Arrest Events Research Articles

Artificial Intelligence in Ventricular Arrhythmias and Sudden Death.

Sudden cardiac arrest due to lethal ventricular arrhythmias is a major cause of mortality worldwide and results in more years of potential life lost than any individual cancer. Most of these sudden cardiac arrest events occur unexpectedly in individuals who have not been identified as high-risk due to the inadequacy of current risk stratification tools. Artificial intelligence tools are increasingly being used to solve complex problems and are poised to help with this major unmet need in the field of clinical electrophysiology. By leveraging large and detailed datasets, artificial intelligence-based prediction models have the potential to enhance the risk stratification of lethal ventricular arrhythmias. This review presents a synthesis of the published literature and a discussion of future directions in this field.

Determine the Vital Sign Observations that can Detect Signs of Cardiopulmonary Arrest in Patients Receiving Internal Medicine Care

Background: In certain hospitals, the Medical Emergency Team (MET) has undergone development to provide prompt and efficient treatment, effectively preventing cardiac arrests. Our objective was to assess the efficiency of observational practices in identifying anomalies in vital signs before cardiac arrest and to evaluate the requirement for implementing a MET system in hospitals across Punjab. Methods: We conducted a comprehensive review of patient charts from four hospitals, specifically focusing on individuals who experienced cardiac arrest over a span of 12 months. We meticulously documented and analyzed the vital signs, symptoms, and interventions that occurred within the 12 hours leading up to the cardiac arrest, comparing them against the trigger criteria established by the Medical Emergency Team (MET). Results: Throughout the designated study period, a total of 130 patients experienced cardiac arrest while in hospitals, with 68 cases (52%) occurring on the wards. Among these patients, 34 individuals (41%) displayed abnormal vital signs that met the criteria established by the Medical Emergency Team (MET). These abnormalities were documented, on average, 3.7 hours prior to the cardiac arrest event. Notably, during this timeframe, 14 patients did not receive any form of intervention, such as supplemental oxygen or medication. Among the remaining patients, nine received intervention within 2 hours, while nine others received intervention after more than 1 hour. It is important to mention that none of the patients responded to the initial intervention. However, only one patient required subsequent re-interventions. Practical Implication: It is essential for healthcare providers in this field to be knowledgeable, skilled, and prepared to respond promptly and effectively to cardiopulmonary arrest emergencies. By staying updated on the latest guidelines and practicing interdisciplinary collaboration, healthcare teams can strive towards optimizing outcomes and ensuring the safety of their patients. Conclusion: There is a prevalent occurrence of notable physiological decline in the hours leading up to cardiac arrests within the wards of Punjab hospitals, indicating the potential value in implementing a Medical Emergency Team (MET) system. However, in order to fully capitalize on the benefits of a MET, it is crucial to enhance the practice of vital sign observation by the nursing staff. Keywords: Medical Emergency Team (MET), cardiac arrests, Internal Medicine.

Who is the real team leader? Comparing leadership performance of the team leader and CPR Coach during simulated cardiac arrest

PurposeTo describe the leadership performance of team leaders and CPR Coaches, and to determine if there is a correlation between leadership scores and CPR performance during management of simulated pediatric cardiac arrest events. MethodsThis is a secondary analysis of data from a prior randomized controlled trial. We observed the performance of both team leaders and CPR coaches during the management of an 18-minute simulated cardiac arrest scenario which was run for 20 resuscitation teams comprised of CPR-certified professionals from four pediatric tertiary care centers. CPR Coaches were responsible for providing real-time verbal feedback of CPR performance to compressors. Two raters were trained to use the Behavioral Assessment Tool (BAT) to assess leadership performance of the team leader and CPR Coach. BAT scores of team leaders and CPR coaches were compared and linked with objective CPR performance. ResultsThere was no significant difference between the BAT scores of team leaders and CPR coaches (median score 27/40 vs 28.8/40, p = 0.16). Higher BAT scores of team leaders were significantly associated with higher percentage of excellent CPR (r = 0.52, p = 0.02), while higher BAT scores of CPR coaches were significantly associated with higher chest compression fraction (r = 0.48, p = 0.03). ConclusionsBoth team leaders and CPR coaches have similarly high leadership performance during the management of simulated cardiac arrest. Leadership behaviors were associated with quality of CPR performance.Clinical Trial Registration: Registration ID: NCT02539238; https://www.clinicaltrials.gov.

Pulmonary Fat Embolism Following Liposuction and Fat Grafting: A Review of Published Cases.

One of the most severe complications of liposuction and fat grafting is pulmonary fat embolism (PFE). However, most healthcare workers are not familiar with PFE. We performed a systematic review to describe the details of PFE. PubMed, EMBASE, and Google Scholar were searched up to October 2022. Further analysis focused on clinical, diagnostic, and outcome parameters. A total of 40 patients from 19 countries were included. Chest computed tomography (CT) yielded 100% accuracy in the diagnosis of PFE. More than 90% of the deceased died within 5 days after surgery, and in 69% of patients, onset of symptoms occurred within 24 h after surgery. The proportions of patients who required mechanical ventilation, had a cardiac arrest event, or died among all patients and among those whose onset of symptoms occurred within 24 h after surgery were 76%, 38%, and 34% versus 86%, 56%, and 54%, respectively. The earlier the onset of symptoms was, the more severe the clinical course was. Once a patient presents with PFE-related symptoms, surgery should be halted, supportive care initiated, and chest CT used to diagnose PFE. According to our review results, if a patient with PFE survives the initial episode without permanent sequelae, a complete recovery can be anticipated.

Inappropriate Shock Delivery Is Common During Pediatric In-Hospital Cardiac Arrest.

To characterize inappropriate shock delivery during pediatric in-hospital cardiac arrest (IHCA). Retrospective cohort study. An international pediatric cardiac arrest quality improvement collaborative Pediatric Resuscitation Quality [pediRES-Q]. All IHCA events from 2015 to 2020 from the pediRES-Q Collaborative for which shock and electrocardiogram waveform data were available. None. We analyzed 418 shocks delivered during 159 cardiac arrest events, with 381 shocks during 158 events at 28 sites remaining after excluding undecipherable rhythms. We classified shocks as: 1) appropriate (ventricular fibrillation [VF] or wide complex ≥ 150/min); 2) indeterminate (narrow complex ≥ 150/min or wide complex 100-149/min); or 3) inappropriate (asystole, sinus, narrow complex < 150/min, or wide complex < 100/min) based on the rhythm immediately preceding shock delivery. Of delivered shocks, 57% were delivered appropriately for VF or wide complex rhythms with a rate greater than or equal to 150/min. Thirteen percent were classified as indeterminate. Thirty percent were delivered inappropriately for asystole (6.8%), sinus (3.1%), narrow complex less than 150/min (11%), or wide complex less than 100/min (8.9%) rhythms. Eighty-eight percent of all shocks were delivered in ICUs or emergency departments, and 30% of those were delivered inappropriately. The rate of inappropriate shock delivery for pediatric IHCA in this international cohort is at least 30%, with 23% delivered to an organized electrical rhythm, identifying opportunity for improvement in rhythm identification training.

Differences in Cerebral Oxygenation in Cardiogenic and Respiratory Cardiac Arrest Before, During, and After Cardiopulmonary Resuscitation.

We compared the changes in cerebral oxygen saturation (ScO2) levels during cardiac arrest (CA) events using porcine models of ventricular fibrillation CA (VF-CA) and asphyxial CA (A-CA). Twenty female pigs were randomly divided into VF-CA and A-CA groups. We initiated cardiopulmonary resuscitation (CPR) 4 min after CA and measured the cerebral tissue oxygenation index (TOI) using near-infrared spectroscopy (NIRS) before, during, and after CPR. In both groups, the TOI was the lowest at 3-4 min after pre-CPR phase initiation (VF-CA group: 3.4 min [2.8-3.9]; A-CA group: 3.2 min [2.9-4.6]; p = 0.386). The increase in TOI differed between the groups in the CPR phase (p < 0.001); it increased more rapidly in the VF-CA group (16.6 [5.5-32.6] vs. 1.1 [0.6-3.3] %/min; p < 0.001). Seven pigs surviving for 60 min after the return of spontaneous circulation in the VF-CA group recovered limb movement, whereas only one in the A-CA group (p = 0.023) achieved movement recovery. The increase in the TOI did not differ significantly between the groups in the post-CPR phase (p = 0.341). Therefore, it is better to monitor ScO2 concomitantly with CPR initiation using NIRS to assess the responsiveness to CPR in clinical settings.

Predicting Cardiac Arrest in Children with Heart Disease: A Novel Machine Learning Algorithm

Children with congenital and acquired heart disease are at a higher risk of cardiac arrest compared to those without heart disease. Although the monitoring of cardiopulmonary resuscitation quality and extracorporeal resuscitation technologies have advanced, survival after cardiac arrest in this population has not improved. Cardiac arrest prevention, using predictive algorithms with machine learning, has the potential to reduce cardiac arrest rates. However, few studies have evaluated the use of these algorithms in predicting cardiac arrest in children with heart disease. We collected demographic, laboratory, and vital sign information from the electronic health records (EHR) of all the patients that were admitted to a single-center pediatric cardiac intensive care unit (CICU), between 2010 and 2019, who had a cardiac arrest during their CICU admission, as well as a comparator group of randomly selected non-cardiac-arrest controls. We compared traditional logistic regression modeling against a novel adaptation of a machine learning algorithm (functional gradient boosting), using time series data to predict the risk of cardiac arrest. A total of 160 unique cardiac arrest events were matched to non-cardiac-arrest time periods. Using 11 different variables (vital signs and laboratory values) from the EHR, our algorithm's peak performance for the prediction of cardiac arrest was at one hour prior to the cardiac arrest (AUROC of 0.85 [0.79,0.90]), a performance that was similar to our previously published multivariable logistic regression model. Our novel machine learning predictive algorithm, which was developed using retrospective data that were collected from the EHR and predicted cardiac arrest in the children that were admitted to a single-center pediatric cardiac intensive care unit, demonstrated a performance that was similar to that of a traditional logistic regression model. While these results are encouraging, future research, including prospective validations with multicenter data, is warranted prior to the implementation of this algorithm as a real-time clinical decision support tool.

Predictive value of a tiered escalation response system: A case control study

ObjectiveRapid response systems designed to detect and respond to clinical deterioration often incorporate a multitiered, escalation response. We sought to determine the ‘predictive strength’ of commonly used triggers, and tiers of escalation, for predicting a rapid response team (RRT) call, unanticipated intensive care unit admission, or cardiac arrest (events). DesignThis was a nested, matched case–control study. SettingThe study setting involved a tertiary referral hospital. ParticipantsCases experienced an event, and controls were matched patients without an event. Outcome measuresSensitivity and specificity and area under the receiver operating characteristic curve (AUC) were measured. Logistic regression determined the set of triggers with the highest AUC. ResultsThere were 321 cases and 321 controls. Nurse triggers occurred in 62%, medical review triggers in 34%, and RRT triggers 20%. Positive predictive value of nurse triggers was 59%, that of medical review triggers was 75%, and that of RRT triggers was 88%. These values were no different when modifications to triggers were considered. The AUC was 0.61 for nurses, 0.67 for medical review, and 0.65 for RRT triggers. With modelling, the AUC was 0.63 for the lowest tier, 0.71 for next highest, and 0.73 for the highest tier. ConclusionFor a three-tiered system, at the lowest tier, specificity of triggers decreases, sensitivity increases, but the discriminatory power is poor. Thus, there is little to be gained by using a rapid response system with more than two tiers. Modifications to triggers reduced the potential number of escalations and did not affect tier discriminatory value.

Analysis and improvement of local cleavage fracture models at elevated loading rates

Brittle fracture has to be excluded in safety-relevant components such as nuclear reactor pressure vessels. Recent work has indicated that brittle failure under dynamic loading cannot be assessed reliably by macroscopic methods such as the Master Curve concept (ASTM E1921). This finding is strongly connected to adiabatic heating processes and local crack arrest events in the crack tip region. However, a detailed study involving the assessment at elevated loading rates with local cleavage fracture models is not available to this point. The present work deals with the application of a local model to various dynamic loading conditions, as well as a proposed model adjustment to improve the analysis results. It was found that existing local concepts are not capable of describing fracture behavior adequately. Though the explicit numerical consideration of heat generation and conduction at elevated loading rates allows a better estimation of failure compared to the Master Curve concept, this still poor assessment quality can also be obtained by simply utilizing the adjusted “dynamic” Master Curve with an increased exponent of p = 0.030 /°C. It is therefore concluded that this exponent adjustment approximates the impact of heat effects quite well. The shortcomings of the numerical model were observed to correlate strongly with the documented amount of local crack arrest events on the fracture surface. This leads to a micromechanically-motivated adjustment of a local approach model to incorporate this mechanism. This modification ensures a more satisfying physical background of the local approach model. Moreover, it significantly improves model analysis accuracy for all examined testing conditions.

Acute lethargy, stridor, and hypoxemia in a young adult.

A young adult with intellectual delay presented to the emergency department (ED) from a group home via ambulance with altered mental status and respiratory distress. The patient was known to be non-verbal but definitely alert and interactive at baseline. On arrival, the patient was lethargic with frequent coughing and notable stridor, unable to obey commands. Emergency medical services reported SpO2 was initially 85%, but the hypoxemia had improved with supplemental oxygen administered via non-rebreather mask. Partial airway obstruction was suspected due to the stridor, and it was feared that the paralysis of rapid sequence intubation might result in a “can't oxygenate, can't ventilate” scenario. Preparations were made for immediate emergency airway management with a dual set-up for awake fiberoptic tracheal intubation and a cricothyroidotomy. Nasal cannula was applied at flush rate with SpO2 sustained at 100% throughout the procedure. Ketamine was used to facilitate fiberoptic nasopharyngoscopy, which identified a green foreign body obstructing a view of the entire glottis. Standard geometry video laryngoscopy was then employed to guide foreign body retrieval with Magill forceps and a DuCanto (SSCOR, Inc) suction catheter (Video 1). It was evident during removal that the foreign body was aspirated broccoli. The patient recovered from sedation and had no further need for supplemental oxygen in the ED. The patient was treated for aspiration pneumonia, admitted for observation, and was discharged at their neurologic baseline the next day. Incomplete foreign body airway obstruction (FBAO) is a time-sensitive emergency that mandates urgent intervention before progression to complete obstruction, which will always rapidly deteriorate to cardiac arrest. Immediate removal is critical to patients surviving with good neurologic outcomes in the event of a cardiac arrest.1 Operators should be prepared to follow well-established algorithms for the management of incomplete and complete FBAOs.2 Magill forceps have been part of airway management for over a century3 and are known to be effective in removing FBAOs in prehospital cardiac arrests.4 The DuCanto (SSCOR, Inc) suction catheter is a wide-bore rigid suction catheter that has been shown to effectively remove viscous liquid in simulated airway contaminations5 but was successful in removing smaller solid foreign bodies for this case. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Implementation of nursing-led follow-up service for patients newly discharged from paediatric intensive care units: quality improvement initiative

BackgroundHuman resource shortages are a global challenge in the healthcare system and create barriers in providing timely follow-up visits for paediatric patients discharged recently from the intensive care unit (ICU)....

Feasibility of accelerated code team activation with code button triggered smartphone notification

IntroductionStudies support rapid interventions to improve outcomes in patients with in-hospital cardiac arrest. We sought to decrease the time to code team activation and improve dissemination of patient-specific data to facilitate targeted treatments. MethodsWe mapped code blue buttons behind each bed to patients through the electronic medical record. Pushing the button sent patient-specific data (admitting diagnosis, presence of difficult airway, and recent laboratory values) through a secure messaging system to the responding teams’ smartphones. The code button also activated a hospital-wide alert through the operator. We piloted the system on seven medicine inpatient units from November 2019 through May 2022. We compared the time from code blue button press to smartphone message receipt vs traditional operator-sent overhead page. ResultsThe code button was the primary mode of code team activation for 12/35 (34.3%) cardiac arrest events. The code team received smartphone notifications a median of 78 s (IQR = 47–127 s) before overhead page. The median time to adrenaline administration for codes activated with the code button was not significantly different (240 s (IQR 142–300 s for code button) vs 148 s (IQR = 34–367 s) for overhead page, p = 0.89). Survival to discharge was 3/12 (25.0%) for codes activated with the code button vs 4/23 (17.4%) when activated by calling the operator (p = 0.67). ConclusionImplementation of a smartphone-based code button notification system reduced time to code team activation by 78 s. Larger cohorts are necessary to assess effects on patient outcomes.

Cardiopulmonary Resuscitation Techniques in the COVID-19 Pandemic Era: Literature Review

Cardiac resuscitation in the era of the COVID-19 pandemic meets its challenges; in addition to the high prevalence of cardiac and pulmonary arrest events in these patients, the transmission rate to health workers who carry out CPR assistance is also relatively high. Therefore, it is necessary to develop CPR techniques in COVID-19 patients that can increase the success of CPR and reduce transmission rates. The purpose of the study was to explain how CPR techniques are in COVID-19 patients. The literature review method through data collection with an electronic database and evaluation of the literature review will use Critical Appraisal to test validity. Data collection with electronic databases was conducted through PubMed, Tailor, Francis, and Google Scholar with the keyword "CPR," "COVID-19," and " technique. "The data was successfully collected in the database of 548 articles then filtered the inclusion and exclusion criteria into ten pieces; then the article passed the Critical Appraisal test. Hasil Literature review CPR technique in covid patients added is the use of PPE level C/3; The recommended compression depth is 2-2.4 inches (5-6cm); manual chest compression is described as effective when administered in the middle of the chest, at a rate of 100-120 minutes. , The recommended position is prone and supine.

Temporal analysis of continuous chest compression rate and depth performed by firefighters during out of hospital cardiac arrest

BackgroundQuality of chest compressions (CC) during cardiopulmonary resuscitation (CPR) often do not meet guideline recommendations for rate and depth. This may be due to the fatiguing nature of physically compressing a patient’s chest, meaning that CPR quality reduces over time. ObjectiveThis analysis investigates the effect of CPR duration on the performance of continuous CCs delivered by firefighters equipped with CPR feedback devices. MethodsData were collected from a first responder group which used CPR feedback and automatic external defibrillator devices when attending out-of-hospital cardiac arrest events. Depth and rate of CC were analysed for 134 patients. Mean CC depth and rate were calculated every 5 s during two-minute episodes of CPR. Regression models were created to evaluate the relationship between applied CC depth and rate as a function of time. ResultsMean (SD) CC depth during the investigation was 48 (9) mm. An inverse relationship was observed between CC depth and CPR duration, where CC depth decreased by 3.39 mm, over two-minutes of CPR (p < 0.001). Mean (SD) CC rate was 112.06 (5.87) compressions per minute. No significant relationship was observed between CC rate and CPR duration (p = 0.077). Mean depth was within guideline range for 33.58% of patient events, while guideline rate was observed in 92.54% of cases. ConclusionsA reduction in CC depth was observed during two-minutes of continuous CCs while CC rate was not affected. One third of patients received a mean CC depth within guideline range (50 to 60 mm).

Cardiopulmonary Resuscitation Capacity Building Training for High School Students in Martapura, Banjar Regency

The Banjar Regency area is prone to flooding and is one of the disaster areas that can cause casualties and stress that triggers an increase in cardiovascular disease sufferers. This condition requires community preparedness for emergencies. The purpose of this community service activity is to train partners skills in cardiopulmonary resuscitation skills to be able to help victims of cardiac or respiratory arrest. The first implementation of this community service activity is carrying out an initial test to recognize emergency signs in heart and lung attacks, then providing an introduction to the concept of heart and lung emergency through lecture methods, discussion, and sharing related to real events of cardiopulmonary arrest in the community, then the final stage is evaluation of student abilities. The target of this community service activity was 40 students who are members of the High School Youth Red Cross in Martapura City, Banjar Regency. The results of this community service activity students understand material related to cardiopulmonary resuscitation, and providing basic life support counseling has a significant effect on student knowledge. Through this activity, students are expected to be able to provide a pre-hospital cardiopulmonary resuscitation simulation, and students can disseminate information to those closest to them.

EBNEO Commentary: Safety and efficacy of erythropoietin in neonates with hypoxic-ischaemic encephalopathy.

EBNEO Commentary: Safety and efficacy of erythropoietin in neonates with hypoxic-ischaemic encephalopathy.

Dedicated chest compressor team: A quality improvement initiative to improve chest compression performance at in-hospital cardiac arrest events through quarterly training

BackgroundHigh-quality cardiopulmonary resuscitation (CPR) is foundational to all resuscitative efforts. Spaced practice improves learners’ skill retention. We evaluated the implementation of a quarterly CPR curriculum and skills training program for a dedicated chest compressor team to improve the quality of CPR performed during in-hospital cardiac arrest (IHCA) events and its impact on patient survival of event. MethodsBaseline observations on CPR performance within the hospital were collected in October 2018. The CPR quarterly training program was implemented in November 2018. Training included use of high-fidelity simulation manikins and team members received real-time feedback scores related to compression rate, depth and recoil. High-quality CPR scores were set at ≥ 70%. Yearly IHCA event survival data was examined in relation to the implementation of training. ResultsQuarterly CPR training of the team led to retention of CPR skills (chest compression rate, depth, and recoil). The team’s initial CPR training performance average score was 49.1%, increasing to 80.3%, with 95% (n = 37) of participants achieving a higher score after feedback during their initial training. A two-sample t-test was used for numerical data and chi-square was used for proportional data analysis. The survival of event prior to this training was 61.0% January-October 2018. Post -training, event survival rose to 73.5% (p-value 0.03) in 2019. ConclusionImplementation of a team that attends quarterly CPR training with a high-fidelity simulation manikin is attainable. This training resulted in improved CPR quality and benefited IHCA event survival.

171 - Sustained reduction in cardiac arrest events in a cardiac intensive care unit: a single center quality improvement experience

171 - Sustained reduction in cardiac arrest events in a cardiac intensive care unit: a single center quality improvement experience

Mechanical life support algorithm for the emergency management of patients with left-sided Impella.

We sought to remedy the limited guidance that is available to support the resuscitation of patients with the Impella Cardiac Power (CP) and 5.0 devices during episodes of cardiac arrest or life-threatening events that can result in haemodynamic decompensation. In a specialist tertiary referral centre we developed, by iteration, a novel resuscitation algorithm for Impella emergencies, which we validated through simulation and assessment by our multi- disciplinary team. A mechanical life support course was established to provide theoretical and practical education, combined with simulation to consolidate knowledge and confidence in algorithm use. We assessed these measures using confidence scoring, a key performance indicator (the time taken to resolve a suction event) and a multiple-choice question (MCQ) examination. Following this intervention, median confidence score increased from 2 (interquartile range [IQR] 2 to 3) to 4 (IQR 4 to 4) out of a maximum of 5 (n=53, p<0.0001). Theoretical knowledge of the Impella, as assessed by median MCQ score, increased from 12 (IQR 10 to 13) to 13 (12 to 14) out of a maximum of 17 (p<0.0001). The use of a bespoke Impella resuscitation algorithm reduced the mean time taken to identify and resolve a suction event by 53 seconds (95% confidence interval 36 to 99, p=0.0003). In conclusion, we present an evidence-based resuscitation algorithm that provides both technical and medical guidance to clinicians responding to life-threatening events in Impella recipients.

A Machine Learning Approach Using Statistical Models for Early Detection of Cardiac Arrest in Newborn Babies in the Cardiac Intensive Care Unit

Cardiac arrest in newborn babies is an alarming yet typical medical emergency. Early detection is critical for providing these babies with the best care and treatment. Recent research has focused on identifying the potential indicators and biomarkers of cardiac arrest in newborn babies and developing accurate and efficient diagnostic tools for early detection. An array of imaging techniques, such as echocardiography and computed tomography may help provide early detection of cardiac arrest. This research aims to develop a Cardiac Machine Learning model (CMLM) using statistical models for the early detection of cardiac arrest in newborn babies in the Cardiac Intensive Care Unit (CICU). The cardiac arrest events were identified using a combination of the neonate’s physiological parameters. Statistical modeling techniques, such as logistic regression and support vector machines, were used to construct predictive models for cardiac arrest. The proposed model will be used in the CICU to enable early detection of cardiac arrest in newborn babies. In a training (Tr) comparison region, the proposed CMLA reached 0.912 delta-p value, 0.894 False discovery rate (FDR) value, 0.076 False omission rate (FOR) value, 0.859 prevalence threshold value and 0.842 CSI value. In a testing (Ts) comparison region, the proposed CMLA reached 0.896 delta-p values, 0.878 FDR value, 0.061 FOR value, 0.844 prevalence threshold values and 0.827 CSI value. It will help reduce the mortality and morbidity of newborn babies due to cardiac arrest in the CICU.