Bacteraemia, a critical bloodstream infection caused by various bacterial pathogens, poses significant health challenges, particularly when compounded by antibiotic resistance. This current study determined the prevalence of bloodstream bacterial isolates and their antibiotic-resistant patterns at the Holy Family Hospital, Nkawkaw, Ghana, spanning a six-year period.

METHODOLOGY

A hospital-based retrospective study was carried out to review records of bacterial isolates of bloodstream infections and their antibiotic-resistant pattern among patients who visited the Holy Family Hospital between 2018 and 2023. The data was collected into an Excel sheet version 2021, cleaned, and exported to the appropriate statistical software, SPSS v26 for statistical analysis. A P-value less than 0.05 was considered statistically significant for all analyses.

RESULTS

Of 3,228 records in this study, the majority (66.0%) were found to be under 1 year of age, while 18.6% were aged 1-10 years. The prevalence of bacteraemia was 8.7% (95% CI: 7.8-9.7%). Klebsiella species was found to be the most prevalent at 30.2%, followed by S. aureus (26.0%). The highest levels of antibiotic resistance were detected against tetracycline (94.5%), penicillin (92.3%), and chloramphenicol (90.9%). Also, significant resistance was also found against vancomycin (88.3%), cefuroxime (86.5%), and cloxacillin (84.4%). Conversely, amikacin demonstrated the highest susceptibility rate (90.5%), followed by ciprofloxacin (75.0%).

CONCLUSION

The study highlights the significant public health burden posed by bacteraemia and the growing challenge of antibiotic resistance. The prevalence of bacteraemia, particularly caused by Gram-negative organisms such as Klebsiella species and E. coli underscores the need for targeted interventions to improve infection control in healthcare settings.

Concepts for point-of-care ultrasound training in low resource settings: a scoping review

BACKGROUND

Point-of-care ultrasound (POCUS) is a potent diagnostic tool especially in resource-limited settings. The implementation of POCUS diagnostics requires adequate training of POCUS operators. This scoping review aimed to identify and describe POCUS training concepts that have been applied in low-and middle-income countries (LMICs).

METHODS AND FINDINGS

All studies on diagnostic POCUS training in LMICs that could be found in the Cochrane, Embase, Google Scholar, and Medline databases up to July 6, 2023, were included and data was extracted for descriptive analysis. The review protocol was registered at OSF https://doi.org/10.17605/OSF.IO/8FQJW . A total of 53 publications were included with 59% of studies (n = 31) conducted in Africa and 23% (n = 12) in Asia. The majority of studies (n = 41, 81%) described short courses amongst which 40% were one-off sessions and 60% described longitudinal trainings. Curricula were mostly related to emergency medicine and obstetrics and organ-focused protocols (lung n = 29 (54%), cardiac n = 28 (53%), obstetric n = 23 (43%)). Trainees were largely medical doctors and clinical officers with minimal or absent ultrasound skills. Training challenges included resource constraints and lack of context adaptation. Best practice recommendations included focus on hands-on training, low trainer to trainee ratio, protected training time, online training options, use of local trainers, short and concise training manuals in print, continuous supervision and early and on-going evaluation, as well as tele-mentoring.

CONCLUSIONS

Context integration and focus on local needs, trainer availability and suitability, durable equipment and maintenance, as well as emphasis on hands on training including patients with relevant pathology, were key aspects for targeted and sustainable POCUS training in LMICs identified in this review.

Integration of smart glasses in telementoring for simulated medical procedures

PURPOSE

To demonstrate the complete process of telementoring implementation using augmented-reality smart glasses for performing a simulated medical procedure.

METHODS

Fifteen participants, including physicians and medical students, were recruited to participate in a telementoring session with an educational focus during simulated thoracostomy with closed pleural drainage. A questionnaire assessing technology usability and usefulness was administered, and the results were analyzed by Cronbach's alfa and multiple correspondence analysis (MCA).

RESULTS

The mean age of the participants was 28.8 and 66.67% of them were women. The test results indicated a Cronbach's alpha of 78% and an MCA of 49.48% for the first three dimensions.

CONCLUSION

The results showed that smart glasses are easy to use and facilitate communication among the professionals involved, providing comfort and safety to participants of care simulations. Additionally, smart glasses were considered to have perceived usefulness.

Early prediction of sepsis in emergency department patients using various methods and scoring systems

BACKGROUND

Early recognition of sepsis, a common life-threatening condition in intensive care units (ICUs), is beneficial for improving patient outcomes. However, most sepsis prediction models were trained and assessed in the ICU, which might not apply to emergency department (ED) settings.

AIM

To establish an early predictive model based on basic but essential information collected upon ED presentation for the follow-up diagnosis of sepsis observed in the ICU.

STUDY DESIGN

This study developed and validated a reliable model of sepsis prediction among ED patients by comparing 10 different methods based on retrospective electronic health record data from the MIMIC-IV database. In-ICU sepsis was identified as the primary outcome. The potential predictors encompassed baseline demographics, vital signs, pain scale, chief complaints and Emergency Severity Index (ESI). 80% and 20% of the total of 425 737 ED visit records were randomly selected for the train set and the test set for model development and validation, respectively.

RESULTS

Among the methods evaluated, XGBoost demonstrated an optimal predictive performance with an area under the curve (AUC) of 0.90 (95% CI: 0.90-0.91). Logistic regression exhibited a comparable predictive ability to XGBoost, with an AUC of 0.89 (95% CI: 0.89-0.90), along with a sensitivity and specificity of 85% (95% CI: 0.83-0.86) and 78% (95% CI: 0.77-0.80), respectively. Neither of the five commonly used severity scoring systems demonstrated satisfactory performance for sepsis prediction. The predictive ability of using ESI as the sole predictor (AUC: 0.79, 95% CI: 0.78-0.80) was also inferior to the model integrating ESI and other basic information.

CONCLUSIONS

The use of ESI combined with basic clinical information upon ED presentation accurately predicted sepsis among ED patients, strengthening its application in ED.

RELEVANCE TO CLINICAL PRACTICE

The proposed model may assist nurses in risk stratification management and prioritize interventions for potential sepsis patients, even in low-resource settings.

Evaluation of Presepsin for Early Diagnosis of Sepsis in the Emergency Department

Background: to date, there are no specific markers available for diagnosing sepsis. Diagnosis is, indeed, mainly determined by clinical suspicion and the evaluation of the patient's overall condition. This evaluation involves assessing various inflammatory markers, such as C-reactive protein (CRP) and procalcitonin (PCT), along with markers of tissue hypoxia, such as serum lactate. Additionally, it includes scores that account for complete blood count (CBC), organ function markers, and the patient's vital parameters, including SOFA, qSOFA, SIRS, and NEWS. Over the years, various potential biomarkers have been studied; among these presepsin appears to offer some significant advantages. Objective: Presepsin, which is the N-terminal fragment of the soluble component of CD14, is primarily elevated in infectious conditions. Its levels rise much earlier in the context of infection compared to currently used biomarkers. As a result, Presepsin shows promise for the early identification of septic patients and could aid in prognostic assessment, allowing clinicians to prioritize care for critically ill individuals. Methods: this study aims to evaluate the role of serum presepsin in the early diagnosis of sepsis in patients who present to the emergency room with a clinical suspicion of sepsis. The secondary objectives include comparing the diagnostic performance of presepsin with traditional biomarkers currently used for sepsis diagnosis and assessing its utility as a prognostic biomarker for mortality risk stratification, in comparison with validated severity prediction scores. Result: Presepsin had valuable diagnostic utility for sepsis (AUC 0.946, p < 0.001) comparable to PCT (AUC 0.905, p < 0.001). Conclusions: the combination of Presepsin, PCT, and EWS yielded the highest diagnostic accuracy for sepsis.

Systematic Review of Commercially Available Clinical CMUT-Based Systems for Use in Medical Ultrasound Imaging: Products, Applications, and Performance

An emerging alternative to conventional piezoelectric technologies, which continue to dominate the ultrasound medical imaging (US) market, is Capacitive Micromachined Ultrasonic Transducers (CMUTs). Ultrasound transducers based on this technology offer a wider frequency bandwidth, improved cost-effectiveness, miniaturized size and effective integration with electronics. These features have led to an increase in the commercialization of CMUTs in the last 10 years. We conducted a review to answer three main research questions: (1) What are the commercially available CMUT-based clinical sonographic devices in the medical imaging space? (2) What are the medical imaging applications of these devices? (3) What is the performance of the devices in these applications? We additionally reported on all the future work expressed by modern studies released in the past 2 years to predict the trend of development in future CMUT device developments and express gaps in current research. The search retrieved 19 commercially available sonographic CMUT products belonging to seven companies. Four of the products were clinically approved. Sonographic CMUT devices have established their niche in the medical US imaging market mainly through the Butterfly iQ and iQ+ for quick preliminary screening, emergency care in resource-limited settings, clinical training, teleguidance, and paramedical applications. There were no commercialized 3D CMUT probes.

Contribution of point-of-care ultrasound in the prehospital management of patients with non-trauma acute dyspnea: a systematic review and meta-analysis

Acute dyspnea is a common symptom whose management is challenging in prehospital settings. Point-of-care ultrasound (POCUS) is increasingly accessible because of device miniaturization. To assess the contribution of POCUS in the prehospital management of patients with acute nontraumatic dyspnea, we performed a systematic review on nontrauma patients of any age managed in the prehospital setting for acute dyspnea and receiving a POCUS examination. We searched seven databases and gray literature for English-language studies published from January 1995 to November 2023. Two independent reviewers completed the study selection, data extraction, and risk of bias assessment. The primary outcome was the assessment of the contribution of POCUS to feasibility, diagnostic, therapeutic, prognosis, patient referral, and transport vector modification. Twenty-three studies were included. The risk of bias assessment identified 3 intermediate-risk, 18 serious-risk, and 2 critical-risk studies. Three studies reported moderate to excellent feasibility for lung POCUS, and three studies reported poor to mediocre feasibility for cardiac POCUS. The median duration of the POCUS examination was less than 5 minutes (six studies). POCUS improved diagnostic identification (seven studies). The diagnostic accuracy of POCUS was excellent for pneumothorax (sensitivity = 100%, specificity = 100%, two studies), very good for acute heart failure (sensitivity = 71-100%, specificity = 72-95%, eight studies), good for pneumonia (sensitivity = 88%, specificity = 59%, one study), and moderate for pleural effusion (sensitivity = 26-53%, specificity = 83-92%, two studies). Treatment was modified in 11 to 54% of the patients (seven studies). POCUS had no significant effect on patient prognosis (two studies). POCUS contributed to patient referrals and transport vectors in 51% (four studies) and 25% (three studies) of patients, respectively. The evidence supports the use of POCUS for managing acute nontraumatic dyspnea in the prehospital setting in terms of feasibility, overall diagnostic contribution, and, particularly, lung ultrasound for acute heart failure diagnosis. Moreover, POCUS seems to have a therapeutic contribution. There is not enough evidence supporting the use of POCUS for pneumonia, pleural effusion, pneumothorax, chronic obstructive pulmonary disease, or asthma exacerbation diagnosis, nor does it support prognostic, patient referral, and transport vector contribution. A high level of evidence is lacking and needed.

The diagnostic performance of automatic B-lines detection for evaluating pulmonary edema in the emergency department among novice point-of-care ultrasound practitioners

PURPOSE

B-lines in lung ultrasound have been a critical clue for detecting pulmonary edema. However, distinguishing B-lines from other artifacts is a challenge, especially for novice point of care ultrasound (POCUS) practitioners. This study aimed to determine the efficacy of automatic detection of B-lines using artificial intelligence (Auto B-lines) for detecting pulmonary edema.

METHODS

A retrospective study was conducted on dyspnea patients treated at the emergency department between January 2023 and June 2024. Ultrasound documentation and electronic emergency department medical records were evaluated for sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of auto B-lines in detection of pulmonary edema.

RESULTS

Sixty-six patients with a final diagnosis of pulmonary edema were enrolled, with 54.68% having positive B-lines in lung ultrasound. Auto B-lines had 95.6% sensitivity (95% confidence interval [CI]: 0.92-0.98) and 77.2% specificity (95% CI: 0.74-0.80). Physicians demonstrated 82.7% sensitivity (95% CI: 0.79-0.97) and 63.09% sensitivity (95% CI: 0.58-0.69).

CONCLUSION

The auto B-lines were highly sensitive in diagnosing pulmonary edema in novice POCUS practitioners. The clinical integration of physicians and artificial intelligence enhances diagnostic capabilities.

Enhanced Diagnostic Precision in Revisited Emergency Patients via Point-of-Care Ultrasound: A Tool for Emergency Department Quality Management

PURPOSE

Unscheduled return visits to the emergency department (ED) were categorized into physician-related, illness-related, and patient-related factors, which are associated with an increased risk of adverse health outcomes, including patient dissatisfaction, infections, hospitalization, transfer to another facility, and mortality. Individuals within 48-72 hours of the initial visit are deemed at elevated risk for diagnostic or management-related errors. The Point-of-care ultrasound (POCUS) may serve as a bedside tool to reduce medical errors by enhancing diagnostic precision. This study aims to determine the diagnostic accuracy of POCUS for detecting various illnesses in revisited patients in the emergency department.

PATIENTS AND METHODS

A retrospective observational study was conducted on unplanned revisits by patients to the emergency department within 72 hours, spanning the period from January 2023 to September 2024. Sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were evaluated based on electronic emergency department medical records and ultrasound documentation.

RESULTS

Five hundred seventy patients were included in this study. POCUS demonstrated a diagnostic accuracy of 75.61% (95% CI 71.87, 79.09), a sensitivity of 81.87% (95% CI 77.65, 85.58), a specificity of 62.50% (95% CI 55.08, 69.51), a positive likelihood ratio of 2.18 (95% CI 1.80, 2.65), and a negative likelihood ratio of 0.29 (95% CI 0.23, 0.37).

CONCLUSION

POCUS demonstrated greater diagnostic accuracy, which may enhance diagnostic precision in revisited patients with various illnesses.

Predicting the Need for Tertiary Trauma Care Using a Multivariable Model: A 4-Year Retrospective Cohort Study

Introduction

Delays in accessing an appropriate level of care can lead to significant morbidity or even mortality of trauma patients. This study aimed to develop a simplified prehospital predictive model to determine the need for tertiary care trauma centers (TTC), enabling timely and appropriate transport decisions by emergency medical service (EMS) teams.

Methods

This is a retrospective cohort study conducted at the emergency department (ED) of Ramathibodi Hospital between January 2020 and April 2024. Prehospital trauma patients aged ≥15 years who were transported by EMS were included in the study. Patients were divided into two groups with and without the need for TTC, and the independent predictive factors of the need for TTC were explored using multivariable regression analysis.

Results

The study included 440 trauma patients, with 31.1% requiring TTC. The predictors of the need for TTC included age (coefficient (Coef.) -0.003; 95% confidence interval (CI): -0.018 to 0.012; P=0.693), traffic mechanism (Coef. 0.848; 95%CI: 0.150 to 1.546; P=0.017), respiratory rate (Coef. 0.044; 95%CI: -0.037 to 1.124; P=0.285), heart rate (Coef. -0.004; 95%CI: -0.020 to 0.012; P=0.610), and Glasgow Coma Scale (Coef. -0.312; 95%CI: -0.451 to -0.173; P<0.001). The predictive model categorized patients into low, moderate, and high-risk groups. Patients who were categorized in the high-risk group showed a positive likelihood ratio (LHR+) of 14.88 for requiring TTC. The model achieved an area under the receiver operating characteristic curve (AuROC) of 73%, indicating the good discriminative ability of this prediction model.

Conclusions

The predictive model classifies trauma patients into three risk groups based on five prognostic variables, which are able to predict the likelihood of requiring TTC. Internal validation has verified its high level of accuracy in trauma triage.

Through the lens: A qualitative exploration of nurses' experiences of smart glasses in urgent care

AIM

To investigate the real-world experiences of nurses' using smart glasses to triage patients in an urgent care centre.

DESIGN

A parallel convergent mixed-method design.

METHODS

We collected data through twelve in-depth interviews with nurses using the device and a survey. Recruitment continued until no new themes emerged. We coded the data using a deductive-thematic approach. Qualitative and survey data were coded and then mapped to the most dominant dimension of the sociotechnical framework. Both the qualitative and quantitative findings were triangulated within each dimension of the framework to gain a comprehensive understanding of user experiences.

RESULTS

Overall, nurses were satisfied with using smart glasses in urgent care and would recommend them to others. Nurses rated the device highly on ease of use, facilitation of training and development, nursing empowerment and communication. Qualitatively, nurses generally felt the device improved workflows and saved staff time. Conversely, technological challenges limited its use, and users questioned its sustainability if inadequate staffing could not be resolved.

CONCLUSION

Smart glasses enhanced urgent care practices by improving workflows, fostering staff communication, and empowering healthcare professionals, notably providing development opportunities for nurses. While smart glasses offered transformative benefits in the urgent care setting, challenges, including technological constraints and insufficient organisational support, were barriers to sustained integration.

IMPLICATIONS FOR PRACTICE

These real-world insights encompass both the benefits and challenges of smart glass utilisation in the context of urgent care. The findings will help inform greater workflow optimisation and future technological developments. Moreover, by sharing these experiences, other healthcare institutions looking to implement smart glass technology can learn from the successes and barriers encountered, facilitating smoother adoption, and maximising the potential benefits for patient care.

REPORTING METHOD

COREQ checklist (consolidated criteria for reporting qualitative research).

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

Flight testing of drone-delivered automated external defibrillators for simulated out-of-hospital cardiac arrest in suburban Thailand

The use of automated external defibrillators (AEDs) in a timely manner is critical for improving survival rates in out-of-hospital cardiac arrest (OHCA) cases. However, in developing countries, logistical and infrastructural challenges often result in delays, particularly in suburban areas. This study evaluates the feasibility and safety of using drones to deliver AEDs in suburban OHCA scenarios. A series of ninety test flights were conducted using a DJI Matrice 600 drone (DJI, China) to deliver a Philips HeartStart AED (Philips, Netherlands) across varying payloads. Bystanders in simulated OHCA situations identified their location via mobile applications, enabling the drone operator to dispatch the drone beyond the pilot's line of sight. The results showed a 97.7% success rate in AED delivery, with a median flight distance of 4042 m and a median response time of 7 min and 39 s. Despite payload variations, the drone maintained adequate speed and landing accuracy, with a mean speed of 9.17 m per second and a median landing error of 122 centimeters. The findings suggest that drones have significant potential for improving emergency medical responses in suburban areas of developing countries. Integration into emergency services could address current delays, though further research is necessary to optimize performance under varying conditions.

Transition of EMS workflow from radio to bell signals to shorten activation time in multiple casualty incident

Multiple casualty incident (MCI) are critical situations mandating an immediate response. Traditionally, members of emergency medical services (EMS) are notified about MCI through radio signals. However, communication failures can lead to delays in activation time of EMS operations. The use of bell signals is proposed as a solution to address these issues. This study uses a retrospective pre-post design evaluating the impact of the bell and radio signal on activation times for EMS operation in MCI. Data were collected from January 2020 to December 2023 and divided into two phases: radio signal use during 2020-2021 (pre-design), and bell signal use during 2022-2023 (post-design). In the event of MCI, the bell or radio is used primarily to alert medical personnel. After the MCI was recognized during the pre-design phase, the dispatcher utilized the radio signal, calling out all EMS personnel twice via radio at 171.425 MHz, with a one-minute interval between communication to notify them of the incident. The ED staff would be informed of these incidents through radio or telephone communication by EMS personnel. In the post-design phase, the dispatcher utilized the bell signal, ringing it three times to alert all staff. Activation time and equipment used by EMS during MCI operations was recorded for both phases. A total of 105 MCI with EMS operations were recorded. In the bell signal group, 52.1% (n = 199) of the participants were male. Mass transportation incidents accounted for the most of the MCI, comprising 73.6% in the bell signal group and 73.1% in the radio signal group. The average activation time was significantly shorter for the bell signal (1.54 min) compared to the radio signal (3.60 min) (P < 0.001). The average response time for the bell signal was 13.20 min, while the radio signal response time averaged 16.10 min (P = 0.042). Early activation time (less than 2 min after EMS dispatch) was significantly more likely in the Bell signal group (adjusted odds ratio, 1.25; 95% confidence interval, 1.10-2.45) than in the Radio signal group. The activation and response times for EMS operations during MCI were significantly reduced by using bell signals to alert EMS staff.

Effects of Emergency Medical Service Response Time on Survival Rate of Out-of-Hospital Cardiac Arrest Patients: a 5-Year Retrospective Study

Introduction

Emergency medical service (EMS) response time is a critical factor in managements of out-of-hospital cardiac arrest (OHCA) cases. This study aimed to investigate the effects of EMS response time on survival of OHCA patients.

Methods

This study employed a retrospective cohort design focused on prognosis research. Data was collected from the Erawan EMS Dispatch Center of the Bangkok Metropolitan Administration from January 2019 to December 2023. All OHCA cases visited by dispatched prehospital teams in Bangkok were included. Multivariable logistic regression was used to analyze the effect of response time on survival at scene, survival to emergency department (ED), and survival to hospital discharge of OHCA cases.

Results

Among the 5,433 OHCA patients included in the study, 29.17% achieved return of spontaneous circulation at the scene, 6.9% survived to ED, and 1% survived to hospital discharge. Each 1-minute increase in response time decreased the likelihood of survival at the scene by 6% (OR: 0.94, p < 0.001), survival to ED admission by 4% (OR: 0.96, p < 0.001), and survival to hospital discharge by 6% (OR: 0.94, p = 0.006). Response times under 8 minutes significantly improved outcomes, with survival at the scene increasing by 2.31 times (p < 0.001), survival to ED by 1.76 times (p < 0.001), and survival to hospital discharge by 2.09 times (p = 0.048).

Conclusions

A maximum response time of 8 minutes significantly enhances survival outcomes, including survival at the scene, survival to ED, and survival to hospital discharge. Furthermore, each 1-minute increase in response time is associated with a 6% reduction in the likelihood of survival to hospital discharge.

Exploring the experiences and challenges of motorcycle ambulance personnel in pre-hospital emergency healthcare services: A qualitative study

BACKROUNDMotorcycle ambulances are particularly useful in navigating narrow and congested areas during premium hours due to their ability to provide rapid access to patients in pre-hospital emergency healthcare services (PHEHS), possessing suitable and necessary advanced life support accessories, and their speed, flexibility, and ease of maneuverability.OBJECTIVEThis study aims to examine the experiences and challenges encountered by motorcycle ambulance workers in PHEHS.METHODSThis study adopts a qualitative research methodology, specifically employing a phenomenological approach within the framework of a case study. The research sample consists of 19 paramedics and Emergency Medical Technicians (EMTs) working on motorcycle ambulances. Purposeful sampling method, specifically the snowball sampling technique, was employed in selecting the sample. Research data were collected through in-depth interviews conducted using a semi-structured interview form, from August 2022 to February 2023. The interviews were transcribed, coded, and thematically analyzed using the MAXQDA program.RESULTSParticipants shared their experiences and the problems they encountered while performing their duties across four themes: purpose of motorcycle ambulances, most frequently assigned cases, challenges encountered, and the importance of teamwork.CONCLUSIONSIt is crucial to ensure personnel safety by forming the motorcycle ambulance team from selected individuals, subjecting the selected personnel to the same standard and comprehensive advanced driving and technical training, regulating working hours, increasing the number of personnel, and fostering teamwork. Further efforts are needed to improve the working conditions of motorcycle ambulance services.

Cardiac arrest: Pre-hospital strategies to facilitate successful resuscitation and improve recovery rates

The estimated annual incidence of out-of-hospital cardiac arrest (OHCA) is approximately 120 cases per 100000 inhabitants in western countries. Although the rates of bystander cardiopulmonary resuscitation (CPR) and use of automated external defibrillator are increasing, the likelihood of survival to hospital discharge is no more than 8%. To date, various devices and methods have been utilized in the initial CPR approach targeting to improve survival and neurological outcomes in OHCA patients. The aim of this review is to discuss strategies that facilitate resuscitation, increase the chance to achieve return to spontaneous circulation and improve survival to hospital discharge and neurological outcomes in the pre-hospital setting.

Enhancing prehospital decision-making: exploring user needs and design considerations for clinical decision support systems

BACKGROUND

In prehospital emergency care, providers face significant challenges in making informed decisions due to factors such as limited cognitive support, high-stress environments, and lack of experience with certain patient conditions. Effective Clinical Decision Support Systems (CDSS) have great potential to alleviate these challenges. However, such systems have not yet been widely adopted in real-world practice and have been found to cause workflow disruptions and usability issues. Therefore, it is critical to investigate how to design CDSS that meet the needs of prehospital providers while accounting for the unique characteristics of prehospital workflows.

METHODS

We conducted semi-structured interviews with 20 prehospital providers recruited from four Emergency Medical Services (EMS) agencies in an urban area in the northeastern U.S. The interviews focused on the decision-making challenges faced by prehospital providers, their technological needs for decision support, and key considerations for the design and implementation of a CDSS that can seamlessly integrate into prehospital care workflows. The data were analyzed using content analysis to identify common themes.

RESULTS

Our qualitative study identified several challenges in prehospital decision-making, including limited access to diagnostic tools, insufficient experience with certain critical patient conditions, and a lack of cognitive support. Participants highlighted several desired features to make CDSS more effective in the dynamic, hands-busy, and cognitively demanding prehospital context, such as automatic prompts for possible patient conditions and treatment options, alerts for critical patient safety events, AI-powered medication identification, and easy retrieval of protocols using hands-free methods (e.g., voice commands). Key considerations for successful CDSS adoption included balancing the frequency and urgency of alerts to reduce alarm fatigue and workflow disruptions, facilitating real-time data collection and documentation to enable decision generation, and ensuring trust and accountability while preventing over-reliance when using CDSS.

CONCLUSION

This study provides empirical insights into the challenges and user needs in prehospital decision-making and offers practical and system design implications for addressing these issues.

Modified National Early Warning Scores (MNEWS) for Predicting the Outcomes of Suspected Sepsis Patients; A Prospective Cohort Study

Introduction

The National Early Warning Score (NEWS) is commonly used to identify patients at high mortality risk. However, it has notable limitations. In this study, to enhance the accuracy, we revised it and evaluated the performance of modified NEWS (MNEWS) in predicting the outcomes of suspected sepsis patients.

Methods

This single-center, prospective cohort study was conducted on patients with suspected sepsis to evaluate the accuracy of MNEWS in predicting mortality, survival to discharge, vasopressor requirements, and the need for mechanical ventilation. The MNEWS comprises the NEWS variables plus age, chronic major organ dysfunction, malignancy, functional status, and specific infected organ involvement. Sensitivity, specificity, likelihood ratio (LR), and area under the receiver operating characteristic curve (AUROC) were used to evaluate the performance of the MNEWS in predicting the studied outcomes.

Results

Of the 1,393 patients included in this study, 209 died. Mean MNEWS was significantly higher in non-survivors than survivors (19.8 vs. 14.9, p<0.001). The AUROC of MNEWS in predicting 30-day mortality was 0.82 (95% CI: 0.79-0.85). MNEWS ≥ 18 had the highest accuracy for 30-day mortality prediction with 76.1% sensitivity, 75% specificity, positive LR of 3.13, and AUROC of 0.76 (95% CI: 0.73-0.79). The AUROC of MNEWS ≥18 for predicting survival until discharge, need for vasopressors, and need for mechanical ventilation were 0.75 (95% CI: 0.72-0.78), 0.72 (95% CI: 0.69-0.75), and 0.76 (95% CI: 0.73-0.79), respectively. Additionally, MNEWS ≥18 demonstrated superior predictive performance, compared with NEWS ≥7 and qSOFA ≥2 for various clinical outcomes.

Conclusions

The MNEWS was similar to the NEWS in overall predictive accuracy for 30-day mortality but exhibited a higher predictive accuracy than did the qSOFA score. Notably, MNEWS ≥18 was a significant indicator of 30-day mortality risk, as well as the likelihood of requiring vasopressors, survival to discharge, and 7-day mortality.

2024 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

This is the eighth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations; a more comprehensive review was done in 2020. This latest summary addresses the most recent published resuscitation evidence reviewed by the International Liaison Committee on Resuscitation task force science experts. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research.

Point-of-care ultrasound use in austere environments: A scoping review

BACKGROUND/OBJECTIVES

Technological developments in point-of-care ultrasound (POCUS), particularly with portable devices, are transforming POCUS use in austere, resource-limited environments (RLS) distinct from typical hospital or medical settings. POCUS has potential to improve diagnostic accuracy in military combat zones, low-resource environments such as the desert or tropics, microgravity, and high altitudes. Our updated narrative scoping review describes POCUS use in these global settings.

METHODS

Using the PRISMA-ScR guidelines, two ultrasound-trained emergency physicians searched PubMed, Embase, and Web of Science on August 6, 2024 for "point-of-care ultrasound in austere environments" and each individual category. Study titles and abstracts were independently screened, then full manuscripts, and data was abstracted with a data collection table. 324 articles met inclusion criteria: research studies describing POCUS in austere environments; involving healthcare professionals; and in English. We excluded abstracts, studies not involving POCUS in austere environments, and non-clinical studies. Reviewers critically appraised studies using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) Quality Assessment Tool.

RESULTS

There were 39 military or conflict zone studies, 101 prehospital, 148 in RLS including low- and middle-income countries, 12 outer space, 15 high altitude, and 32 involving POCUS use in multiple austere environments. There were 6 randomized-control trials, 11 systematic/scoping reviews, 13 narrative reviews, 112 prospective observational/cohort, 34 prospective cross-sectional studies, 23 retrospective, 6 feasibility, 45 case reports, 13 case series, and 5 educational curriculum studies. GRADE study quality was variable, with 74 high quality, 129 moderate, 82 low, and 56 very low.

CONCLUSION

The existing literature is mixed with variability in study settings, design, and POCUS examination types, providing an initial understanding of POCUS applications. Most studies are in RLS or prehospital settings. Additional high-quality studies are needed to guide POCUS training, disseminate use in non-hospital settings, and maximize impact for improved clinical outcomes in diverse austere environments.

Automatic B-lines: a tool for minimizing time to diuretic administration in pulmonary edema patients in the emergency department of a developing country

BACKGROUND

Effective management of pulmonary edema in the emergency department (ED) is crucial given its significant global impact on health. This study aimed to investigate the hypothesis: "Does the utilization of Automatic B-lines via ultrasonography in patients with pulmonary edema facilitate faster diuretic administration in a developing country?"

METHODS

This retrospective observational study was conducted at a tertiary academic center in Thailand. Patients with pulmonary edema admitted to the ED between January 2023 and June 2024 were enrolled. Ultrasound documentation and electronic ED medical records were compared to assess the time of diuretic administration between patients who had lung ultrasounds utilizing automatic B-lines and those who had manual B-lines counted by physician eye inspection. Multivariate logistic regression was employed to examine the relationship between the use of automatic B-lines and early diuretic administration.

RESULTS

The study included 134 patients with pulmonary edema. The time to diuretic administration was significantly shorter in the automatic B-lines group (median time [Q1-Q3], 55 min; range, 35-110 min) compared to the non-automatic B-lines group (median time, 100 min; range, 75-145 min). In the multivariable logistic regression analysis, early diuretic administration within 60 min of triage was significantly more likely in the automatic B-lines group (adjusted odds ratio, 1.45; 95% confidence interval, 1.10-2.45) than in the non-automatic B-lines group.

CONCLUSIONS

In a developing country, patients with pulmonary edema who had lung ultrasound evaluation with automated B lines experienced a fastest diuresis compared to those who utilized ultrasonography without automatic B lines. Implementing automatic B-lines as an early screening protocol could enhance clinical practice in the ED.

Optimising telecommunicator recognition of out-of-hospital cardiac arrest: A scoping review

Aim

To summarize existing literature and identify knowledge gaps regarding barriers and enablers of telecommunicators' recognition of out-of-hospital cardiac arrest (OHCA).

Methods

This scoping review was undertaken by an International Liaison Committee on Resuscitation (ILCOR) Basic Life Support scoping review team and guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR). Studies were eligible for inclusion if they were peer-reviewed and explored barriers and enablers of telecommunicator recognition of OHCA. We searched Ovid MEDLINE® and Embase and included articles from database inception till June 18th, 2024.

Results

We screened 9,244 studies and included 62 eligible studies on telecommunicator recognition of OHCA. The studies ranged in methodology. The majority were observational studies of emergency calls. The barriers most frequently described to OHCA recognition were breathing status and agonal breathing. The most frequently tested enabler for recognition was a variety of dispatch protocols focusing on breathing assessment. Only one randomized controlled trial (RCT) was identified, which found no difference in OHCA recognition with the addition of machine learning alerting telecommunicators in suspected OHCA cases.

Conclusion

Most studies were observational, assessed barriers to recognition of OHCA and compared different dispatch protocols. Only one RCT was identified. Randomized trials should be conducted to inform how to improve telecommunicator recognition of OHCA, including recognition of pediatric OHCAs and assessment of dispatch protocols.

2024 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces

This is the eighth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations; a more comprehensive review was done in 2020. This latest summary addresses the most recent published resuscitation evidence reviewed by the International Liaison Committee on Resuscitation task force science experts. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research.

The effect of smart glasses combined with ultrasound on radial arterial catheterization: a randomized controlled trial

BACKGROUND

The integration of smart glasses with ultrasound technology offers a novel approach to improve the efficiency of radial arterial catheterization. Few studies have investigated the effectiveness of smart glasses in enhancing procedural outcomes in a clinical setting. This study aims to assess whether smart glasses combined with ultrasound can improve the initial success rate of radial artery catheterization compared to traditional ultrasound-guided methods in adults.

METHODS

This single-blinded, randomized controlled trial enrolled patients aged 18-70 with American Society of Anesthesiologists physical status I-III, who required radial artery catheterization as part of their procedure under general anesthesia. Patients were randomized 1:1 into the ultrasound group and the smart glasses group. Radial arterial catheterization was carried out by one of six anesthesiologists before general anesthesia. The primary endpoint was the first puncture success rate. Secondary endpoints included hand-eye coordination (measured by head rotations, probe repositioning and needle redirections), operator's satisfaction.

RESULTS

A total of 222 patients were analyzed, with the smart glasses group demonstrating a higher rate of first puncture success compared to the control group (88.3% [98/111] vs. 72.1% [80/111]; P = 0.002; relative risk [RR], 1.23; 95% CI (1.07, 1.40)). Hand-eye coordination improved significantly in the smart glasses group than the control group, including: fewer number of head rotations (0 [0, 0] vs. 3 [2, 6]; P < 0.001); fewer number of ultrasound probe repositioning (0 [0, 0] vs. 0 [0, 1]; P < 0.001); fewer number of needle redirections (0 [0, 1] vs. 1 [0, 3]; P < 0.001). The proportion of positive satisfaction (81 to 100 points) in the smart glasses group was higher (89.2% [99/111] vs. 69.4% [77/111]; P <  0.001; RR, 1.29; 95% CI (1.12, 1.48)).

CONCLUSIONS

The use of smart glasses significantly improved the first puncture success rate, hand-eye coordination ability and operators' satisfaction in radial arterial catheterization.

TRIAL REGISTRATION

The study was registered at Chictr.org.cn with the number ChiCTR2400081399 on 29/02/2024.

The ligamentous cervical instability etiology of human disease from the forward head-facedown lifestyle: emphasis on obstruction of fluid flow into and out of the brain

Ligamentous cervical instability, especially ligamentous upper cervical instability, can be the missing structural cause and/or co-morbidity for many chronic disabling brain and systemic body symptoms and diagnoses. Due to the forward head-facedown lifestyle from excessive computer and cell phone usage, the posterior ligament complex of the cervical spine undergoes a slow stretch termed "creep" which can, over time, lead to cervical instability and a breakdown of the cervical curve. As this degenerative process continues, the cervical curve straightens and ultimately becomes kyphotic, a process called cervical dysstructure; simultaneously, the atlas (C1) moves forward, both of which can lead to encroachment of the structures in the carotid sheath, especially the internal jugular veins and vagus nerves. This obstruction of fluid flow can account for many brain diseases, and compression and stretch of the vagus nerve for body diseases, including dysautonomia. This article describes the consequences of impaired fluid flow into and out of the brain, especially venous flow through the internal jugular veins, leading to intracranial hypertension (formerly called pseudotumor cerebri). Cervical structural, internal jugular vein, and optic nerve sheath measurements are presented from a retrospective chart review of 227 consecutive patients with no obvious cause for 1 of 8 specific brain or mental health symptoms-anxiety, brain fog, concentration difficulty, depression/hopelessness, headaches, obsessive thoughts, panic attacks, and rumination on traumatic events. A case example is given to demonstrate how cervical structural treatments can open up internal jugular veins and improve a patient's chronic symptoms.

Application of artificial intelligence in triage in emergencies and disasters: a systematic review

INTRODUCTION AND OBJECTIVE

Modern and intelligent triage systems are used today due to the growing trend of disasters and emergencies worldwide and the increase in the number of injured people facing the challenge of using traditional triage methods. The main objective of this study is to investigate the application of artificial intelligence and Technology in the triage of patients injured by disasters and emergencies and the challenges of the implementation of intelligent triage systems.

METHOD

The present study is a systematic review and follows PRISMA guidelines. The protocol of this study was registered in PROSPERO with the code CRD42023471415. To find relevant studies, the databases PubMed, Scopus and Web of Science (ISI) were searched without a time limit until September 2024. The scientific search engine Google Scholar and the references of the final articles were read manually for the final review.

RESULTS

The search identified 2,630 articles, narrowing down to 19 high-quality studies on AI in triage, which improved patient care through optimized resource management and real-time data transmission. AI algorithms like OpenPose and YOLO enhanced efficiency in mass casualty incidents, while e-triage systems allowed for continuous vital sign monitoring and faster triaging. AI tools demonstrated high accuracy in diagnosing COVID-19 (94.57%). Implementing intelligent triage systems faced challenges such as trust issues, training needs, equipment shortages, and data privacy concerns.

CONCLUSION

Developing assessment systems using artificial intelligence enables timely treatment and better resuscitation services for people injured in disasters. For future studies, we recommend designing intelligent triage systems to remove the obstacles in triaging children and disabled people in disasters.

Educational effectiveness of remote training with smart glasses for impression-taking

PURPOSE

To compare the educational outcomes of remote instruction (RI) in impression-taking using smart glasses with those of face-to-face instruction (FI) and paper-based self-learning (SL) and analyze the educational effects, aiming to develop a remote clinical training strategy.

METHODS

Participants were recruited from among the dental residents who were trained in the first-year clinical program at the university hospital in 2023. The participants were divided into three groups as the original skill level was equal, and the groups were assigned RI, FI, printed guidance, and SL. All the participants took impressions of the jaw models attached to the mannequin using alginate impression material. Next, assigned instructions were provided. Then again, the trainees took impressions of the jaw models. The pre- and postinstruction impressions of each participant were evaluated, and the change in the impression score was statistically analyzed.

RESULTS

The pre- and postinstruction scores of the trainees in the RI and FI groups showed a significant increase (p < 0.05), whereas no significant difference was observed in the score changes in the SL group. In the intergroup comparisons, the score changes of the RI and FI groups were greater than those of the SL group, although no significant difference was found between the score changes of the RI and FI groups (p < 0.05).

CONCLUSION

RI in impression-taking using smart glasses has a greater educational effectiveness than paper-based SL. It has also been suggested that RI can have educational efficacy similar to FI.

The Impact of Global Warming on the Rise in Heat-Related Illnesses in Emergency Medical Services

PURPOSE

Global warming is one of the critical problems affecting health, society, and the economy. High temperatures are linked to an increase in heat-related illnesses, which have significantly impacted the public health system, particularly emergency medical services (EMS). Analyzing the pattern of heat-related illness cases in EMS can improve resource utilization and preparedness within the public health system.

PATIENTS AND METHODS

A retrospective study was conducted on EMS data from Srinagarind Hospital, Thailand, covering the summer months (February to May) from 2020 to 2024. Patients with heat-related illnesses were identified in the EMS database using the 10th revision of the International Classification of Diseases (ICD-10) version 2019, specifically codes under "T67 Effects of Heat and Light", which include heat stroke, heat syncope, heat cramps, heat exhaustion, and heat fatigue.

RESULTS

A total of 136 EMS operations from the hospital's database were analyzed. In the summer 2024 group, 95.7% (N=44) of the patients were male. The majority of EMS triage cases required resuscitation (P = 0.020). Outdoor activity was identified as a significant factor related to heat illness, with rates of 83.3%, 92.9%, 93.3%, 97.1%, and 93.5% over the five years of the study. The activation time was 1.30 minutes for the summer of 2024 and 1.24 minutes for the summer of 2023. Notably, the average scene time in the summer 2024 group was significantly longer at 25.2 minutes, compared to 12.0 minutes in the summer 2020 group (P<0.001).

CONCLUSION

Outdoor activity was the most significant risk factor associated with increased heat-related illnesses. Other contributing factors included male gender, age between 20-40 years, scene temperatures above 35°C, and prolonged scene times exceeding 15 minutes.

Prospective and External Validation of Machine Learning Models for Short- and Long-Term Mortality in Acutely Admitted Patients Using Blood Tests

Background: Predicting mortality in emergency departments (EDs) using machine learning models presents challenges, particularly in balancing simplicity with performance. This study aims to develop models that are both simple and effective for predicting short- and long-term mortality in ED patients. Our approach uses a minimal set of variables derived from one single blood sample obtained at admission. Methods: Data from three cohorts at two large Danish university hospitals were analyzed, including one retrospective and two prospective cohorts where prognostic models were applied to predict individual mortality risk, spanning the years 2013-2022. Routine biochemistry analyzed in blood samples collected at admission was the primary data source for the prediction models. The outcomes were mortality at 10, 30, 90, and 365 days after admission to the ED. The models were developed using Light Gradient Boosting Machines. The evaluation of mortality predictions involved metrics such as Area Under the Receiver Operating Characteristic Curve (AUC), sensitivity, specificity, negative predictive values, positive predictive values, and Matthews correlation coefficient (MCC). Results: A total of 43,648 unique patients with 65,484 admissions were analyzed. The models showed high accuracy, with very good to excellent AUC values between 0.87 and 0.93 across different time intervals. Conclusions: This study demonstrates that a single assessment of routine clinical biochemistry upon admission can serve as a powerful predictor for both short-term and long-term mortality in ED admissions.

The association between integrating echocardiography use in the management of septic shock patients and outcomes in the intensive care unit: a systematic review and meta-analysis

OBJECTIVES

Septic shock in critically ill patients can increases morbidity and mortality. We aimed to study the effect on outcomes when integrating point of care (POC) echocardiography in the management of septic shock patients in the Intensive Care Unit (ICU) who are being treated according to the Surviving Sepsis Campaign (SSC) guidelines.

METHODS

An electronic search of MEDLINE through PubMed, clinical trials.gov and google scholar was conducted for the period from January 1990-January 2024 to identify studies of septic shock adult and pediatric patients in the ICU managed according to SSC guidelines with or without POC echocardiography. Three reviewers extracted data independent of each other. Cochrane collaboration tool was used for bias assessment. Random effect meta-analysis used to pool data.

RESULTS

A total of 1701 articles identified. Seven studies included in the final report with a total of 3885 patients. POC echocardiography guided septic shock management was associated with lower in-hospital and 28-day mortality (sOR = 0.82 [95%CI: 0.71-0.95], p = 0.01), more frequent initiation of inotropic support (sOR = 2.42 [95%CI 1.92-3.03], p < 0.0001) and shorter time to achieve lactate clearance (SMD = - 0.87 h [95%CI - 1.23 h to - 0.51 h], p < 0.0001). Summary estimates did not achieve significance for effect of POC echocardiography on 24-h fluid intake (SMD = - 2.11 ml [95%CI - 5.93 ml to 1.72 ml], p = 0.28) on mechanical ventilation-free days (SMD = 0.03 days [95%CI - 0.04 to 0.10], p = 0.94). Shock reversal time analysis was less meaningful due to the small number of studies reporting outcome.

CONCLUSIONS

POC echocardiography guided management in septic shock patients in the ICU can lead to a decrease in mortality, increase in initiation of inotropic support, and a decrease in lactate clearance time. Larger cohort studies and data collection and analysis are needed for further understanding and optimizing standardization of protocols for POC echocardiography use in septic shock patients in the ICU.

Comprehensive Risk Analysis of Emergency Medical Response Systems in Serbian Healthcare: Assessing Systemic Vulnerabilities in Disaster Preparedness and Response

BACKGROUND/OBJECTIVES

Emergency Medical Response Systems (EMRSs) play a vital role in delivering medical aid during natural and man-made disasters. This quantitative research delves into the analysis of risk and effectiveness within Serbia's Emergency Medical Services (EMS), with a special emphasis on how work organization, resource distribution, and preparedness for mass casualty events contribute to overall disaster preparedness.

METHODS

The study was conducted using a questionnaire consisting of 7 sections and a total of 88 variables, distributed to and collected from 172 healthcare institutions (Public Health Centers and Hospitals). Statistical methods, including Pearson's correlation, multivariate regression analysis, and chi-square tests, were rigorously applied to analyze and interpret the data.

RESULTS

The results from the multivariate regression analysis revealed that the organization of working hours (β = 0.035) and shift work (β = 0.042) were significant predictors of EMS organization, explaining 1.9% of the variance (R2 = 0.019). Furthermore, shift work (β = -0.045) and working hours (β = -0.037) accounted for 2.0% of the variance in the number of EMS points performed (R2 = 0.020). Also, the availability of ambulance vehicles (β = 0.075) and financial resources (β = 0.033) explained 4.1% of the variance in mass casualty preparedness (R2 = 0.041). When it comes to service area coverage, the regression results suggest that none of the predictors were statistically significant. Based on Pearson's correlation results, there is a statistically significant correlation between the EMS organization and several key variables such as the number of EMS doctors (p = 0.000), emergency medicine specialists (p = 0.000), etc. Moreover, the Chi-square test results reveal statistically significant correlations between EMS organization and how EMS activities are conducted (p = 0.001), the number of activity locations (p = 0.005), and the structure of working hours (p = 0.001).

CONCLUSIONS

Additionally, the results underscore the necessity for increased financial support, standardized protocols, and enhanced intersectoral collaboration to strengthen Serbia's EMRS and improve overall disaster response effectiveness. Based on these findings, a clear roadmap is provided for policymakers, healthcare administrators, and EMS personnel to prioritize strategic interventions and build a robust emergency medical response system.

Optimizing Defibrillator Deployment with Bus-Mounted Automated External Defibrillator

OBJECTIVES

Early defibrillation with an automated external defibrillator (AED) can effectively improve the survival rate of patients with out-of-hospital cardiac arrest (OHCA). Placing AEDs in public locations can reduce the defibrillation response interval from collapse to defibrillation. Most public AEDs are currently placed in a stationary way (S-AED) with limited coverage area. Bus mounted AED (B-AED) can be delivered directly to the demand point. Although B-AEDs are only available during bus operating hours, they provide greater coverage area. When the number of available AEDs is insufficient, better coverage may be achieved by placing a portion of AEDs as B-AEDs. Our purpose is developing a model to determine the optimal locations of B-AEDs and S-AEDs with a predetermined number of available AEDs. The goal is to maximize the total coverage level of all demand points.

METHODS

We proposed a joint location model to place B-AEDs and S-AEDs based on the p-median problem (JPMP). Using data from Chang'an District, Xi'an City, China, we determined the optimal AED deployment. The performance of JPMP was compared with several other models. The coverage results of JPMP are analyzed in details, including the quantity assignment, coverage level, and geographical location of B-AEDs and S-AEDs. The impact of the bus departure intervals on coverage was also discussed.

RESULTS

The use of B-AEDs results in an average 98.43% increase in the number of covered demand points, and an average 74.05% increase in total coverage level. In optimal AED deployment, B-AEDs coverage follows an inverted U-shaped curve with increasing number of available AEDs. It begins to decrease when all demand points during the operating hours are covered. With a constant number of available AEDs, the total coverage level increases and then decreases as the bus departure interval increases. The larger the number of available AEDs, the smaller the optimal departure interval.

CONCLUSIONS

With a given number of available AEDs, combinational deployment of B-AEDs and S-AEDs significantly improves the coverage level. B-AEDs are recommended when AEDs are insufficient. If more AEDs are available, better coverage can be obtained with reasonable location of S-AEDs and B-AEDs.

One decade of point-prevalence surveys for carriage of extended-spectrum beta-lactamase-producing enterobacterales: whole genome sequencing based prevalence and genetic characterization in a large Dutch teaching hospital from 2013 to 2022

OBJECTIVES

To determine the prevalence, trends, and potential nosocomial transmission events of the hidden reservoir of rectal carriage of extended-spectrum beta-lactamase-producing Enterobacterales (ESBL-E).

METHODS

From 2013 to 2022, yearly point prevalence surveys were conducted in a large Dutch teaching hospital. On the day of the survey, all admitted patients were screened for ESBL-E rectal carriage using peri-anal swabs and a consistent and sensitive selective culturing method. All Enterobacterales phenotypically suspected of ESBL production were analysed using whole genome sequencing for ESBL gene detection and clonal relatedness analysis.

RESULTS

On average, the ESBL-E prevalence was 4.6% (188/4,119 patients), ranging from 2.1 to 6.6% per year. The ESBL-prevalence decreased on average 5.5% per year. After time trend correction, the prevalence in 2016 and 2020 was lower compared to the other year. Among the ESBL-E, Escherichia coli (80%) and CTX-M genes (85%) predominated. Potential nosocomial transmission events could be found in 5.9% (11/188) of the ESBL-E carriers.

CONCLUSIONS

The ESBL-E rectal carriage prevalence among hospitalized patients was 4.6% with a downward trend from 2013 to 2022. The decrease in ESBL-E prevalence in 2020 could have been due to the COVID-19 pandemic and subsequent countrywide measures as no nosocomial transmission events were detected in 2020. However, the persistently low ESBL-E prevalences in 2021 and 2022 suggest that the decline in ESBL-E prevalence goes beyond the COVID-19 pandemic, indicating that overall ESBL-E carriage rates are declining over time. Continuous monitoring of ESBL-E prevalence and transmission rates can aid infection control policy to keep antibiotic resistance rates in hospitals low.

Interpretable Machine Learning Models for Predicting Critical Outcomes in Patients with Suspected Urinary Tract Infection with Positive Urine Culture

(1) Background: Urinary tract infection (UTI) is a leading cause of emergency department visits and hospital admissions. Despite many studies identifying UTI-related risk factors for bacteremia or sepsis, a significant gap remains in developing predictive models for in-hospital mortality or the necessity for emergent intensive care unit admission in the emergency department. This study aimed to construct interpretable machine learning models capable of identifying patients at high risk for critical outcomes. (2) Methods: This was a retrospective study of adult patients with urinary tract infection (UTI), extracted from the Medical Information Mart for Intensive Care IV Emergency Department (MIMIC-IV-ED) database. The critical outcome is defined as either in-hospital mortality or transfer to an intensive care unit within 12 h. ED visits were randomly partitioned into a 70%/30% split for training and validation. The extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM) algorithms were constructed using variables selected from the stepwise logistic regression model. The XGBoost model was then compared to the traditional model and clinical decision rules (CDRs) on the validation data using the area under the curve (AUC). (3) Results: There were 3622 visits among 3235 unique patients diagnosed with UTI. Of the 2535 patients in the training group, 836 (33%) experienced critical outcomes, and of the 1087 patients in the validation group, 358 (32.9%) did. The AUCs for different machine learning models were as follows: XGBoost, 0.833; RF, 0.814; and SVM, 0.799. The XGBoost model performed better than others. (4) Conclusions: Machine learning models outperformed existing traditional CDRs for predicting critical outcomes of ED patients with UTI. Future research should prospectively evaluate the effectiveness of this approach and integrate it into clinical practice.

Agreement of point of care ultrasound and final clinical diagnosis in patients with acute heart failure, acute coronary syndrome, and shock: POCUS not missing the target

Point-of-care ultrasound (POCUS) is an important tool for clinical diagnosis and decision-making in critical and non-critical scenarios. Dyspnea, chest pain, and shock are conditions susceptible to evaluation with ultrasound considering diagnostic accuracy and clinical impact already proven. There is scarce evidence in diagnosis agreement using ultrasound as an extension of physical examination. We aimed to evaluate ED patients in whom POCUS was performed, to analyze agreement between clinical initial diagnosis using ultrasound images and final diagnosis. Furthermore, we analyze failed diagnosis, inconclusive POCUS exams, and discuss details. A cross-sectional analytical study was conducted on adults who visited the emergency department with any of these three chief complaints: dyspnea, chest pain, and shock. All were evaluated with ultrasound at admission. Agreement between initial diagnosis using POCUS and final definite diagnosis was calculated. Failed diagnosis and inconclusive exams were analyzed. A total of 209 patients were analyzed. Populations: mostly males, mean age 64 years old, hypertensive. Agreement on patients with dyspnea and suspicion of acute decompensated heart failure was 0.98; agreement on chest pain suspicion of non-ST acute coronary syndrome was 0.96; agreement on type of shock was 0.90. Among the population, 12 patients had an inconclusive POCUS exam, and 16 patients had a failed diagnosis. The use of POCUS in the emergency department shows almost perfect agreement when compared with the final diagnosis in individuals experiencing acutely decompensated heart failure, acute coronary syndrome, and shock. Prospective studies are needed to evaluate the impact of this tool on mortality and prognosis when there are diagnostic errors.

Unlocking the potential of HB/RDW ratio as a simple marker for predicting mortality in acute ischemic stroke patients after thrombolysis

BACKGROUND

Systemic inflammation impairs outcomes in acute ischemic stroke (AIS). There is limited knowledge regarding the prognostic value of inflammatory biomarkers derived from complete blood count in predicting in-hospital mortality (IHM) in AIS patients treated with recombinant tissue plasminogen activator (rt-PA). Our study aims to compare the predictive performance of various inflammatory biomarkers for predicting IHM in AIS patients.

METHODS

This retrospective study included AIS patients treated with rt-PA between January 2015 and July 2022. We identified the following inflammatory biomarkers: white blood cell counts (WBCs), absolute neutrophil count, absolute lymphocyte count, neutrophil to lymphocyte count ratio, platelet to neutrophil ratio, platelet to lymphocyte ratio, red cell distribution width (RDW), RDW to platelet ratio (RPR), and hemoglobin to RDW (HB/RDW) at admission before rt-PA administration. We assessed the predictive value of these biomarkers for IHM by plotting receiver operating characteristic (ROC) curves. The associations between inflammatory biomarkers and IHM were analyzed using multivariable logistic regression (MVLR) analyses.

RESULTS

Of 345 AIS patients, IHM occurred in 65 patients (18.84%). HB/RDW and RDW showed better predictive performance compared to other inflammatory biomarkers. In ROC curve analysis, HB/RDW and RDW had an area under ROC of 0.668. HB/RDW outperformed RDW in terms of the positive likelihood ratio (2.733 vs 1.575), accuracy (0.757 vs 0.585), specificity (0.814 vs 0.560), and positive predictive values (0.388 vs 0.267). In MVLR analysis, RDW, RPR, and HB/RDW remained significantly associated with IHM (per 1-unit increases: odds ratios (ORs) = 1.450, 95% CI: [1.178-1.784]; per 1-unit increases: ORs = 1.329, 95% CI [1.103-1.602]; and per 0.1-unit decreases: ORs = 1.412, 95% CI [1.089-1.831], respectively).

CONCLUSIONS

The association between HB/RDW and IHM in AIS patients treated with rt-PA was significant. HB/RDW exhibited superior predictive performance compared to other inflammatory biomarkers in predicting IHM.

Utility of shaking chills as a diagnostic sign for bacteremia in adults: a systematic review and meta-analysis

BACKGROUND

Accurate prediction of bacteremia is essential for guiding blood culture collection and optimal antibiotic treatment. Shaking chills, defined as a subjective chill sensation with objective body shivering, have been suggested as a potential predictor of bacteremia; however, conflicting findings exist. To address the evidence gap, we conducted a systematic review and meta-analysis of studies to assess the diagnostic accuracy of shaking chills for predicting bacteremia among adult patients.

METHODS

We included studies reporting the diagnostic accuracy of shaking chills or chills for bacteremia. Adult patients with suspected bacteremia who underwent at least one set of blood cultures were included. Our main analysis focused on studies that assessed shaking chills. We searched these studies through CENTRAL, MEDLINE, Embase, the World Health Organization ICTRP Search Portal, and ClinicalTrials.gov. Study selection, data extraction, evaluation for risk of bias, and applicability using the QUADAS-2 tool were conducted by two independent investigators. We estimated a summary receiver operating characteristic curve and a summary point of sensitivity and specificity of the index tests, using a hierarchical model and the bivariate model, respectively.

RESULTS

We identified 19 studies with a total of 14,641 patients in which the accuracy of shaking chills was evaluated. The pooled sensitivity and specificity of shaking chills were 0.37 (95% confidence interval [CI], 0.29 to 0.45) and 0.87 (95% CI, 0.83 to 0.90), respectively. Most studies had a low risk of bias in the index test domain and a high risk of bias and a high applicability concern in the patient-selection domain.

CONCLUSIONS

Shaking chills are a highly specific but less sensitive predictor of bacteremia. Blood cultures and early initiation of antibiotics should be considered for patients with an episode of shaking chills; however, the absence of shaking chills must not lead to exclusion of bacteremia and early antibiotic treatment.

Gamified learning for resuscitation education: A systematic review

Aim

To systematically review published literature to evaluate the impact of gamified learning on educational and clinical outcomes during life support education.

Methods

This systematic review was conducted as part of the continuous evidence evaluation process of the International Liaison Committee on Resuscitation (ILCOR). A search of PubMed, Embase, and Cochrane was conducted from inception until February 12, 2024. Studies examining incorporation of gamified learning were eligible for inclusion. Reviewers independently extracted data on study design and outcomes; appropriate risk of bias assessment tools were used across all outcomes.

Results

2261 articles were identified and screened, yielding sixteen articles (seven randomized trials, nine observational studies) which comprised the final review. No meta-analyses were conducted due to significant heterogeneity of intervention, population, and outcome. Only one study was found to have a low risk of bias; the remaining studies were found to have moderate to high risk. Fourteen studies were in healthcare providers and two were in laypersons. Most studies (11 of 16) examined the impact of a digital platform (computer or smartphone). Most (15 of 16) studies found a positive effect on at least one educational domain; one study found no effect. No included study found a negative effect on any educational domain.

Conclusion

This systematic review found a very heterogeneous group of studies with low certainty evidence, all but one of which demonstrated a positive effect on one or more educational domains. Future studies should examine the underlying causes of improved learning with gamification and assess the resource requirements with implementation and dissemination of gamified learning.

Diagnostic accuracy of prehospital lung ultrasound for acute decompensated heart failure: A systematic review and Meta-analysis

BACKGROUND

Lung ultrasound (LUS) reduces time to diagnosis and treatment of acute decompensated heart failure (ADHF) in emergency department (ED) patients with undifferentiated dyspnea. We conducted a systematic review to evaluate the diagnostic accuracy and clinical impact of LUS for ADHF in the prehospital setting.

METHODS

We performed a keyword search of multiple databases from inception through June 1, 2023. Included studies were those enrolling prehospital patients with undifferentiated dyspnea or suspected ADHF, and specifically diagnostic studies comparing prehospital LUS to a gold standard and intervention studies with a non-US comparator group. Title and abstract screening, full text review, risk of bias (ROB) assessments, and data extraction were performed by multiple authors. and adjudicated. The primary outcome was pooled sensitivity, specificity, and diagnostic likelihood ratios (LR) for prehospital LUS. A test-treatment threshold of 0.7 was applied based on prior ADHF literature in the ED. Intervention outcomes included mortality, mechanical ventilation, and time to HF specific treatment.

RESULTS

Eight diagnostic studies (n = 691) and two intervention studies (n = 70) met inclusion criteria. No diagnostic studies were low-ROB. Both intervention studies were critical-ROB, and not pooled. Pooled sensitivity and specificity of prehospital LUS for ADHF were 86.7% (95%CI:70.8%-94.6%) and 87.5% (78.2%-93.2%), respectively, with similar performance by physician vs. paramedic LUS and number of lung zones evaluated. Pooled LR+ and LR- were 7.27 (95% CI: 3.69-13.10) and 0.17 (95% CI: 0.06-0.34), respectively. Area under the summary receiver operating characteristic curve was 0.922. At the observed 42.4% ADHF prevalence (pre-test probability), positive pre-hospital LUS exceeded the 70% threshold to initiate treatment (post-test probability 84%, 80-88%).

CONCLUSIONS

LUS had similar diagnostic test characteristics for ADHF diagnosis in the prehospital setting as in the ED. A positive prehospital LUS may be sufficient to initiate early ADHF treatment based on published test-treatment thresholds. More studies are needed to determine the clinical impact of prehospital LUS.

Antimicrobial Stewardship in the Emergency Department Observation Unit: Definition of a New Indicator and Evaluation of Antimicrobial Use and Clinical Outcomes

We aimed to define a novel indicator for monitoring antimicrobial use specifically in the Emergency Department Observation Unit (EDOU) and to assess the long-term impact of an institutional education-based antimicrobial stewardship program (ASP) on the antimicrobial prescribing pattern and clinical outcomes in this setting. A quasi-experimental interrupted time-series study was performed from 2011 to 2022. An educational ASP was implemented at the EDOU in 2015. To estimate changes in antimicrobial use, we designed an indicator adjusted for patients at risk of antimicrobial prescribing: defined daily doses (DDDs) per 100 patients transferred from the Emergency Department to the Observation Unit (TOs) per quarter. The number of bloodstream infections (BSIs) and the crude all-cause 14-day mortality were assessed as clinical outcomes. Antimicrobial use showed a sustained reduction with a trend change of -1.17 DDD per 100 TO and a relative effect of -45.6% (CI95% -64.5 to -26.7), particularly relevant for meropenem and piperacillin-tazobactam, with relative effects of -80.4% (-115.0 to -45.7) and -67.9% (-93.9 to -41.9), respectively. The incidence density of all BSIs increased significantly during the ASP period, with a relative effect of 123.2% (41.3 to 284.7). The mortality rate remained low and stable throughout the study period, with an absolute effect of -0.7% (-16.0 to 14.7). The regular monitoring of antimicrobial use in the EDOU by using this new quantitative indicator was useful to demonstrate that an institutional education-based ASP successfully achieved a long-term reduction in overall antimicrobial use, with a low and steady BSI mortality rate.

An AI-based multiphase framework for improving the mechanical ventilation availability in emergency departments during respiratory disease seasons: a case study

BACKGROUND

Shortages of mechanical ventilation have become a constant problem in Emergency Departments (EDs), thereby affecting the timely deployment of medical interventions that counteract the severe health complications experienced during respiratory disease seasons. It is then necessary to count on agile and robust methodological approaches predicting the expected demand loads to EDs while supporting the timely allocation of ventilators. In this paper, we propose an integration of Artificial Intelligence (AI) and Discrete-event Simulation (DES) to design effective interventions ensuring the high availability of ventilators for patients needing these devices.

METHODS

First, we applied Random Forest (RF) to estimate the mechanical ventilation probability of respiratory-affected patients entering the emergency wards. Second, we introduced the RF predictions into a DES model to diagnose the response of EDs in terms of mechanical ventilator availability. Lately, we pretested two different interventions suggested by decision-makers to address the scarcity of this resource. A case study in a European hospital group was used to validate the proposed methodology.

RESULTS

The number of patients in the training cohort was 734, while the test group comprised 315. The sensitivity of the AI model was 93.08% (95% confidence interval, [88.46 - 96.26%]), whilst the specificity was 85.45% [77.45 - 91.45%]. On the other hand, the positive and negative predictive values were 91.62% (86.75 - 95.13%) and 87.85% (80.12 - 93.36%). Also, the Receiver Operator Characteristic (ROC) curve plot was 95.00% (89.25 - 100%). Finally, the median waiting time for mechanical ventilation was decreased by 17.48% after implementing a new resource capacity strategy.

CONCLUSIONS

Combining AI and DES helps healthcare decision-makers to elucidate interventions shortening the waiting times for mechanical ventilators in EDs during respiratory disease epidemics and pandemics.

Quantitative Metrics in Mass-Gathering Studies: A Comprehensive Systematic Review

INTRODUCTION

Mass gatherings are events where many people come together at a specific location for a specific purpose, such as concerts, sports events, or religious gatherings, within a certain period of time. In mass-gathering studies, many rates and ratios are used to assess the demand for medical resources. Understanding such metrics is crucial for effective planning and intervention efforts. Therefore, this systematic review aims to investigate the usage of rates and ratios reported in mass-gathering studies.

METHODS

In this systematic review, the PRISMA guidelines were followed. Articles published through December 2023 were searched on Web of Science, Scopus, Cochrane, and PubMed using the specified keywords. Subsequently, articles were screened based on titles, abstracts, and full texts to determine their eligibility for inclusion in the study. Finally, the articles that were related to the study's aim were evaluated.

RESULTS

Out of 745 articles screened, 55 were deemed relevant for inclusion in the study. These included 45 original research articles, three special reports, three case presentations, two brief reports, one short paper, and one field report. A total of 15 metrics were identified, which were subsequently classified into three categories: assessment of population density, assessment of in-event health services, and assessment of out-of-event health services.

CONCLUSION

The findings of this study revealed notable inconsistencies in the reporting of rates and ratios in mass-gathering studies. To address these inconsistencies and to standardize the information reported in mass-gathering studies, a Metrics and Essential Ratios for Gathering Events (MERGE) table was proposed. Future research should promote consistency in terminology and adopt standardized methods for presenting rates and ratios. This would not only enhance comparability but would also contribute to a more nuanced understanding of the dynamics associated with mass gatherings.

Designing Chinese hospital emergency departments to leverage artificial intelligence-a systematic literature review on the challenges and opportunities

Artificial intelligence (AI) has witnessed rapid advances in the healthcare domain in recent years, especially in the emergency field, where AI is likely to radically reshape medical service delivery. Although AI has substantial potential to enhance diagnostic accuracy and operational efficiency in hospitals, research on its applications in Emergency Department building design remains relatively scarce. Therefore, this study aims to investigate Emergency Department facility design by identifying the challenges and opportunities of using AI. Two systematic literature reviews are combined, one in AI and the other in sensors, to explore their potential application to support decision-making, resource optimisation and patient monitoring. These reviews have then informed a discussion on integrating AI sensors in contemporary Emergency Department designs for use in China to support the evidence base on resuscitation units, emergency operating rooms and Emergency Department Intensive Care Unit (ED-ICU) design. We hope to inform the strategic implementation of AI sensors and how they might transform Emergency Department design to support medical staff and enhance the patient experience.

Development and validation of prognostic machine learning models for short- and long-term mortality among acutely admitted patients based on blood tests

Several scores predicting mortality at the emergency department have been developed. However, all with shortcomings either simple and applicable in a clinical setting, with poor performance, or advanced, with high performance, but clinically difficult to implement. This study aimed to explore if machine learning algorithms could predict all-cause short- and long-term mortality based on the routine blood test collected at admission.

METHODS

We analyzed data from a retrospective cohort study, including patients > 18 years admitted to the Emergency Department (ED) of Copenhagen University Hospital Hvidovre, Denmark between November 2013 and March 2017. The primary outcomes were 3-, 10-, 30-, and 365-day mortality after admission. PyCaret, an automated machine learning library, was used to evaluate the predictive performance of fifteen machine learning algorithms using the area under the receiver operating characteristic curve (AUC).

RESULTS

Data from 48,841 admissions were analyzed, of these 34,190 (70%) were randomly divided into training data, and 14,651 (30%) were in test data. Eight machine learning algorithms achieved very good to excellent results of AUC on test data in a of range 0.85-0.93. In prediction of short-term mortality, lactate dehydrogenase (LDH), leukocyte counts and differentials, Blood urea nitrogen (BUN) and mean corpuscular hemoglobin concentration (MCHC) were the best predictors, whereas prediction of long-term mortality was favored by age, LDH, soluble urokinase plasminogen activator receptor (suPAR), albumin, and blood urea nitrogen (BUN).

CONCLUSION

The findings suggest that measures of biomarkers taken from one blood sample during admission to the ED can identify patients at high risk of short-and long-term mortality following emergency admissions.

Global stroke statistics 2023: Availability of reperfusion services around the world

BACKGROUND

Disparities in the availability of reperfusion services for acute ischemic stroke are considerable globally and require urgent attention. Contemporary data on the availability of reperfusion services in different countries are used to provide the necessary evidence to prioritize where access to acute stroke treatment is needed.

AIMS

To provide a snapshot of published literature on the provision of reperfusion services globally, including when facilitated by telemedicine or mobile stroke unit services.

METHODS

We searched PubMed to identify original articles, published up to January 2023 for the most recent, representative, and relevant patient-level data for each country. Keywords included thrombolysis, endovascular thrombectomy and telemedicine. We also screened reference lists of review articles, citation history of articles, and the gray literature. The information is provided as a narrative summary.

RESULTS

Of 11,222 potentially eligible articles retrieved, 148 were included for review following de-duplications and full-text review. Data were also obtained from national stroke clinical registry reports, Registry of Stroke Care Quality (RES-Q) and PRE-hospital Stroke Treatment Organization (PRESTO) repositories, and other national sources. Overall, we found evidence of the provision of intravenous thrombolysis services in 70 countries (63% high-income countries (HICs)) and endovascular thrombectomy services in 33 countries (68% HICs), corresponding to far less than half of the countries in the world. Recent data (from 2019 or later) were lacking for 35 of 67 countries with known year of data (52%). We found published data on 74 different stroke telemedicine programs (93% in HICs) and 14 active mobile stroke unit pre-hospital ambulance services (80% in HICs) around the world.

CONCLUSION

Despite remarkable advancements in reperfusion therapies for stroke, it is evident from available patient-level data that their availability remains unevenly distributed globally. Contemporary published data on availability of reperfusion services remain scarce, even in HICs, thereby making it difficult to reliably ascertain current gaps in the provision of this vital acute stroke treatment around the world.