Wrestling injuries during the 2016 Rio and 2020 Tokyo Olympic Games.

OBJECTIVES: To evaluate and compare the injuries of Olympic wrestlers during the 2016 Rio and 2020 Tokyo Olympic Games held in August 2021 due to the COVID-19 pandemic. METHODS: In this descriptive epidemiological study, injury report forms were used to collect and analyse injury data during the competitions. RESULTS: During 410 matches in the Rio Olympic Games, 21 injuries were recorded among 346 wrestlers (112=women), a rate of 5.1 injuries/100 bouts and 6.1 injuries/100 athletes. During 322 matches in the Tokyo Olympic Games, 28 injuries were recorded among 287 wrestlers (96=women), with 8.7 injuries/100 bouts and 9.8 injuries/100 athletes. However, these apparent differences in injury rates between Tokyo and Rio were not statistically significant (injuries/bout: p=0.057, 95% CI: 0.31 to 1.02; injuries/athlete: p=0.087, 95% CI: 0.33 to 1.08). Mild injuries comprised the greatest proportion of injuries in both Olympic Games. Severe injuries accounted for 0%, 16.7% and 36.4% of injuries in Greco-Roman, Freestyle and Women's wrestling, respectively. CONCLUSION: Most wrestling injuries in the 2016 Rio and 2020 Tokyo Olympic Games were mild skin injuries in the head and face regions due to direct body contact during standing positions in the 1/8-final round of wrestling competitions. No critical injury was observed during the recent Olympic Games. Attention should be drawn to preventing upper limb joint dislocations as common severe injuries in both Olympic Games. While not statistically significant, the Tokyo Games, after the COVID-19 pandemic, witnessed a higher injury occurrence than the Rio Games.

Modification of a Conventional Deep Learning Model to Classify Simulated Breathing Patterns: A Step toward Real-Time Monitoring of Patients with Respiratory Infectious Diseases.

The emergence of the global coronavirus pandemic in 2019 (COVID-19 disease) created a need for remote methods to detect and continuously monitor patients with infectious respiratory diseases. Many different devices, including thermometers, pulse oximeters, smartwatches, and rings, were proposed to monitor the symptoms of infected individuals at home. However, these consumer-grade devices are typically not capable of automated monitoring during both day and night. This study aims to develop a method to classify and monitor breathing patterns in real-time using tissue hemodynamic responses and a deep convolutional neural network (CNN)-based classification algorithm. Tissue hemodynamic responses at the sternal manubrium were collected in 21 healthy volunteers using a wearable near-infrared spectroscopy (NIRS) device during three different breathing conditions. We developed a deep CNN-based classification algorithm to classify and monitor breathing patterns in real time. The classification method was designed by improving and modifying the pre-activation residual network (Pre-ResNet) previously developed to classify two-dimensional (2D) images. Three different one-dimensional CNN (1D-CNN) classification models based on Pre-ResNet were developed. By using these models, we were able to obtain an average classification accuracy of 88.79% (without Stage 1 (data size reducing convolutional layer)), 90.58% (with 1 × 3 Stage 1), and 91.77% (with 1 × 5 Stage 1).

Optical Monitoring of Breathing Patterns and Tissue Oxygenation: A Potential Application in COVID-19 Screening and Monitoring.

The worldwide outbreak of the novel Coronavirus (COVID-19) has highlighted the need for a screening and monitoring system for infectious respiratory diseases in the acute and chronic phase. The purpose of this study was to examine the feasibility of using a wearable near-infrared spectroscopy (NIRS) sensor to collect respiratory signals and distinguish between normal and simulated pathological breathing. Twenty-one healthy adults participated in an experiment that examined five separate breathing conditions. Respiratory signals were collected with a continuous-wave NIRS sensor (PortaLite, Artinis Medical Systems) affixed over the sternal manubrium. Following a three-minute baseline, participants began five minutes of imposed difficult breathing using a respiratory trainer. After a five minute recovery period, participants began five minutes of imposed rapid and shallow breathing. The study concluded with five additional minutes of regular breathing. NIRS signals were analyzed using a machine learning model to distinguish between normal and simulated pathological breathing. Three features: breathing interval, breathing depth, and O2Hb signal amplitude were extracted from the NIRS data and, when used together, resulted in a weighted average accuracy of 0.87. This study demonstrated that a wearable NIRS sensor can monitor respiratory patterns continuously and non-invasively and we identified three respiratory features that can distinguish between normal and simulated pathological breathing.

Moderate and Severe Injuries at Five International Olympic-Style Wrestling Tournaments during 2016-2019.

As a contact sport, wrestling may result in injuries. Based on the severity, they are classified as mild, moderate, severe and critical. All injuries occurring at international competitions are documented in a cloud-based surveillance system. The purpose of this study was to analyze the incidence and characteristics of moderate and severe (including critical) wrestling injuries that occurred during five international Olympic-style wrestling competitions in 2016-2019. Three Wrestling World Championships and two European Wrestling tournaments were organized by the Hungarian Wrestling Federation in 2016-2019. A total of 2483 wrestlers in three Olympic wrestling styles have competed in 3007 matches. Data from all injuries were recorded and analyzed to define rates, locations, types and severity, and to compare with previous reports. A total of 53 wrestlers sustained 55 injuries, which is equivalent to an overall injury incidence rate of 9.1‰ (9.1/1000 athletic exposures). Greco-Roman and Women Wrestling had the same injury incidence rate, while Freestyle had a lower one (9.5‰ versus 8.5‰). The injury proportion by regions and anatomic locations were on head and face 29.1%, spine and trunk 16.4 % and the upper-and-lower extremity injuries equally 27.3%. The most common types of injuries included ligament lesions, joint injuries, skin lacerations, and contusions. Five wrestlers (0.8‰) sustained strangulation or concussion. Wrestling injury rates during United World Wrestling competitions are not high, but when happen they can be serious. Despite relatively low incidence rate of injuries, there is a need for continuous education for medical teams, referees and coaches to avoid wrestling injuries.

Outcomes of free flap reconstructions with near-infrared spectroscopy (NIRS) monitoring: A systematic review.

BACKGROUND: Free flap failure or vascular compromise remains a dreadful complication of microvascular free tissue transfer. Near-infrared spectroscopy (NIRS) is a novel technique for free flap monitoring that has the propensity for early detection of vascular compromise when compared to the current gold standard, clinical monitoring (CM). The objective of this review is to evaluate the efficacy of a NIRS system in the postoperative monitoring of free flaps and its effect on flap salvage. METHODS: A comprehensive literature review was performed including English-language articles evaluating the use of NIRS in free flap monitoring. MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), OVID, and Web of Science were searched upto December 2017. RESULTS: A total of 590 articles were identified, and 10 articles were included for analysis. Overall, flaps with vascular compromise monitored with NIRS had a significantly higher salvage rate of 89% compared with a salvage rate of 50% in the flaps monitored by CM alone (p < .01). Partial loss occurred in 15% of the successful salvages in the NIRS group versus 80% with CM alone (p < .01). Detection of vascular compromise by NIRS preceded clinical signs on average by 82 ± 49 min. NIRS was accurate in detecting compromised flaps with a low false-positive and false-negative rate. CONCLUSION: Despite lack of robust data, NIRS has the potential to be an objective, accurate, and continuous postoperative free flap monitoring technique with a greater flap salvage rate than CM alone.

Monitoring spinal cord hemodynamics and tissue oxygenation: a review of the literature with special focus on the near-infrared spectroscopy technique.

STUDY DESIGN: Review. OBJECTIVES: Clinical studies have shown that the hemodynamic management of patients following acute spinal cord injury (SCI) is an important aspect of their treatment for maintaining spinal cord (SC) perfusion and minimizing ischemic secondary injury to the SC. While this highlights the importance of ensuring adequate perfusion and oxygenation to the injured cord, a method for the real-time monitoring of these hemodynamic measures within the SC is lacking. The purpose of this review is to discuss current and potential methods for SC hemodynamic monitoring with special focus on applications using near-infrared spectroscopy (NIRS). METHODS: A literature search using the PubMed database. All peer-reviewed articles on NIRS monitoring of SC published from inception to May 2019 were reviewed. RESULTS: Among 125 papers related to SC hemodynamics monitoring, 26 focused on direct/indirect NIRS monitoring of the SC. DISCUSSION: Current options for continuous, non-invasive, and real-time monitoring of SC hemodynamics are challenging and limited in scope. As a relatively new technique, NIRS has been successfully used for monitoring human cerebral hemodynamics, and has shown promising results in intraoperative assessment of SC hemodynamics in both human and animal models. Although utilizing NIRS to monitor the SC has been validated, applying NIRS clinically following SCI requires further development and investigation. CONCLUSIONS: NIRS is a promising non-invasive technique with the potential to provide real-time monitoring of relevant parameters in the SC. Currently, in its first developmental stages, further clinical and experimental studies are mandatory to ensure the validity and safety of NIRS techniques.

Effect of acute hypoxia on inspiratory muscle oxygenation during incremental inspiratory loading in healthy adults.

PURPOSE: To non-invasively examine the effect of acute hypoxia and inspiratory threshold loading (ITL) on inspiratory muscles [sternocleidomastoid (SCM), scalene (SA) and parasternal (PS)] oxygenation in healthy adults using near-infrared spectroscopy (NIRS). METHODS: Twenty healthy adults (12 M/8 F) were randomly assigned to perform two ITL tests while breathing a normoxic or hypoxic (FIO2 = 15 %) gas mixture. NIRS devices were placed over the SCM, PS, SA, and a control muscle, tibialis anterior (TA), to monitor oxygenated (O2Hb), deoxygenated (HHb), total hemoglobin (tHb) and tissue saturation index (TSI). With the nose occluded, subjects breathed normally for 4 min through a mouthpiece that was connected to a weighted threshold loading device. ITL began by adding a 100-g weight to the ITL device. Then, every 2 min 50-g was added until task failure. Vital signs, ECG and ventilatory measures were monitored throughout the protocol. RESULT: Participants were 31 ± 12 year and had normal spirometry. At task failure, the maximum load and ventilatory parameters did not differ between the hypoxic and normoxic ITL. At hypoxic ITL task failure, SpO2 was significantly lower, and ∆HHb increased more so in SA, SCM and PS than normoxic values. SCM ∆TSI decreased more so during hypoxic compared to normoxic ITL. ∆tHb in the inspiratory muscles (SCM, PS and SA) increased significantly compared to the decrease in TA during both hypoxic and normoxic ITL. CONCLUSION: The SCM, an accessory inspiratory muscle was the most vulnerable to deoxygenation during incremental loading and this response was accentuated by acute hypoxia.

Zika and Rio Olympic Games.

Zika virus (ZIKV) is an arthropod-borne virus that is mainly transmitted via a bite from a female mosquito of the Aedes species. However, ZIKV can be transmitted sexually or via blood. Due to the recent ZIKV outbreak in South and Central America, many national and international organizations are concerned about the safety of athletes, coaches, staff, and spectators during the Olympic and Paralympic Games. Infected individuals are generally asymptomatic or have mild symptoms. However, ZIKV infection can potentially cause serious complications such as Guillain-Barre syndrome and congenital defects. Preferred diagnosis is based on real-time reverse-transcription polymerase chain reaction from blood and urine. Currently, there is no treatment or immunization available for ZIKV infection, and disease control is limited to preventing mosquito bites.

Rapid Weight Loss in Sports with Weight Classes.

Weight-sensitive sports are popular among elite and nonelite athletes. Rapid weight loss (RWL) practice has been an essential part of many of these sports for many decades. Due to the limited epidemiological studies on the prevalence of RWL, its true prevalence is unknown. It is estimated that more than half of athletes in weight-class sports have practiced RWL during the competitive periods. As RWL can have significant physical, physiological, and psychological negative effects on athletes, its practice has been discouraged for many years. It seems that appropriate rule changes have had the biggest impact on the practice of RWL in sports like wrestling. An individualized and well-planned gradual and safe weight loss program under the supervision of a team of coaching staff, athletic trainers, sports nutritionists, and sports physicians is recommended.

Risk factors for acute compartment syndrome of the leg associated with tibial diaphyseal fractures in adults.

BACKGROUND: We sought to examine the occurrence of acute compartment syndrome (ACS) in the cohort of patients with tibial diaphyseal fractures and to detect associated risk factors that could predict this occurrence. MATERIALS AND METHODS: A total of 1,125 patients with tibial diaphyseal fractures that were treated in our centre were included into this retrospective cohort study. All patients were treated with surgical fixation. Among them some were complicated by ACS of the leg. Age, gender, year and mechanism of injury, injury severity score (ISS), fracture characteristics and classifications and the type of fixation, as well as ACS characteristics in affected patients were studied. RESULTS: Of the cohort of patients 772 (69 %) were male (mean age 39.60 ± 15.97 years) and the rest were women (mean age 45.08 ± 19.04 years). ACS of the leg occurred in 87 (7.73 %) of all tibial diaphyseal fractures. The mean age of those patients that developed ACS (33.08 ± 12.8) was significantly lower than those who did not develop it (42.01 ± 17.3, P < 0.001). No significant difference in incidence of ACS was found in open versus closed fractures, between anatomic sites and following IM nailing (P = 0.67). Increasing pain was the most common symptom in 71 % of cases with ACS. CONCLUSIONS: We found that younger patients are definitely at a significantly higher risk of ACS following acute tibial diaphyseal fractures. Male gender, open fracture and IM nailing were not risk factors for ACS of the leg associated with tibial diaphyseal fractures in adults. LEVEL OF EVIDENCE: Level IV.

Methods of muscle spasticity assessment in children with cerebral palsy: a scoping review.

BACKGROUND: Evaluating muscle spasticity in children with cerebral palsy (CP) is essential for determining the most effective treatment strategies. This scoping review assesses the current methods used to evaluate muscle spasticity, highlighting both traditional and innovative technologies, and their respective advantages and limitations. METHODS: A search (to April 2024) used keywords such as muscle spasticity, cerebral palsy, and assessment methods. Selection criteria included articles involving CP children, assessing spasticity objectively/subjectively, comparing methods, or evaluating method effectiveness. RESULTS: From an initial pool of 1971 articles, 30 met our inclusion criteria. These studies collectively appraised a variety of techniques ranging from well-established clinical scales like the modified Ashworth Scale and Tardieu Scale, to cutting-edge technologies such as real-time sonoelastography and inertial sensors. Notably, innovative methods such as the dynamic evaluation of range of motion scale and the stiffness tool were highlighted for their potential to provide more nuanced and precise assessments of spasticity. The review unveiled a critical insight: while traditional methods are convenient and widely used, they often fall short in reliability and objectivity. CONCLUSION: The review discussed the strengths and limitations of each method and concluded that more reliable methods are needed to measure the level of muscle spasticity more accurately.

Two-Stream Convolutional Neural Networks for Breathing Pattern Classification: Real-Time Monitoring of Respiratory Disease Patients.

A two-stream convolutional neural network (TCNN) for breathing pattern classification has been devised for the continuous monitoring of patients with infectious respiratory diseases. The TCNN consists of a convolutional neural network (CNN)-based autoencoder and classifier. The encoder of the autoencoder generates deep compressed feature maps, which contain the most important information constituting data. These maps are concatenated with feature maps generated by the classifier to classify breathing patterns. The TCNN, single-stream CNN (SCNN), and state-of-the-art classification models were applied to classify four breathing patterns: normal, slow, rapid, and breath holding. The input data consisted of chest tissue hemodynamic responses measured using a wearable near-infrared spectroscopy device on 14 healthy adult participants. Among the classification models evaluated, random forest had the lowest classification accuracy at 88.49%, while the TCNN achieved the highest classification accuracy at 94.63%. In addition, the proposed TCNN performed 2.6% better in terms of classification accuracy than an SCNN (without an autoencoder). Moreover, the TCNN mitigates the issue of declining learning performance with increasing network depth, as observed in the SCNN model. These results prove the robustness of the TCNN in classifying breathing patterns despite using a significantly smaller number of parameters and computations compared to state-of-the-art classification models.

Enhancing upper extremity muscle strength in individuals with spinal cord injury using low-intensity blood flow restriction exercise.

OBJECTIVES: This study explores the feasibility and effects of low-intensity blood flow restriction exercise on forearm muscle strength and function in individuals with spinal cord injury. STUDY DESIGN: Pilot randomized clinical trial. PATIENTS AND METHODS: Ten male and female adult participants with chronic cervical and thoracic spinal cord injury underwent an 8-week low-intensity blood flow restriction exercise programme that targeted forearm muscles. Each participant's contralateral forearm served as the control. Grip strength was the primary outcome measure, and participants also provided qualitative feedback on their experiences. RESULTS: The study revealed a significant increase in participants' forearm muscle strength on the experimental side engaged in low-intensity blood flow restriction training, with an average strength gain of 7.5 ± 0.36 kg after 16 exercise sessions (Cohen's d = -6.32, 95% CI -8.34, -6.68). In comparison, the control side, following a conventional high- intensity exercise regimen without BFR, showed a more modest strength increase of 4.4 ± 0.67 kg. A mean Patient's Global Impression of Change score of 2.2 reflected overall improvements in participants' daily activities and health status. CONCLUSION: This study highlights the feasibility and effectiveness of low-intensity blood flow restriction exercise as a safe and promising approach to enhancing forearm muscle strength in individuals with spinal cord injury. The observed positive outcomes, coupled with a high level of participant satisfaction, underscore the potential of this innovative method to significantly improve limb muscle strength, thereby contributing to greater functional independence in this population.

Detecting cardiac states with wearable photoplethysmograms and implications for out-of-hospital cardiac arrest detection.

Out-of-hospital cardiac arrest (OHCA) is a global health problem affecting approximately 4.4 million individuals yearly. OHCA has a poor survival rate, specifically when unwitnessed (accounting for up to 75% of cases). Rapid recognition can significantly improve OHCA survival, and consumer wearables with continuous cardiopulmonary monitoring capabilities hold potential to "witness" cardiac arrest and activate emergency services. In this study, we used an arterial occlusion model to simulate cardiac arrest and investigated the ability of infrared photoplethysmogram (PPG) sensors, often utilized in consumer wearable devices, to differentiate normal cardiac pulsation, pulseless cardiac (i.e., resembling a cardiac arrest), and non-physiologic (i.e., off-body) states. Across the classification models trained and evaluated on three anatomical locations, higher classification performances were observed on the finger (macro average F1-score of 0.964 on the fingertip and 0.954 on the finger base) compared to the wrist (macro average F1-score of 0.837). The wrist-based classification model, which was trained and evaluated using all PPG measurements, including both high- and low-quality recordings, achieved a macro average precision and recall of 0.922 and 0.800, respectively. This wrist-based model, which represents the most common form factor in consumer wearables, could only capture about 43.8% of pulseless events. However, models trained and tested exclusively on high-quality recordings achieved higher classification outcomes (macro average F1-score of 0.975 on the fingertip, 0.973 on the finger base, and 0.934 on the wrist). The fingertip model had the highest performance to differentiate arterial occlusion pulselessness from normal cardiac pulsation and off-body measurements with macro average precision and recall of 0.978 and 0.972, respectively. This model was able to identify 93.7% of pulseless states (i.e., resembling a cardiac arrest event), with a 0.4% false positive rate. All classification models relied on a combination of time-, power spectral density (PSD)-, and frequency-domain features to differentiate normal cardiac pulsation, pulseless cardiac, and off-body PPG recordings. However, our best model represented an idealized detection condition, relying on ensuring high-quality PPG data for training and evaluation of machine learning algorithms. While 90.7% of our PPG recordings from the fingertip were considered of high quality, only 53.2% of the measurements from the wrist passed the quality criteria. Our findings have implications for adapting consumer wearables to provide OHCA detection, involving advancements in hardware and software to ensure high-quality measurements in real-world settings, as well as development of wearables with form factors that enable high-quality PPG data acquisition more consistently. Given these improvements, we demonstrate that OHCA detection can feasibly be made available to anyone using PPG-based consumer wearables.

Wearable devices for out-of-hospital cardiac arrest: A population survey on the willingness to adhere.

Objectives: When an out-of-hospital cardiac arrest (OHCA) occurs, the first step in the chain of survival is detection. However, 75% of OHCAs are unwitnessed, representing the largest barrier to activating the chain of survival. Wearable devices have the potential to be "artificial bystanders," detecting OHCA and alerting 9-1-1. We sought to understand factors impacting users' willingness for continuous use of a wearable device through an online survey to inform future use of these systems for automated OHCA detection. Methods: Data were collected from October 2022 to June 2023 through voluntary response sampling. The survey investigated user convenience and perception of urgency to understand design preferences and willingness to adhere to continuous wearable use across different hypothetical risk levels. Associations between categorical variables and willingness were evaluated through nonparametric tests. Logistic models were fit to evaluate the association between continuous variables and willingness at different hypothetical risk levels. Results: The survey was completed by 359 participants. Participants preferred hand-based devices (wristbands: 87%, watches: 86%, rings: 62%) and prioritized comfort (94%), cost (83%), and size (72%). Participants were more willing to adhere at higher levels of hypothetical risk. At the baseline risk of 0.1%, older individuals with prior wearable use were most willing to adhere to continuous wearable use. Conclusion: Individuals were willing to continuously wear wearable devices for OHCA detection, especially at increased hypothetical risk of OHCA. Optimizing willingness is not just a matter of adjusting for user preferences, but also increasing perception of urgency through awareness and education about OHCA.

Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review.

Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2-11%. For the roughly 75% of OHCAs that are unwitnessed, survival is approximately 2-4.4%, as there are no bystanders present to provide life-saving interventions and alert Emergency Medical Services. Sensor technologies may reduce the number of unwitnessed OHCAs through automated detection of OHCA-associated physiological changes. However, no technologies are widely available for OHCA detection. This review identifies research and commercial technologies developed for cardiopulmonary monitoring that may be best suited for use in the context of OHCA, and provides recommendations for technology development, testing, and implementation. We conducted a systematic review of published studies along with a search of grey literature to identify technologies that were able to provide cardiopulmonary monitoring, and could be used to detect OHCA. We searched MEDLINE, EMBASE, Web of Science, and Engineering Village using MeSH keywords. Following inclusion, we summarized trends and findings from included studies. Our searches retrieved 6945 unique publications between January, 1950 and May, 2023. 90 studies met the inclusion criteria. In addition, our grey literature search identified 26 commercial technologies. Among included technologies, 52% utilized electrocardiography (ECG) and 40% utilized photoplethysmography (PPG) sensors. Most wearable devices were multi-modal (59%), utilizing more than one sensor simultaneously. Most included devices were wearable technologies (84%), with chest patches (22%), wrist-worn devices (18%), and garments (14%) being the most prevalent. ECG and PPG sensors are heavily utilized in devices for cardiopulmonary monitoring that could be adapted to OHCA detection. Developers seeking to rapidly develop methods for OHCA detection should focus on using ECG- and/or PPG-based multimodal systems as these are most prevalent in existing devices. However, novel sensor technology development could overcome limitations in existing sensors and could serve as potential additions to or replacements for ECG- and PPG-based devices.

100 top-cited scientific papers in limb prosthetics.

Research has tremendously contributed to the developments in both practical and fundamental aspects of limb prosthetics. These advancements are reflected in scientific articles, particularly in the most cited papers. This article aimed to identify the 100 top-cited articles in the field of limb prosthetics and to investigate their main characteristics. Articles related to the field of limb prosthetics and published in the Web of Knowledge database of the Institute for Scientific Information (ISI) from the period of 1980 to 2012. The 100 most cited articles in limb prosthetics were selected based on the citation index report. All types of articles except for proceedings and letters were included in the study. The study design and level of evidence were determined using Sackett's initial rules of evidence. The level of evidence was categorized either as a systematic review or meta-analysis, randomized controlled trial, cohort study, case-control study, case series, expert opinion, or design and development. The top cited articles in prosthetics were published from 1980 to 2012 with a citation range of 11 to 90 times since publication. The mean citation rate was 24.43 (SD 16.7) times. Eighty-four percent of the articles were original publications and were most commonly prospective (76%) and case series studies (67%) that used human subjects (96%) providing level 4 evidence. Among the various fields, rehabilitation (47%), orthopedics (29%), and sport sciences (28%) were the most common fields of study. The study established that studies conducted in North America and were written in English had the highest citations. Top cited articles primarily dealt with lower limb prosthetics, specifically, on transtibial and transradial prosthetic limbs. Majority of the articles were experimental studies.

The effect of recognition on survival after out-of-hospital cardiac arrest and implications for biosensor technologies.

BACKGROUND: Biosensor technologies have been proposed as a solution to provide recognition and facilitate earlier responses to unwitnessed out-of-hospital cardiac arrest (OHCA) cases. We sought to estimate the effect of recognition on survival and modelled the potential incremental impact of increased recognition of unwitnessed cases on survival to hospital discharge, to demonstrate the potential benefit of biosensor technologies. METHODS: We included cases from the British Columbia Cardiac Arrest Registry (2019-2020), which includes Emergency Medical Services (EMS)-assessed OHCAs. We excluded cases that would not have benefitted from early recognition (EMS-witnessed, terminal illness, or do-not-resuscitate). Using a mediation analysis, we estimated the relative benefits on survival of a witness recognizing vs. intervening in an OHCA; and estimated the expected additional number of survivors resulting from increasing recognition alone using a bootstrap logistic regression framework. RESULTS: Of 13,655 EMS-assessed cases, 11,412 were included (6314 EMS-treated, 5098 EMS-untreated). Survival to hospital discharge was 191/8879 (2.2%) in unwitnessed cases and 429/2533 (17%) in bystander-witnessed cases. Of the total effect attributable to a bystander witness, recognition accounted for 84% (95% CI: 72, 86) of the benefit. If all previously unwitnessed cases had been bystander witnessed, we would expect 1198 additional survivors. If these cases had been recognized, but no interventions performed, we would expect 912 additional survivors. CONCLUSION: Unwitnessed OHCA account for the majority of OHCAs, yet survival is dismal. Methods to improve recognition, such as with biosensor technologies, may lead to substantial improvements in overall survival.

Evaluation of transcutaneous near-infrared spectroscopy for early detection of cardiac arrest in an animal model.

Sudden cardiac arrest (SCA) is a leading cause of mortality worldwide. The SCA-to-resuscitation interval is a key determinant of patient outcomes, highlighting the clinical need for reliable and timely detection of SCA. Near-infrared spectroscopy (NIRS), a non-invasive optical technique, may have utility for this application. We investigated transcutaneous NIRS as a method to detect pentobarbital-induced changes during cardiac arrest in eight Yucatan miniature pigs. NIRS measurements during cardiac arrest were compared to invasively acquired carotid blood pressure and partial oxygen pressure (PO2) of spinal cord tissues. We observed statistically significant decreases in mean arterial pressure (MAP) 64.68 mmHg ± 13.08, p < 0.0001), spinal cord PO2 (38.16 mmHg ± 20.04, p = 0.0028), and NIRS-derived tissue oxygen saturation (TSI%) (14.50% ± 3.80, p < 0.0001) from baseline to 5 min after pentobarbital administration. Euthanasia-to-first change in hemodynamics for MAP and TSI (%) were similar [MAP (10.43 ± 4.73 s) vs TSI (%) (12.04 ± 1.85 s), p = 0.3714]. No significant difference was detected between NIRS and blood pressure-derived pulse rates during baseline periods (p > 0.99) and following pentobarbital administration (p = 0.97). Transcutaneous NIRS demonstrated the potential to identify rapid hemodynamic changes due to cardiac arrest in periods similar to invasive indices. We conclude that transcutaneous NIRS monitoring may present a novel, non-invasive approach for SCA detection, which warrants further investigation.