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.

The Force-Frequency Characteristics of Quartz Wafers under a Cantilever Beam Structure.

This study investigated the force-frequency characteristics of quartz wafers inside a cantilever beam frame. Firstly, the force-frequency coefficient formula of quartz wafers with fixed ends under axial force was analyzed. Firstly, the formula for the force-frequency coefficient of quartz wafers with fixed ends under axial force was analyzed. A force-frequency coefficient formula suitable for cantilever beam structures was derived by considering the changes in surface stress and stiffness of quartz wafers with fixed ends and one end under force on the other. Subsequently, the formula's accuracy was verified by experiments, and the accuracy was more than 92%. In addition, strain simulation analysis was performed on three different shapes of quartz wafers, and experimental verification was carried out on two of them. The results revealed that trapezoidal quartz wafers and cantilever beam structures exhibited superior stress distribution to rectangular chips. Furthermore, by positioning electrodes at various locations on the surface of the quartz chip, it was observed that, as the electrodes moved closer to the fixed end, the force-frequency coefficient of the rectangular quartz chip increased, along with an increase in chip strain under the cantilever structure. In summary, this study provides a new approach for designing cantilever quartz resonator sensors in the future.

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.

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.

Arthroscopic-assisted radiocarpal ligaments tensioning for dynamic radiocarpal instability.

BACKGROUND: Dynamic radiocarpal instability is one of the causes of post-trauma radial-sided wrist pain. It is not easy to diagnose and may possibly be overlooked. The key ligaments responsible for dynamic radiocarpal instability are the radioscaphocapitate (RSC) and long radiolunate (LRL) ligaments. Tensioning of these 2 ligaments could be a method of treatment for dynamic carpal instability. We proposed a method for arthroscopic thermal shrinkage of these 2 ligaments, and for setting a landmark arthroscopically to facilitate identification of these 2 ligaments during the combined open suture tensioning procedure. METHODS: Between January 2016 and May 2020, 12 patients treated with this method were enrolled. The mean age was 33.3 years (range, 18-57 years), and the mean duration from injury to operation was 7.8 months (range, 3-25 months). The diagnosis was mainly depended on the physical examinations and confirmed under arthroscopy. The mean follow-up was 17.7 months (range, 12-26 months). RESULTS: All the patients had marked improvement of pain, grip strength, the Disabilities of the Arm, Shoulder and Hand questionnaire (DASH), and the radiocarpal stability. The wrist range of motion showed significant decrease around 5o in both flexion and extension and around 4o in the ulnar deviation at the final follow-ups. All patients were able to return to their previous full level of work and activities. CONCLUSIONS: We conclude that arthroscopic thermal shrinkage combined with open suture tensioning can be effective in treating dynamic carpal instability, while the arthroscopic-assisted landmark setting can help identify the accurate location of the RSC and LRL ligaments without dissecting too much soft tissue.

Point-of-care Ultrasound Helps Differentiate the Causes of Unilateral Lower Limb Swelling with Rapid Progression: A Case Report with Literature Review.

Unilateral lower limb swelling is a common complaint among emergency department (ED) patients. However, an isolated intramuscular hematoma is an uncommon cause of lower limb swelling. We present a case of left thigh swelling after a traffic accident in which an intramuscular hematoma was diagnosed using point-of-care ultrasound. A literature review was also conducted.

Neuroprognostic Accuracy of Quantitative Versus Standard Pupillary Light Reflex for Adult Postcardiac Arrest Patients: A Systematic Review and Meta-Analysis.

OBJECTIVES: An automated infrared pupillometer measures quantitative pupillary light reflex using a calibrated light stimulus. We examined whether the timing of performing quantitative pupillary light reflex or standard pupillary light reflex may impact its neuroprognostic performance in postcardiac arrest comatose patients and whether quantitative pupillary light reflex may outperform standard pupillary light reflex in early postresuscitation phase. DATA SOURCES: PubMed and Embase databases from their inception to July 2020. STUDY SELECTION: We selected studies providing sufficient data of prognostic values of standard pupillary light reflex or quantitative pupillary light reflex to predict neurologic outcomes in adult postcardiac arrest comatose patients. DATA EXTRACTION: Quantitative data required for building a 2 × 2 contingency table were extracted, and study quality was assessed using standard criteria. DATA SYNTHESIS: We used the bivariate random-effects model to estimate the pooled sensitivity and specificity of standard pupillary light reflex or quantitative pupillary light reflex in predicting poor neurologic outcome during early (< 72 hr), middle (between 72 and 144 hr), and late (≧ 145 hr) postresuscitation periods, respectively. We included 39 studies involving 17,179 patients. For quantitative pupillary light reflex, the cut off points used in included studies to define absent pupillary light reflex ranged from 0% to 13% (median: 7%) and from zero to 2 (median: 2) for pupillary light reflex amplitude and Neurologic Pupil index, respectively. Late standard pupillary light reflex had the highest area under the receiver operating characteristic curve (0.98, 95% CI [CI], 0.97-0.99). For early standard pupillary light reflex, the area under the receiver operating characteristic curve was 0.80 (95% CI, 0.76-0.83), with a specificity of 0.91 (95% CI, 0.85-0.95). For early quantitative pupillary light reflex, the area under the receiver operating characteristic curve was 0.83 (95% CI, 0.79-0.86), with a specificity of 0.99 (95% CI, 0.91-1.00). CONCLUSIONS: Timing of pupillary light reflex examination may impact neuroprognostic accuracy. The highest prognostic performance was achieved with late standard pupillary light reflex. Early quantitative pupillary light reflex had a similar specificity to late standard pupillary light reflex and had better specificity than early standard pupillary light reflex. For postresuscitation comatose patients, early quantitative pupillary light reflex may substitute for early standard pupillary light reflex in the neurologic prognostication algorithm.

Early percutaneous cholecystostomy versus antibiotic treatment for mild and moderate acute cholecystitis: A retrospective cohort study.

BACKGROUND: Percutaneous cholecystostomy (PC) is an effective treatment for severe acute cholecystitis (AC). Guidelines recommend PC as rescue therapy for patients with mild or moderate AC who do not receive emergent cholecystectomy. This study aims to investigate whether PC could be a first-line treatment for these patients. METHODS: Adult patients admitted through the emergency department between October 2004 and December 2013 were retrospectively reviewed. Patients with mild or moderate AC who did not undergo emergent cholecystectomy were included. Early PC was defined as a PC tube inserted within 24 h of diagnosis. The outcomes were compared between patients who received antibiotics plus early PC (early PC group) and those who received antibiotic treatment alone (antibiotic group). RESULTS: A total of 698 patients were included. The mean age was 63.4 years. There were 171 patients in the early PC group and 527 patients in the antibiotic group. Multivariable logistic regression analyses indicated that early PC was significantly associated with a decreased rate of prolonged fever (odds ratio [OR], 0.31; 95% confidence interval [CI], 0.16-0.57; p < 0.001). Early PC also correlated with both increased short-term (OR, 15.95; 95% CI, 5.73-44.38; p < 0.001) and long-term treatment success (OR, 4.27; 95% CI, 2.55-7.15; p < 0.001). CONCLUSION: For patients with mild/moderate AC without emergent cholecystectomy, early PC might expedite sepsis resolution and improve the treatment success rate compared with antibiotic treatment alone. This result should be deemed as hypothesis-generating and should be examined in a randomized controlled trial.

Significance of the mass-compression effect of postlaminectomy/laminotomy fibrosis on histological changes on the dura mater and nerve root of the cauda equina: an experimental study in rats.

PURPOSE: The precise mechanism and pathological role of postlaminectomy/laminotomy fibrosis (PLF) in postoperative neurological deficits have not been established. Many studies use magnetic resonance imaging (MRI) to prove that there is no consistent correlation between PLF and postoperative neurological deficits and back pain (PNDBP). Therefore, we assumed that the direct-compression effect may not be the only factor but that other neurological deficits associated with pathological mechanisms should exist and need more investigation. The purpose of this study was to compare over time the differences and changes in histopathological properties of PLF in rats. METHODS: We used a rat model with walking-track analysis for neurologic evaluation, grading scale to evaluate PLF, histomorphometric measurements of dura sac diameter, and histological tissue reactions (dura mater and spinal rootlets) juxtaposed to the postlaminectomy/laminotomy defect. The 54 adult Sprague-Dawley rats were divided into laminotomy (n = 18), laminectomy (n = 18), and sham-operation groups (n = 18). All groups were subdivided into three equal subgroups based on different postoperative time points (1, 2, and 3 months). All sections of vertebral column were stained with hematoxylin and eosin and with Masson's trichrome. RESULTS: The results showed that only a slight compression effect reflected by nonsignificant changes in the maximum anterior-posterior diameters within the dura sac, in the walking tract test, and increased grades of PLF over time. In addition, significant pathological inflammatory changes, such as thickening of the dura mater, axonal swelling, and neovascularization, were found in the post-laminectomy/laminotomy groups at each time point. CONCLUSION: Laminectomy-/laminotomy-related inflammation may lead to PLF, and these pathological changes may be the main cause of postoperative neurological deficits. These findings show that research on preventing PLF should include perioperative modulation of inflammatory reactions induced by laminectomy/laminotomy.

Ultrasound-Guided Sciatic Nerve Hydrodissection Can Improve the Clinical Outcomes of Patients with Deep Gluteal Syndrome: A Case-Series Study.

Deep gluteal syndrome (DGS) is caused by sciatic nerve entrapment. Because fascial entrapment neuropathies may occur in multiple locations, ultrasound-guided nerve hydrodissection is a key component of DGS treatment. In this study, we examined the clinical outcomes of patients with DGS undergoing ultrasound-guided sciatic nerve hydrodissection. A 10 mL mixture consisting of 5% dextrose, 0.2% lidocaine (Xylocaine), and 4 mg betamethasone (Rinderon) was used for nerve hydrodissection. Clinical outcomes were evaluated using Numeric Rating Scale (NRS) scores of pain, the proportion of patients with favorable outcomes (reduction of ≥50% in pain), the duration for which patients exhibited favorable outcomes (percentage of follow-up duration), and the occurrence of major complications and minor side effects. A total of 53 patients were consecutively included and followed up for 3 to 19 months. After the initial injection, the NRS scores significantly improved at 1 week, 1 month, 3 months, and the final follow-up. Specifically, 73.6%, 71.7%, 64.2%, and 62.3% of the patients exhibited favorable outcomes at 1 week, 1 month, 3 months, and the final follow-up, respectively. The median duration for which the patients exhibited favorable outcomes was 84.7% of the follow-up period. Three patients (5.7%) experienced transient dizziness and vomiting, which resolved without further treatment. No vessel or nerve puncture was observed. Overall, ultrasound-guided sciatic nerve hydrodissection is a safe procedure that mitigates the pain associated with DGS. To achieve favorable outcomes, three consecutive injections 3 weeks apart are required.

Deep Learning-Based Localization and Detection of Malpositioned Nasogastric Tubes on Portable Supine Chest X-Rays in Intensive Care and Emergency Medicine: A Multi-center Retrospective Study.

Malposition of a nasogastric tube (NGT) can lead to severe complications. We aimed to develop a computer-aided detection (CAD) system to localize NGTs and detect NGT malposition on portable chest X-rays (CXRs). A total of 7378 portable CXRs were retrospectively retrieved from two hospitals between 2015 and 2020. All CXRs were annotated with pixel-level labels for NGT localization and image-level labels for NGT presence and malposition. In the CAD system, DeepLabv3 + with backbone ResNeSt50 and DenseNet121 served as the model architecture for segmentation and classification models, respectively. The CAD system was tested on images from chronologically different datasets (National Taiwan University Hospital (National Taiwan University Hospital)-20), geographically different datasets (National Taiwan University Hospital-Yunlin Branch (YB)), and the public CLiP dataset. For the segmentation model, the Dice coefficients indicated accurate delineation of the NGT course (National Taiwan University Hospital-20: 0.665, 95% confidence interval (CI) 0.630-0.696; National Taiwan University Hospital-Yunlin Branch: 0.646, 95% CI 0.614-0.678). The distance between the predicted and ground-truth NGT tips suggested accurate tip localization (National Taiwan University Hospital-20: 1.64 cm, 95% CI 0.99-2.41; National Taiwan University Hospital-Yunlin Branch: 2.83 cm, 95% CI 1.94-3.76). For the classification model, NGT presence was detected with high accuracy (area under the receiver operating characteristic curve (AUC): National Taiwan University Hospital-20: 0.998, 95% CI 0.995-1.000; National Taiwan University Hospital-Yunlin Branch: 0.998, 95% CI 0.995-1.000; CLiP dataset: 0.991, 95% CI 0.990-0.992). The CAD system also detected NGT malposition with high accuracy (AUC: National Taiwan University Hospital-20: 0.964, 95% CI 0.917-1.000; National Taiwan University Hospital-Yunlin Branch: 0.991, 95% CI 0.970-1.000) and detected abnormal nasoenteric tube positions with favorable performance (AUC: 0.839, 95% CI 0.807-0.869). The CAD system accurately localized NGTs and detected NGT malposition, demonstrating excellent potential for external generalizability.

Application of Machine Learning to Ultrasonography in Identifying Anatomical Landmarks for Cricothyroidotomy Among Female Adults: A Multi-center Prospective Observational Study.

We aimed to develop machine learning (ML)-based algorithms to assist physicians in ultrasound-guided localization of cricoid cartilage (CC) and thyroid cartilage (TC) in cricothyroidotomy. Adult female volunteers were prospectively recruited from two hospitals between September and December, 2020. Ultrasonographic images were collected via a modified longitudinal technique. You Only Look Once (YOLOv5s), Faster Regions with Convolutional Neural Network features (Faster R-CNN), and Single Shot Detector (SSD) were selected as the model architectures. A total of 488 women (mean age: 36.0 years) participated in the study, contributing to a total of 292,053 frames of ultrasonographic images. The derived ML-based algorithms demonstrated excellent discriminative performance for the presence of CC (area under the receiver operating characteristic curve [AUC]: YOLOv5s, 0.989, 95% confidence interval [CI]: 0.982-0.994; Faster R-CNN, 0.986, 95% CI: 0.980-0.991; SSD, 0.968, 95% CI: 0.956-0.977) and TC (AUC: YOLOv5s, 0.989, 95% CI: 0.977-0.997; Faster R-CNN, 0.981, 95% CI: 0.965-0.991; SSD, 0.982, 95% CI: 0.973-0.990). Furthermore, in the frames where the model could correctly indicate the presence of CC or TC, it also accurately localized CC (intersection-over-union: YOLOv5s, 0.753, 95% CI: 0.739-0.765; Faster R-CNN, 0.720, 95% CI: 0.709-0.732; SSD, 0.739, 95% CI: 0.726-0.751) or TC (intersection-over-union: YOLOv5s, 0.739, 95% CI: 0.722-0.755; Faster R-CNN, 0.709, 95% CI: 0.687-0.730; SSD, 0.713, 95% CI: 0.695-0.730). The ML-based algorithms could identify anatomical landmarks for cricothyroidotomy in adult females with favorable discriminative and localization performance. Further studies are warranted to transfer this algorithm to hand-held portable ultrasound devices for clinical use.

Prognostic Impact of Heart Rhythm Shockability Trajectory in Out-of-Hospital Cardiac Arrest: A Multicenter Retrospective Study.

BACKGROUND: This study aimed to investigate the association between the temporal transitions in heart rhythms during cardiopulmonary resuscitation (CPR) and outcomes after out-of-hospital cardiac arrest. METHODS: This was an analysis of the prospectively collected databases in 3 academic hospitals in northern and central Taiwan. Adult patients with out-of-hospital cardiac arrest transported by emergency medical service between 2015 and 2022 were included. Favorable neurological recovery and survival to hospital discharge were the primary and secondary outcomes, respectively. Time-specific heart rhythm shockability was defined as the probability of shockable rhythms at a particular time point during CPR. The temporal changes in the time-specific heart rhythm shockability were calculated by group-based trajectory modeling. Multivariable logistic regression analyses were performed to examine the association between the trajectory group and outcomes. Subgroup analyses examined the effects of extracorporeal CPR in different trajectories. RESULTS: The study comprised 2118 patients. The median patient age was 69.1 years, and 1376 (65.0%) patients were male. Three distinct trajectories were identified: high-shockability (52 patients; 2.5%), intermediate-shockability (262 patients; 12.4%), and low-shockability (1804 patients; 85.2%) trajectories. The median proportion of shockable rhythms over the course of CPR for the 3 trajectories was 81.7% (interquartile range, 73.2%-100.0%), 26.7% (interquartile range, 16.7%-37.5%), and 0% (interquartile range, 0%-0%), respectively. The multivariable analysis indicated both intermediate- and high-shockability trajectories were associated with favorable neurological recovery (intermediate-shockability: adjusted odds ratio [aOR], 4.98 [95% CI, 2.34-10.59]; high-shockability: aOR, 5.40 [95% CI, 2.03-14.32]) and survival (intermediate-shockability: aOR, 2.46 [95% CI, 1.44-4.18]; high-shockability: aOR, 2.76 [95% CI, 1.20-6.38]). The subgroup analysis further indicated extracorporeal CPR was significantly associated with favorable neurological outcomes (aOR, 4.06 [95% CI, 1.11-14.81]) only in the intermediate-shockability trajectory. CONCLUSIONS: Heart rhythm shockability trajectories were associated with out-of-hospital cardiac arrest outcomes, which may be a supplementary factor in guiding the allocation of medical resources, such as extracorporeal CPR.

End-tidal Carbon Dioxide Trajectory-based Prognostication of Out-of-hospital Cardiac Arrest.

Background: During cardiopulmonary resuscitation (CPR), end-tidal carbon dioxide (EtCO2) is primarily determined by pulmonary blood flow, thereby reflecting the blood flow generated by CPR. We aimed to develop an EtCO2 trajectory-based prediction model for prognostication at specific time points during CPR in patients with out-of-hospital cardiac arrest (OHCA). Methods: We screened patients receiving CPR between 2015-2021 from a prospectively collected database of a tertiary-care medical center. The primary outcome was survival to hospital discharge. We used group-based trajectory modeling to identify the EtCO2 trajectories. Multivariable logistic regression analysis was used for model development and internally validated using bootstrapping. We assessed performance of the model using the area under the receiver operating characteristic curve (AUC). Results: The primary analysis included 542 patients with a median age of 68.0 years. Three distinct EtCO2 trajectories were identified in patients resuscitated for 20 minutes (min): low (average EtCO2 10.0 millimeters of mercury [mm Hg]; intermediate (average EtCO2 26.5 mm Hg); and high (average EtCO2: 51.5 mm Hg). Twenty-min EtCO2 trajectory was fitted as an ordinal variable (low, intermediate, and high) and positively associated with survival (odds ratio 2.25, 95% confidence interval [CI] 1.07-4.74). When the 20-min EtCO2 trajectory was combined with other variables, including arrest location and arrest rhythms, the AUC of the 20-min prediction model for survival was 0.89 (95% CI 0.86-0.92). All predictors in the 20-min model remained statistically significant after bootstrapping. Conclusion: Time-specific EtCO2 trajectory was a significant predictor of OHCA outcomes, which could be combined with other baseline variables for intra-arrest prognostication. For this purpose, the 20-min survival model achieved excellent discriminative performance in predicting survival to hospital discharge.

Prognostic implication of heart failure stage and left ventricular ejection fraction for patients with in-hospital cardiac arrest: a 16-year retrospective cohort study.

BACKGROUND: The 2022 AHA/ACC/HFSA guidelines for the management of heart failure (HF) makes therapeutic recommendations based on HF status. We investigated whether the prognosis of in-hospital cardiac arrest (IHCA) could be stratified by HF stage and left ventricular ejection fraction (LVEF). METHODS: This single-center retrospective study analyzed the data of patients who experienced IHCA between 2005 and 2020. Based on admission diagnosis, past medical records, and pre-arrest echocardiography, patients were classified into general IHCA, at-risk for HF, pre-HF, HF with preserved ejection fraction (HFpEF), and HF with mildly reduced ejection fraction or HF with reduced ejection fraction (HFmrEF-or-HFrEF) groups. RESULTS: This study included 2,466 patients, including 485 (19.7%), 546 (22.1%), 863 (35.0%), 342 (13.9%), and 230 (9.3%) patients with general IHCA, at-risk for HF, pre-HF, HFpEF, and HFmrEF-or-HFrEF, respectively. A total of 405 (16.4%) patients survived to hospital discharge, with 228 (9.2%) patients achieving favorable neurological recovery. Multivariable logistic regression analysis indicated that pre-HF and HFpEF were associated with better neurological (pre-HF, OR: 2.11, 95% confidence interval [CI]: 1.23-3.61, p = 0.006; HFpEF, OR: 1.90, 95% CI: 1.00-3.61, p = 0.05) and survival outcomes (pre-HF, OR: 2.00, 95% CI: 1.34-2.97, p < 0.001; HFpEF, OR: 1.91, 95% CI: 1.20-3.05, p = 0.007), compared with general IHCA. CONCLUSION: HF stage and LVEF could stratify patients with IHCA into different prognoses. Pre-HF and HFpEF were significantly associated with favorable neurological and survival outcomes after IHCA. Further studies are warranted to investigate whether HF status-directed management could improve IHCA outcomes.

Deep Learning-based Diagnosis of Pulmonary Tuberculosis on Chest X-ray in the Emergency Department: A Retrospective Study.

Prompt and correct detection of pulmonary tuberculosis (PTB) is critical in preventing its spread. We aimed to develop a deep learning-based algorithm for detecting PTB on chest X-ray (CXRs) in the emergency department. This retrospective study included 3498 CXRs acquired from the National Taiwan University Hospital (NTUH). The images were chronologically split into a training dataset, NTUH-1519 (images acquired during the years 2015 to 2019; n = 2144), and a testing dataset, NTUH-20 (images acquired during the year 2020; n = 1354). Public databases, including the NIH ChestX-ray14 dataset (model training; 112,120 images), Montgomery County (model testing; 138 images), and Shenzhen (model testing; 662 images), were also used in model development. EfficientNetV2 was the basic architecture of the algorithm. Images from ChestX-ray14 were employed for pseudo-labelling to perform semi-supervised learning. The algorithm demonstrated excellent performance in detecting PTB (area under the receiver operating characteristic curve [AUC] 0.878, 95% confidence interval [CI] 0.854-0.900) in NTUH-20. The algorithm showed significantly better performance in posterior-anterior (PA) CXR (AUC 0.940, 95% CI 0.912-0.965, p-value < 0.001) compared with anterior-posterior (AUC 0.782, 95% CI 0.644-0.897) or portable anterior-posterior (AUC 0.869, 95% CI 0.814-0.918) CXR. The algorithm accurately detected cases of bacteriologically confirmed PTB (AUC 0.854, 95% CI 0.823-0.883). Finally, the algorithm tested favourably in Montgomery County (AUC 0.838, 95% CI 0.765-0.904) and Shenzhen (AUC 0.806, 95% CI 0.771-0.839). A deep learning-based algorithm could detect PTB on CXR with excellent performance, which may help shorten the interval between detection and airborne isolation for patients with PTB.

Biphasic versus monophasic defibrillation in out-of-hospital cardiac arrest: a systematic review and meta-analysis.

OBJECTIVE: Biphasic defibrillation is more effective than monophasic one in controlled in-hospital conditions. The present review evaluated the performance of both waveforms in the defibrillation of patients of out-of-hospital cardiac arrest (OHCA) with initial ventricular fibrillation (Vf) rhythm under the context of current recommendations for cardiopulmonary resuscitation. METHODS: From inception to June 2012, Medline, Embase, and the Cochrane Central Register of Controlled Trials were searched systemically for randomized controlled trials (RCTs) and observational cohort studies that compared the effects of biphasic and monophasic shocks on Vf termination, return of spontaneous circulation (ROSC), and survival to hospital discharge in OHCA patients with initial Vf rhythm. No restrictions were applied regarding language, population, or publication year. RESULTS: Four RCTs including 572 patients were identified from 131 potentially relevant references for meta-analysis. The synthesis of these RCTs yielded fixed-effect pooled risk ratios (RRs) for biphasic and monophasic waveforms on Vf termination survival to hospital discharge (RR, 1.14; 95% CI, [0.84-1.54]). CONCLUSION: Biphasic waveforms did not seem superior to monophasic ones with respect to Vf termination, ROSC, or survival to hospital discharge in OHCA patients with initial Vf rhythm under the context of current guidelines. However, most trials were conducted in accordance with previous guidelines for cardiopulmonary resuscitation. Therefore, further trials are needed to clarify this issue.

[Silencing hypoxia inducible factor-2α gene by small interference RNA inhibits the growth of mammosphere cells in nude mice under hypoxic microenvironment].

OBJECTIVE: To explore the effects of silencing hypoxia inducible factor-2α (HIF-2α) by small interference RNA on the growth of mammosphere cells in nude mice under hypoxic microenvironment. METHODS: The empty and interference vectors were transfected into MCF-7 cell. Then G418 was added to screen the positive cells to obtain stable cell line. The empty and interference vectors were inoculated subcutaneously into left and right back near hind limb of nude mice. The volume and weight of tumors were calculated respectively. The expressions of HIF-2α, CD44, OCT-4 and KLF-4 protein in xenograft tumor tissues were detected by Western blot. RESULTS: The expression vector of HIF-2α-siRNA was successfully established. The formation of mammosphere was lowered by silencing HIF-2α gene expression. In contract to empty vector group cell, there were obvious decreases in the volumes and weights of tumors in interference group (P < 0.05). The expression of HIF-2α protein of interference group (0.42 ± 0.01) was much lower than that of the empty vector group (0.89 ± 0.03, P < 0.05), the expression of CD44 protein of interference group (0.21 ± 0.01) was much lower than the empty vector group (0.78 ± 0.03, P < 0.05), the expression of OCT-4 protein of interference group (0.42 ± 0.01)was much lower than the empty vector group (0.68 ± 0.03, P < 0.05) and the expression of KLF-4 protein of interference group (0.34 ± 0.01) was much lower than the empty vector group (0.72 ± 0.03, P < 0.05). CONCLUSION: Silencing HIF-2α gene can effectively inhibit the growth of breast cancer stem cells in nude mice under hypoxic microenvironment. Its mechanism may be through inhibited capacity for self-renewal and proliferation of breast cancer stem cells in vivo through the down-regulated expressions of markers associated with stem cells. HIF-2α is expected to become a new target for gene therapy of breast cancer.

[Expression of breast cancer resistance protein and p-glycoprotein in residual breast cancer tissue after chemotherapy and its correlation with cancer stem cells].

OBJECTIVE: To compare the expression differences of breast cancer resistance protein(BCRP/ABCG2) and P-glycoprotein(P-gp) in breast cancer tissue before chemotherapy and in residual breast cancer tissue, and to explore its correlation with breast cancer stem cells. METHODS: Immunohistochemistry was used to detect the expression of ABCG2, P-gp, and breast cancer stem cells(BCSCs) markers(CD44 and CD24) in breast cancer tissue before chemotherapy and residual breast cancer tissue after chemotherapy. Immunofluorescence was applied for determination of the CD44 and CD24 protein expressions of BCSCs microspheres cells. The monoclone-forming ability of BCSCs microspheres cells was detected by limited dilution assay. The expressions of ABCG2, P-gp, CD44, and CD24 proteins were detected by Western blot. RESULTS: Compared with those in breast cancer tissue before chemotherapy, the expression levels of ABCG2 and P-gp were positively correlated with the expression level of CD44 protein(Χ(2)=41.34, r=0.83;Χ(2)=22.81, r=0.61) in residual breast cancer tissue after chemotherapy;meanwhile, they were negatively correlated with the expression of CD24 protein(Χ(2)=-21.25, r=0.72;Χ(2)=-17.26, r=0.65) (all P<0.05) .The diameter of BCSCs microspheres were increased significantly after chemotherapy.The content of BCSCs increased by about 2.5 times after chemotherapy.The expressions of ABCG2, P-gp and CD44 proteins significantly increased and that of CD24 protein significantly declined(P<0.05) . CONCLUSION: Chemotherapy endows residual breast cancer tissue with cancer stem cells-like features, leading to multidrug resistance of breast cancer.

Utilizing a nomogram to predict the one-year postoperative mortality risk for geriatric patients with a hip fracture.

Despite the abundance of research on the risk factors for mortality following hip fracture surgery, there has been a dearth of studies on prediction models in this population. The objective of this research was to explore the influencing factors and construct a clinical nomogram to predict one-year postoperative mortality in patients with hip fracture surgeries. Using the Ditmanson Research Database (DRD), we included 2333 subjects, aged ≥ 50 years who underwent hip fracture surgery between October, 2008 and August, 2021. The endpoint was all-cause mortality. A least absolute shrinkage and selection operator (LASSO) derived Cox regression was performed to select the independent predictors of one-year postoperative mortality. A nomogram was built for predicting one-year postoperative mortality. The prognostic performance of nomogram was evaluated. On the basis of tertiary points in a nomogram, the patients were divided into low, middle and high risk groups, and compared by the Kaplan-Meier analysis. Within 1 year after hip fracture surgery, 274 patients (11.74%) died. Variables retained in the final model comprised age, sex, length of stay, RBC transfusions, hemoglobin, platelet, and eGFR. The AUC for one-year mortality predictions were 0.717 (95% CI = 0.685-0.749). The Kaplan-Meier curves were significantly different among the three risk groups (p < 0.001). The nomogram showed good calibration. In summary, we explored the one-year postoperative mortality risk in geriatric patients with a hip fracture and developed a prediction model that could help clinicians identify patients at high risk of postoperative mortality.