Deep Learning-Based Localization and Detection of Malpositioned Endotracheal Tube on Portable Supine Chest Radiographs in Intensive and Emergency Medicine: A Multicenter Retrospective Study.

OBJECTIVES: We aimed to develop a computer-aided detection (CAD) system to localize and detect the malposition of endotracheal tubes (ETTs) on portable supine chest radiographs (CXRs). DESIGN: This was a retrospective diagnostic study. DeepLabv3+ with ResNeSt50 backbone and DenseNet121 served as the model architecture for segmentation and classification tasks, respectively. SETTING: Multicenter study. PATIENTS: For the training dataset, images meeting the following inclusion criteria were included: 1) patient age greater than or equal to 20 years; 2) portable supine CXR; 3) examination in emergency departments or ICUs; and 4) examination between 2015 and 2019 at National Taiwan University Hospital (NTUH) (NTUH-1519 dataset: 5,767 images). The derived CAD system was tested on images from chronologically (examination during 2020 at NTUH, NTUH-20 dataset: 955 images) or geographically (examination between 2015 and 2020 at NTUH Yunlin Branch [YB], NTUH-YB dataset: 656 images) different datasets. All CXRs were annotated with pixel-level labels of ETT and with image-level labels of ETT presence and malposition. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: For the segmentation model, the Dice coefficients indicated that ETT would be delineated accurately (NTUH-20: 0.854; 95% CI, 0.824-0.881 and NTUH-YB: 0.839; 95% CI, 0.820-0.857). For the classification model, the presence of ETT could be accurately detected with high accuracy (area under the receiver operating characteristic curve [AUC]: NTUH-20, 1.000; 95% CI, 0.999-1.000 and NTUH-YB: 0.994; 95% CI, 0.984-1.000). Furthermore, among those images with ETT, ETT malposition could be detected with high accuracy (AUC: NTUH-20, 0.847; 95% CI, 0.671-0.980 and NTUH-YB, 0.734; 95% CI, 0.630-0.833), especially for endobronchial intubation (AUC: NTUH-20, 0.991; 95% CI, 0.969-1.000 and NTUH-YB, 0.966; 95% CI, 0.933-0.991). CONCLUSIONS: The derived CAD system could localize ETT and detect ETT malposition with excellent performance, especially for endobronchial intubation, and with favorable potential for external generalizability.

Impact of Postarrest Vasoactive-Inotropic Score on Acute Kidney Injury in Cardiac Arrest Survivors: A Retrospective Cohort Study.

Background: Postarrest acute kidney injury (AKI) is a major health burden because it is associated with prolonged hospitalization, increased dialysis requirement, high mortality, and unfavorable neurological outcomes. Managing hemodynamic instability during the early postarrest period is critical; however, the role of quantified vasopressor dependence in AKI development in relation to illness severity remains unclear. Methods: A retrospective, observational cohort study that enrolled 411 non-traumatic adult cardiac arrest survivors without pre-arrest end-stage kidney disease between January 2017 and December 2019, grouped according to their baseline kidney function. The criteria for kidney injury were based on the Kidney Disease: Improving Global Outcomes definition and AKI staging system. The degree of vasopressor dependence within the first 24 h following return of spontaneous circulation (ROSC) was presented using the maximum vasoactive-inotropic score ( VIS max ). Results: Of the 411 patients, 181 (44%) had early AKI after ROSC. Patients with AKI showed an increased risk of in-hospital mortality (adjusted OR [aOR] 5.40, 95% CI 3.36-8.69, p < 0.001) and unfavorable neurological outcome (aOR 5.70, 95% CI 3.45-9.43, p < 0.001) compared to patients without AKI. The risk of adverse outcomes increased with illness severity. Patients with vasopressor support had an increased risk of early AKI. A low VIS max was associated with AKI stage 1-2 (aOR 2.51, 95% CI 1.20-5.24), whereas a high VIS max was associated with an increased risk for AKI stage 3 (aOR 2.46, 95% CI 1.28-4.75). Conclusions: Early AKI is associated with an increased risk of in-hospital mortality and unfavorable neurologic recovery in cardiac arrest survivors. Postarrest VIS max is an independent predictor of the development and severity of AKI following ROSC, regardless of baseline kidney function.

Outcome prediction of cardiac arrest with automatically computed gray-white matter ratio on computed tomography images.

BACKGROUND: This study aimed to develop an automated method to measure the gray-white matter ratio (GWR) from brain computed tomography (CT) scans of patients with out-of-hospital cardiac arrest (OHCA) and assess its significance in predicting early-stage neurological outcomes. METHODS: Patients with OHCA who underwent brain CT imaging within 12 h of return of spontaneous circulation were enrolled in this retrospective study. The primary outcome endpoint measure was a favorable neurological outcome, defined as cerebral performance category 1 or 2 at hospital discharge. We proposed an automated method comprising image registration, K-means segmentation, segmentation refinement, and GWR calculation to measure the GWR for each CT scan. The K-means segmentation and segmentation refinement was employed to refine the segmentations within regions of interest (ROIs), consequently enhancing GWR calculation accuracy through more precise segmentations. RESULTS: Overall, 443 patients were divided into derivation N=265, 60% and validation N=178, 40% sets, based on age and sex. The ROI Hounsfield unit values derived from the automated method showed a strong correlation with those obtained from the manual method. Regarding outcome prediction, the automated method significantly outperformed the manual method in GWR calculation (AUC 0.79 vs. 0.70) across the entire dataset. The automated method also demonstrated superior performance across sensitivity, specificity, and positive and negative predictive values using the cutoff value determined from the derivation set. Moreover, GWR was an independent predictor of outcomes in logistic regression analysis. Incorporating the GWR with other clinical and resuscitation variables significantly enhanced the performance of prediction models compared to those without the GWR. CONCLUSIONS: Automated measurement of the GWR from non-contrast brain CT images offers valuable insights for predicting neurological outcomes during the early post-cardiac arrest period.

The compliance with TTM protocol may benefit outcomes in cardiac arrest survivors: A retrospective cohort study.

BACKGROUND: Established protocols for implementing high-quality targeted temperature management (TTM) provide guidance concerning the cooling rate, duration of maintenance, and rewarming speed. However, whether compliant to TTM protocols results in improved survival and better neurological recovery has not been examined. METHODS: A retrospective cohort study enrolled 1141 survivors of non-traumatic adult cardiac arrest with a pre-arrest cerebral performance category (CPC) score of 1-2 from 2015 to 2020 at a tertiary medical center. Of the survivors, 330 patients who underwent TTM were further included. Patients with spontaneous hypothermia (<35 °C) (n = 107) and expired during the TTM (n = 21) were excluded. A total of 202 patients were thus enrolled. One hundred and ten patients underwent TTM that completely complied with the protocol (protocol-complaint group), but 92 patients deviated in some manner from the protocol (protocol non-compliant group). RESULTS: Fifty patients (50%) and 46 patients (50%) in the protocol-compliant and non-compliant groups, respectively, did not survive to hospital discharge. In the protocol-compliant group, 42 patients (38.2%) had favorable neurological recovery, compared with 32 patients (34.8%) in the protocol non-compliant group. After adjusting for age, initial shockable rhythm, witnessed collapse, and cardiopulmonary resuscitation duration, protocol non-compliant was associated with the poor neurological outcomes (aOR 2.44, 95% CI = 1.13-5.25), but not with in-hospital mortality (aOR 1.31, 95% CI = 0.70-2.47). The most common reason for noncompliance was a prolonged duration reaching the target temperature (n = 33, 58.7%). The number of phases of non-compliant was not significantly associated with in-hospital mortality or poor neurological recovery. CONCLUSION: Among cardiac arrest survivors undergoing TTM, those who did not receive TTM that in compliance with the protocol were more likely to experience poor neurological recovery than those whose TTM fully complied with the protocols. The most frequently identified deviation was a prolonged duration to reaching the target temperature.

A novel scale for triage assessment of frailty in the emergency department (ED-FraS): a prospective videotaped study.

BACKGROUND: Rapid recognition of frailty in older patients in the ED is an important first step toward better geriatric care in the ED. We aimed to develop and validate a novel frailty assessment scale at ED triage, the Emergency Department Frailty Scale (ED-FraS). METHODS: We conducted a prospective cohort study enrolling adult patients aged 65 years or older who visited the ED at an academic medical center. The entire triage process was recorded, and triage data were collected, including the Taiwan Triage and Acuity Scale (TTAS). Five physician raters provided ED-FraS levels after reviewing videos. A modified TTAS (mTTAS) incorporating ED-FraS was also created. The primary outcome was hospital admission following the ED visit, and secondary outcomes included the ED length of stay (EDLOS) and total ED visit charges. RESULTS: A total of 256 patients were included. Twenty-seven percent of the patients were frail according to the ED-FraS. The majority of ED-FraS was level 2 (57%), while the majority of TTAS was level 3 (81%). There was a weak agreement between the ED-FraS and TTAS (kappa coefficient of 0.02). The hospital admission rate and charge were highest at ED-FraS level 5 (severely frail), whereas the EDLOS was longest at level 4 (moderately frail). The area under the Receiver Operating Characteristic curve (AUROC) in predicting hospital admission for the TTAS, ED-FraS, and mTTAS were 0.57, 0.62, and 0.63, respectively. The ED-FraS explained more variation in EDLOS (R2 = 0.096) compared with the other two methods. CONCLUSIONS: The ED-Fras tool is a simple and valid screening tool for identifying frail older adults in the ED. It also can complement and enhance ED triage systems. Further research is needed to test its real-time use at ED triage internationally.

Application of Phosphorylated Tau for Predicting Outcomes Among Sudden Cardiac Arrest Survivors.

BACKGROUND: Phosphorylated Tau (p-Tau), an early biomarker of neuronal damage, has emerged as a promising candidate for predicting neurological outcomes in cardiac arrest (CA) survivors. Despite its potential, the correlation of p-Tau with other clinical indicators remains underexplored. This study assesses the predictive capability of p-Tau and its effectiveness when used in conjunction with other predictors. METHODS: In this single-center retrospective study, 230 CA survivors had plasma and brain computed tomography scans collected within 24 h after the return of spontaneous circulation (ROSC) from January 2016 to June 2023. The patients with prearrest Cerebral Performance Category scores ≥ 3 were excluded (n = 33). The neurological outcomes at discharge with Cerebral Performance Category scores 1-2 indicated favorable outcomes. Plasma p-Tau levels were measured using an enzyme-linked immunosorbent assay, diastolic blood pressure (DBP) was recorded after ROSC, and the gray-to-white matter ratio (GWR) was calculated from brain computed tomography scans within 24 h after ROSC. RESULTS: Of 197 patients enrolled in the study, 54 (27.4%) had favorable outcomes. Regression analysis showed that higher p-Tau levels correlated with unfavorable neurological outcomes. The levels of p-Tau were significantly correlated with DBP and GWR. For p-Tau to differentiate between neurological outcomes, an optimal cutoff of 456 pg/mL yielded an area under the receiver operating characteristic curve of 0.71. Combining p-Tau, GWR, and DBP improved predictive accuracy (area under the receiver operating characteristic curve = 0.80 vs. 0.71, p = 0.008). CONCLUSIONS: Plasma p-Tau levels measured within 24 h following ROSC, particularly when combined with GWR and DBP, may serve as a promising biomarker of neurological outcomes in CA survivors, with higher levels predicting unfavorable outcomes.

Large language model application in emergency medicine and critical care.

In the rapidly evolving healthcare landscape, artificial intelligence (AI), particularly the large language models (LLMs), like OpenAI's Chat Generative Pretrained Transformer (ChatGPT), has shown transformative potential in emergency medicine and critical care. This review article highlights the advancement and applications of ChatGPT, from diagnostic assistance to clinical documentation and patient communication, demonstrating its ability to perform comparably to human professionals in medical examinations. ChatGPT could assist clinical decision-making and medication selection in critical care, showcasing its potential to optimize patient care management. However, integrating LLMs into healthcare raises legal, ethical, and privacy concerns, including data protection and the necessity for informed consent. Finally, we addressed the challenges related to the accuracy of LLMs, such as the risk of providing incorrect medical advice. These concerns underscore the importance of ongoing research and regulation to ensure their ethical and practical use in healthcare.

Performance of Prehospital ECG and Impact on Prehospital Service Time: Comparison between EMT-II and EMT-P Teams.

Background: Prehospital electrocardiogram (PHECG) shortens door-to-balloon time in patients with ST-elevation myocardial infarction. However, it may increase the prehospital service time, thus offsetting the benefits gained. The performance of PHECG could be influenced by the proficiency of the emergency medical technicians (EMTs). Objectives: To investigate whether there are differences in the performance of PHECG between EMT-II and EMT-paramedics (EMT-P). Methods: This prospectively designed, retrospectively analyzed study of PHECG was conducted in Taipei from February 2019 to April 2021. Comparisons were made between EMT-II and EMT-P teams. The primary outcomes were the acceptance of PHECG suggestions and prehospital service time. The secondary outcomes were gender disparities in the primary outcomes. Results: A total of 2,991 patients were included, of whom 2,617 received PHECG. For the primary outcomes, the acceptance of PHECG was higher in those approached by EMT-P (99.6% vs. 71.5%, p < 0.001). The scene time and scene-to-hospital time showed no significant differences. For gender disparities, the acceptance of PHECG in female patients was significantly lower in those approached by EMT-II (59.3% vs. 99.2%, p < 0.001). The scene time and scene-to-hospital time were generally longer in the female patients, especially in the younger and middle age groups. Compared to EMT-P, both were significantly longer in the female patients approached by EMT-II. Conclusions: The acceptance of PHECG was lower in those approached by EMT-II, especially in females. Although there were generally no significant differences between EMT-II and EMT-P, the scene time and scene-to-hospital time were significantly longer in female patients, especially in those aged < 75 years approached by EMT-II.

Clinical Validation of Explainable Deep Learning Model for Predicting the Mortality of In-Hospital Cardiac Arrest Using Diagnosis Codes of Electronic Health Records.

Background: Using deep learning for disease outcome prediction is an approach that has made large advances in recent years. Notwithstanding its excellent performance, clinicians are also interested in learning how input affects prediction. Clinical validation of explainable deep learning models is also as yet unexplored. This study aims to evaluate the performance of Deep SHapley Additive exPlanations (D-SHAP) model in accurately identifying the diagnosis code associated with the highest mortality risk. Methods: Incidences of at least one in-hospital cardiac arrest (IHCA) for 168,693 patients as well as 1,569,478 clinical records were extracted from Taiwan's National Health Insurance Research Database. We propose a D-SHAP model to provide insights into deep learning model predictions. We trained a deep learning model to predict the 30-day mortality likelihoods of IHCA patients and used D-SHAP to see how the diagnosis codes affected the model's predictions. Physicians were asked to annotate a cardiac arrest dataset and provide expert opinions, which we used to validate our proposed method. A 1-to-4-point annotation of each record (current decision) along with four previous records (historical decision) was used to validate the current and historical D-SHAP values. Results: A subset consisting of 402 patients with at least one cardiac arrest record was randomly selected from the IHCA cohort. The median age was 72 years, with mean and standard deviation of 69 ± 17 years. Results indicated that D-SHAP can identify the cause of mortality based on the diagnosis codes. The top five most important diagnosis codes, namely respiratory failure, sepsis, pneumonia, shock, and acute kidney injury were consistent with the physician's opinion. Some diagnoses, such as urinary tract infection, showed a discrepancy between D-SHAP and clinical judgment due to the lower frequency of the disease and its occurrence in combination with other comorbidities. Conclusions: The D-SHAP framework was found to be an effective tool to explain deep neural networks and identify most of the important diagnoses for predicting patients' 30-day mortality. However, physicians should always carefully consider the structure of the original database and underlying pathophysiology.

Combination of Cerebral Computed Tomography and Simplified Cardiac Arrest Hospital Prognosis (sCAHP) Score for Predicting Neurological Recovery in Cardiac Arrest Survivors.

Background: Cerebral computed tomography (CT) and various severity scoring systems have been developed for the early prediction of the neurological outcomes of cardiac arrest survivors. However, few studies have combined these approaches. Therefore, we evaluated the value of the combination of cerebral CT and severity score for neuroprognostication. Methods: This single-center, retrospective observational study included consecutive patients surviving nontraumatic cardiac arrest (January 2016 and December 2020). Gray-to-white ratio (GWR), third and fourth ventricle characteristics, and medial temporal lobe atrophy scores were evaluated on noncontrast cerebral CT. Simplified cardiac arrest hospital prognosis (sCAHP) score was calculated for severity assessment. The associations between the CT characteristics, sCAHP score and neurological outcomes were analyzed. Results: This study enrolled 559 patients. Of them, 194 (34.7%) were discharged with favorable neurological outcomes. Patients with favorable neurological outcome had a higher GWR (1.37 vs 1.25, p < 0.001), area of fourth ventricle (461 vs 413 mm 2 , p < 0.001), anteroposterior diameter of fourth ventricle (0.95 vs 0.86 cm , p < 0.001) and a lower sCAHP score (146 vs 190, p < 0.001) than those with poor recovery. Patients with higher sCAHP score had lower GWR (p trend < 0.001), area of fourth ventricle (p trend = 0.019) and anteroposterior diameter of fourth ventricle (p trend = 0.014). The predictive ability by using area under receiver operating characteristic curve (AUC) for the combination of sCAHP score and GWR was significantly higher than that calculated for sCAHP (0.86 vs 0.76, p < 0.001) or GWR (0.86 vs 0.81, p = 0.001) alone. Conclusions: The combination of GWR and sCAHP score can be used to effectively predict the neurological outcomes of cardiac arrest survivors and thus ensure timely intervention for those at high risk of poor recovery.

Point-of-care testing for adult out-of-hospital cardiac arrest resuscitated at the ED to predict ROSC: Development and external validation of POC-ED-ROSC model.

BACKGROUND AND IMPORTANCE: Most prediction models, like return of spontaneous circulation (ROSC) after cardiac arrest (RACA) or Utstein-based (UB)-ROSC score, were developed for prehospital settings to predict the probability of ROSC in patients with out-of-hospital cardiac arrest (OHCA). A prediction model has been lacking for the probability of ROSC in patients with OHCA at emergency departments (EDs). OBJECTIVE: In the present study, a point-of-care (POC) testing-based model, POC-ED-ROSC, was developed and validated for predicting ROSC of OHCA at EDs. DESIGN, SETTINGS AND PARTICIPANTS: Prospectively collected data for adult OHCA patients between 2015 and 2020 were analysed. POC blood gas analysis obtained within 5 min of ED arrival was used. OUTCOMES MEASURE AND ANALYSIS: The primary outcome was ROSC. In the derivation cohort, multivariable logistic regression was used to develop the POC-ED-ROSC model. In the temporally split validation cohort, the discriminative performance of the POC-ED-ROSC model was assessed using the area under the receiver operating characteristic (ROC) curve (AUC) and compared with RACA or UB-ROSC score using DeLong test. MAIN RESULTS: The study included 606 and 270 patients in the derivation and validation cohorts, respectively. In the total cohort, 471 patients achieved ROSC. Age, initial cardiac rhythm at ED, pre-hospital resuscitation duration, and POC testing-measured blood levels of lactate, potassium and glucose were significant predictors included in the POC-ED-ROSC model. The model was validated with fair discriminative performance (AUC: 0.75, 95% confidence interval [CI]: 0.69-0.81) with no significant differences from RACA (AUC: 0.68, 95% CI: 0.62-0.74) or UB-ROSC score (AUC: 0.74, 95% CI: 0.68-0.79). CONCLUSION: Using only six easily accessible variables, the POC-ED-ROSC model can predict ROSC for OHCA resuscitated at ED with fair accuracy.

Acute exacerbation of chronic obstructive pulmonary disease in United States emergency departments, 2010-2018.

OBJECTIVES: Little is known about the recent status of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in the U.S. emergency department (ED). This study aimed to describe the disease burden (visit and hospitalization rate) of AECOPD in the ED and to investigate factors associated with the disease burden of AECOPD. METHODS: Data were obtained from the National Hospital Ambulatory Medical Care Survey (NHAMCS), 2010-2018. Adult ED visits (aged 40 years or above) with AECOPD were identified using International Classification of Diseases codes. Analysis used descriptive statistics and multivariable logistic regression accounting for NHAMCS's complex survey design. RESULTS: There were 1,366 adult AECOPD ED visits in the unweighted sample. Over the 9-year study period, there were an estimated 7,508,000 ED visits for AECOPD, and the proportion of AECOPD visits in the entire ED population remained stable at approximately 14 per 1,000 visits. The mean age of these AECOPD visits was 66 years, and 42% were men. Medicare or Medicaid insurance, presentation in non-summer seasons, the Midwest and South regions (vs. Northeast), and arrival by ambulance were independently associated with a higher visit rate of AECOPD, whereas non-Hispanic black or Hispanic race/ethnicity (vs. non-Hispanic white) was associated with a lower visit rate of AECOPD. The proportion of AECOPD visits that were hospitalized decreased from 51% to 2010 to 31% in 2018 (p = 0.002). Arrival by ambulance was independently associated with a higher hospitalization rate, whereas the South and West regions (vs. Northeast) were independently associated with a lower hospitalization rate. The use of antibiotics appeared to be stable over time, but the use of systemic corticosteroids appeared to increase with near statistical significance (p = 0.07). CONCLUSIONS: The number of ED visits for AECOPD remained high; however, hospitalizations for AECOPD appeared to decrease over time. Some patients were disproportionately affected by AECOPD, and certain patient and ED factors were associated with hospitalizations. The reasons for decreased ED admissions for AECOPD deserve further investigation.

The Effectiveness of Online-Only Blended Cardiopulmonary Resuscitation Training: Static-Group Comparison Study.

BACKGROUND: Basic life support (BLS) education is essential for improving bystander cardiopulmonary resuscitation (CPR) rates, but the imparting of such education faces obstacles during the outbreak of emerging infectious diseases, such as COVID-19. When face-to-face teaching is limited, distance learning-blended learning (BL) or an online-only model-is encouraged. However, evidence regarding the effect of online-only CPR training is scarce, and comparative studies on classroom-based BL (CBL) are lacking. While other strategies have recommended self-directed learning and deliberate practice to enhance CPR education, no previous studies have incorporated all of these instructional methods into a BLS course. OBJECTIVE: This study aimed to demonstrate a novel BLS training model-remote practice BL (RBL)-and compare its educational outcomes with those of the conventional CBL model. METHODS: A static-group comparison study was conducted. It included RBL and CBL courses that shared the same paradigm, comprising online lectures, a deliberate practice session with Little Anne quality CPR (QCPR) manikin feedback, and a final assessment session. In the main intervention, the RBL group was required to perform distant self-directed deliberate practice and complete the final assessment via an online video conference. Manikin-rated CPR scores were measured as the primary outcome; the number of retakes of the final examination was the secondary outcome. RESULTS: A total of 52 and 104 participants from the RBL and CBL groups, respectively, were eligible for data analysis. A comparison of the 2 groups revealed that there were more women in the RBL group than the CBL group (36/52, 69.2% vs 51/104, 49%, respectively; P=.02). After adjustment, there were no significant differences in scores for QCPR release (96.9 vs 96.4, respectively; P=.61), QCPR depth (99.2 vs 99.5, respectively; P=.27), or QCPR rate (94.9 vs 95.5, respectively; P=.83). The RBL group spent more days practicing before the final assessment (12.4 vs 8.9 days, respectively; P<.001) and also had a higher number of retakes (1.4 vs 1.1 times, respectively; P<.001). CONCLUSIONS: We developed a remote practice BL-based method for online-only distant BLS CPR training. In terms of CPR performance, using remote self-directed deliberate practice was not inferior to the conventional classroom-based instructor-led method, although it tended to take more time to achieve the same effect. TRIAL REGISTRATION: Not applicable.

The effect of point-of-care ultrasound on length of stay and mortality in patients with chest pain/dyspnea.

PURPOSE: This study aims to investigate the effects of point-of-care ultrasound (PoCUS) on length of stay (LOS) and mortality in hemodynamically stable patients with chest pain/dyspnea. MATERIALS AND METHODS: The prospective study was conducted from June 2020 to May 2021. A convenience sample of adult non-traumatic patients with chest pain/dyspnea was included and evaluated by PoCUS. The primary outcome was the relationship between the door-to-PoCUS time and LOS/mortality categorized by the ST-segment elevation (STE) and non-STE on the initial electrocardiogram. The diagnostic accuracy of PoCUS was computed, compared to the final diagnosis. RESULTS: A total of 465 patients were included. 3 of 18 patients with STE had unexpected cardiac tamponade and 1 had myocarditis with pulmonary edema. PoCUS had a minimal effect on LOS and mortality in patients with STE. In the non-STE group, the shorter door-to-PoCUS time was associated with a shorter LOS (coefficient, 1.26±0.47, p=0.008). After categorizing the timing of PoCUS as 30, 60, 90, and 120 minutes, PoCUS had a positive effect, especially when performed within 90 minutes of arrival, on LOS of less than 360 minutes (OR, 2.42, 95% CI, 1.61-3.64) and patient survival (OR, 3.32, 95% CI, 1.14-9.71). The overall diagnostic performance of PoCUS was 96.6% (95% CI, 94.9-98.2%), but lower efficacy occurred in pulmonary embolism and myocardial infarction. CONCLUSION: The use of PoCUS was associated with a shorter LOS and less mortality in patients with non-STE, especially when performed within 90 minutes of arrival. Although the effect on patients with STE was minimal, PoCUS played a role in discovering unexpected diagnoses.

TIMECARD score: An easily operated prediction model of unfavorable neurological outcomes in out-of-hospital cardiac arrest patients with targeted temperature management.

BACKGROUND: Targeted temperature management (TTM) is recommended for comatose out-of-hospital cardiac arrest (OHCA) survivors. Several prediction models have been proposed; however, most of these tools require data conversion and complex calculations. Early and easy predictive model of neurological prognosis in OHCA survivors with TTM warrant investigation. MATERIALS AND METHODS: This multicenter retrospective cohort study enrolled 408 non-traumatic adult OHCA survivors with TTM from the TaIwan network of targeted temperature ManagEment for CARDiac arrest (TIMECARD) registry during January 2014 to June 2019. The primary outcome was unfavorable neurological outcome at discharge. The clinical variables associated with unfavorable neurological outcomes were identified and a risk prediction score-TIMECARD score was developed. The model was validated with data from National Taiwan University Hospital. RESULTS: There were 319 (78.2%) patients presented unfavorable neurological outcomes at hospital discharge. Eight independent variables, including malignancy, no bystander cardiopulmonary resuscitation (CPR), non-shockable rhythm, call-to-start CPR duration >5 min, CPR duration >20 min, sodium bicarbonate use during resuscitation, Glasgow Coma Scale motor score of 1 at return of spontaneous circulation, and no emergent coronary angiography, revealed a significant correlation with unfavorable neurological prognosis in TTM-treated OHCA survivors. The TIMECARD score was established and demonstrated good discriminatory performance in the development cohort (area under the receiver operating characteristic curve [AUC] = 0.855) and validation cohorts (AUC = 0.918 and 0.877, respectively). CONCLUSION: In emergency settings, the TIMECARD score is a practical and simple-to-calculate tool for predicting neurological prognosis in OHCA survivors, and may help determine whether to initiate TTM in indicated patients.

Comparison of outcomes between cardiogenic and non-cardiogenic cardiac arrest patients receiving targeted temperature management: The nationwide TIMECARD multicenter registry.

BACKGROUND AND PURPOSE: Targeted temperature management (TTM) has been recommended for post-resuscitation care of cardiac arrest (CA) patients who remain comatose. However, the differences between cardiogenic and non-cardiogenic causes need further investigation. Thus, this study aimed to investigate the difference in outcomes between cardiogenic and non-cardiogenic CA patients receiving TTM. METHODS: The TIMECARD registry established the study cohort and database for patients receiving TTM between January 2013 and September 2019. A total of 543 patients were enrolled, with 305 and 238 patients in the cardiogenic and non-cardiogenic groups, respectively. RESULTS: Compared with the non-cardiogenic group, the cardiogenic group had higher proportion of initial shockable rhythm, better survival (cardiogenic: 45.9%; non-cardiogenic: 30.7%, P = 0.0017), and better neurologic performance at discharge. In the cardiogenic group, witnessed collapse (OR = 0.31, 95% CI: 0.13-0.72), and coronary intervention (OR = 0.45, 95% CI: 0.24-0.84) were positive predictors for overall outcome. Mean arterial pressure <65 mmHg led to poor outcome regardless in the cardiogenic (OR = 3.31, 95% CI: 1.46-7.52) or non-cardiogenic group (OR = 2.39, 95% CI: 1.06-5.39). CONCLUSION: Patients with cardiogenic CA post TTM had better survival and neurologic performance at discharge than those without cardiogenic CA. Cardiogenic etiology was a potential predictor of better cardiac arrest survival, but it was not an independent risk factor for overall outcome after adjusting for potential covariates. In the cardiogenic group, better outcomes were reported in patients with witnessed collapse, bystander cardiopulmonary resuscitation, as well as those receiving coronary intervention.

Association between independent practice time and patient outcomes in the emergency department: a retrospective study of residents in three urban hospitals in Taiwan.

BACKGROUND: The purpose of the study was to investigate the relationship between the independent practice time of residents and the quality of care provided in the Emergency Department (ED) across three urban hospitals in Taiwan. The study focused on non-pediatric and non-obstetric complaints, aiming to provide insights into the optimal balance between resident autonomy and patient safety. METHODS: A comprehensive retrospective study was conducted using de-identified electronic health records (EHRs) from the hospital's integrated medical database (iMD) from August 2015 to July 2019. The independent practice time was defined as the duration from the first medical order by a resident to the first modifications by the attending physician. The primary outcome was revisits to the ED within 72 h following discharge. Statistical analysis was conducted using RStudio and pyGAM. RESULTS: The study identified several factors associated with shorter independent practice times (< 30 minutes), including older patient age, male sex, higher body temperature, higher heart rate, lower blood pressure, and the presence of certain comorbidities. Residents practicing independently for 30-120 minutes were associated with similar adjusted odds of patient revisits to the ED (OR 1.034, 95% CI 0.978-1.093) and no higher risk of 7-day mortality (OR 0.674, 95% CI 0.592-0.767) compared to the group with less autonomy. However, independent practice times exceeding 120 minutes were associated with higher odds of revisiting the ED within 72 h. For the group with 120-210 minutes of independent practice time, the OR was 1.113 (95% CI: 1.025-1.208, p = 0.011). For the group with > 210 minutes, the OR was 1.259 (95% CI: 1.094-1.449, p = 0.001), indicating an increased risk of adverse outcomes as the independent practice time increasing. CONCLUSIONS: The study concludes that while providing residents an independent practice time between 30 to 120 minutes may be beneficial, caution should be exercised when this time exceeds 120 minutes. The findings underscore the importance of optimal supervision in enhancing patient care quality and safety. Further research is recommended to explore the long-term effects of different levels of resident autonomy on patient outcomes and the professional development of the residents themselves.

Deep Learning-based Diagnosis and Localization of Pneumothorax on Portable Supine Chest X-ray in Intensive and Emergency Medicine: A Retrospective Study.

PURPOSE: To develop two deep learning-based systems for diagnosing and localizing pneumothorax on portable supine chest X-rays (SCXRs). METHODS: For this retrospective study, images meeting the following inclusion criteria were included: (1) patient age ≥ 20 years; (2) portable SCXR; (3) imaging obtained in the emergency department or intensive care unit. Included images were temporally split into training (1571 images, between January 2015 and December 2019) and testing (1071 images, between January 2020 to December 2020) datasets. All images were annotated using pixel-level labels. Object detection and image segmentation were adopted to develop separate systems. For the detection-based system, EfficientNet-B2, DneseNet-121, and Inception-v3 were the architecture for the classification model; Deformable DETR, TOOD, and VFNet were the architecture for the localization model. Both classification and localization models of the segmentation-based system shared the UNet architecture. RESULTS: In diagnosing pneumothorax, performance was excellent for both detection-based (Area under receiver operating characteristics curve [AUC]: 0.940, 95% confidence interval [CI]: 0.907-0.967) and segmentation-based (AUC: 0.979, 95% CI: 0.963-0.991) systems. For images with both predicted and ground-truth pneumothorax, lesion localization was highly accurate (detection-based Dice coefficient: 0.758, 95% CI: 0.707-0.806; segmentation-based Dice coefficient: 0.681, 95% CI: 0.642-0.721). The performance of the two deep learning-based systems declined as pneumothorax size diminished. Nonetheless, both systems were similar or better than human readers in diagnosis or localization performance across all sizes of pneumothorax. CONCLUSIONS: Both deep learning-based systems excelled when tested in a temporally different dataset with differing patient or image characteristics, showing favourable potential for external generalizability.

Should We Prolong the Observation Period for Neurological Recovery After Cardiac Arrest?

OBJECTIVES: To evaluate whether the recommended observation period of 7 days for cardiac arrest survivors is sufficient for conscious recovery and to identify the variables associated with eventual neurologic recovery among patients with delayed awakening. DESIGN: A retrospective cohort study. SETTING: A single tertiary medical center. PATIENTS: Five-hundred twenty-nine nontraumatic adult cardiac arrest survivors with prearrest favorable neurologic function (Cerebral Performance Category 1-2) who survived to hospital discharge during 2011-2019. INTERVENTIONS: The enrolled patients were classified into favorable (Cerebral Performance Category 1-2) and poor (Cerebral Performance Category 3-4) neurologic recovery according to their neurologic function at hospital discharge. Among patients with favorable neurologic recovery, those who recovered within 7 days were assigned to the early recovery group or after 7 days as the late recovery group. MEASUREMENTS AND MAIN RESULTS: There were 395 patients exhibiting favorable neurologic recovery (n = 357 in the early group, n = 38 in late group) and 134 patients exhibiting poor neurologic recovery (poor recovery group). Among patients who remained unconscious on day 7, delayed awakening was associated with male sex (odds ratio [OR], 3.905; 95% CI, 1.153-13.221), prehospital return of spontaneous circulation (OR, 7.628; 95% CI, 2.084-27.922), therapeutic hypothermia (OR, 4.320; 95% CI, 1.624-11.488), and extracorporeal cardiopulmonary resuscitation (OR, 4.508; 95% CI, 1.414-14.371). Being transferred from another hospital, however, was less likely to be associated with delayed awakening (OR, 0.061; 95% CI, 0.009-0.431). The median duration for patients to regain clear consciousness in the late recovery group was 12.12 days. No patient who recovered consciousness had an unfavorable electroencephalography pattern, however, in patients with poor recovery, the 7-day electroencephalography showed 45 patients with generalized suppression (33.6%), two with burst suppression (1.5%), 14 with seizure/epileptic discharge (10.5%), and one with status epilepticus (0.7%). CONCLUSIONS: Up to 9.6% of cardiac arrest patients with favorable outcomes recover consciousness after the recommended 7 days of observation, indicating the observation time of 7 days seems justified but longer duration may be needed. The results of the culturally and clinically isolated population may limit the application to other population.

Pain trajectories in the emergency department: Patient characteristics and clinical outcomes.

BACKGROUND: Little is known about pain trajectories in the emergency department (ED), which could inform the heterogeneous response to pain treatment. We aimed to identify clinically relevant subphenotypes of pain resolution in the ED and their relationships with clinical outcomes. METHODS: This retrospective cohort study used electronic clinical warehouse data from a tertiary medical center. We retrieved data from 733,398 ED visits over a 7-year period. We selected one ED visit per person and retrieved data including patient demographics, triage data, repeated pain scores evaluated on a numeric rating scale, pain characteristics, laboratory markers, and patient disposition. The primary outcome measures were hospitalization and ED revisit. RESULTS: 28,105 adult ED patients were included with a total of 154,405 pain measurements. Three distinct pain trajectory groups were identified: no pain (57.1%); moderate-to-severe pain, fast resolvers (17.9%); and moderate pain, slow resolvers (24.9%). The fast resolvers responded well to treatment and were independently associated with a lower risk of hospitalization (adjusted odds ratio [aOR], 0.75; 95% confidence interval [CI], 0.70-0.81). By contrast, the slow resolvers had lingering pain in the ED and were independently associated with a higher risk of ED revisit (aOR, 2.65; 95%CI, 1.85-3.69). This group also had higher levels of inflammatory markers, including a higher leukocyte count and a higher level of C-reactive protein. CONCLUSIONS: We identified three novel pain subphenotypes with distinct patterns in clinical characteristics and patient outcomes. A better understanding of the pain trajectories may help with the personalized approach to pain management in the ED.