Vitamin D deficiency as a risk factor for sudden cardiac arrest: A multicenter case-control study.

BACKGROUND AND AIMS: Vitamin D is known to influence the risk of cardiovascular disease, which is a recognized risk factor for sudden cardiac arrest (SCA). However, the relationship between vitamin D and SCA is not well understood. Therefore, this study aims to investigate the association between vitamin D and SCA in out-of-hospital cardiac arrest (OHCA) patients compared to healthy controls. METHODS AND RESULTS: Using the Phase II Cardiac Arrest Pursuit Trial with Unique Registration and Epidemiologic Surveillance (CAPTURES II) registry, a 1:1 propensity score-matched case-control study was conducted between 2017 and 2020. Serum 25-hydroxyvitamin D (vitamin D) levels in patients with OHCA (454 cases) and healthy controls (454 cases) were compared after matching for age, sex, cardiovascular risk factors, and lifestyle behaviors. The mean vitamin D levels were 14.5 ± 7.6 and 21.3 ± 8.3 ng/mL among SCA cases and controls, respectively. Logistic regression analysis was used adjusting for cardiovascular risk factors, lifestyle behaviors, corrected serum calcium levels, and estimated glomerular filtration rate (eGRF). The adjusted odds ratio (aOR) for vitamin D was 0.89 (95% confidence interval [CI] 0.87-0.91). The dose-response relationship demonstrated that vitamin D deficiency was associated with SCA incidence (severe deficiency, aOR 10.87, 95% CI 4.82-24.54; moderate deficiency, aOR 2.24, 95% CI 1.20-4.20). CONCLUSION: Vitamin D deficiency was independently and strongly associated with an increased risk of SCA, irrespective of cardiovascular and lifestyle factors, corrected calcium levels, and eGFR.

Circulating mitochondrial N-formyl peptides contribute to secondary nosocomial infection in patients with septic shock.

Secondary infections typically worsen outcomes of patients recovering from septic shock. Neutrophil [polymorphonuclear leukocytes (PMNs)] migration to secondarily inoculated sites may play a key role in inhibiting progression from local bacterial inoculation to secondary infection. Mitochondrial N-formyl peptide (mtFP) occupancy of formyl peptide receptor-1 (FPR1) has been shown to suppress PMN chemotaxis. Therefore, we studied the association between circulating mtFPs and the development of secondary infection in patients with septic shock. We collected clinical data and plasma samples from patients with septic shock admitted to the intensive care unit for longer than 72 h. Impacts of circulating nicotinamide adenine dinucleotide dehydrogenase subunit-6 (ND6) upon clinical outcomes were analyzed. Next, the role of ND6 in PMN chemotaxis was investigated using isolated human PMNs. Studying plasma samples from 97 patients with septic shock, we found that circulating ND6 levels at admission were independently and highly associated with the development of secondary infection (odds ratio = 30.317, 95% CI: 2.904 to 316.407, P = 0.004) and increased 90-d mortality (odds ratio = 1.572, 95% CI: 1.002 to 2.465, P = 0.049). In ex vivo experiments, ND6 pretreatment suppressed FPR1-mediated PMN chemotactic responses to bacterial peptides in the presence of multiple cytokines and chemokines, despite increased nondirectional PMN movements. Circulating mtFPs appear to contribute to the development of secondary infection and increased mortality in patients with septic shock who survive their early hyperinflammatory phase. The increased susceptibility to secondary infection is probably partly mediated by the suppression of FPR1-mediated PMN chemotaxis to secondary infected sites.

Delayed arrival of advanced life support adversely affects the neurological outcome in a multi-tier emergency response system.

AIM: Prehospital management of out-of-hospital cardiac arrest (OHCA) is based on basic life support, with the addition of advanced life support (ALS) if possible. This study aimed to investigate the effect of delayed arrival of ALS on neurological outcomes of patients with OHCA at hospital discharge. METHODS: This was a retrospective study of a registry of patients with OHCA. A multi-tier emergency response system was established in the study area. ALS was initiated when the second-arrival team arrived at the scene. A restricted cubic spline curve was used to investigate the relationship between the response time interval of the second-arrival team and neurological outcomes at hospital discharge. Multivariable logistic regression analysis was performed to assess the independent association between the response time interval of the second-arrival team and neurological outcomes of patients at hospital discharge. RESULTS: A total of 3186 adult OHCA patients who received ALS at the scene were included in the final analysis. A restricted cubic spline curve showed that a long response time interval of the second-arrival team was correlated with a high likelihood of poor neurological outcomes. Meanwhile, multivariable logistic regression analysis showed that a long response time interval of the second-arrival team was independently associated with poor neurological outcomes (odds ratio, 1.10; 95% confidence interval, 1.03-1.17). CONCLUSION: In a multi-tiered prehospital emergency response system, the delayed arrival of ALS was associated with poor neurological outcomes at hospital discharge.

Impact of an Emergency Department Isolation Policy for Patients With Suspected COVID-19 on Door-to-Electrocardiography Time and Clinical Outcomes in Patients With Acute Myocardial Infarction.

BACKGROUND: Rapid electrocardiography diagnosis within 10 minutes of presentation is critical for acute myocardial infarction (AMI) patients in the emergency department (ED). However, the coronavirus disease 2019 (COVID-19) pandemic has significantly impacted the emergency care system. Screening for COVID-19 symptoms and implementing isolation policies in EDs may delay the door-to-electrocardiography (DTE) time. METHODS: We conducted a cross-sectional study of 1,458 AMI patients who presented to a single ED in South Korea from January 2019 to December 2021. We used multivariate logistic regression analysis to assess the impact of COVID-19 pandemic and ED isolation policies on DTE time and clinical outcomes. RESULTS: We found that the mean DTE time increased significantly from 5.5 to 11.9 minutes (P < 0.01) in ST segment elevation myocardial infarction (STEMI) patients and 22.3 to 26.7 minutes (P < 0.01) in non-ST segment elevation myocardial infarction (NSTEMI) patients. Isolated patients had a longer mean DTE time compared to non-isolated patients in both STEMI (9.2 vs. 24.4 minutes) and NSTEMI (22.4 vs. 61.7 minutes) groups (P < 0.01). The adjusted odds ratio (aOR) for the effect of COVID-19 duration on DTE ≥ 10 minutes was 1.93 (95% confidence interval [CI], 1.51-2.47), and the aOR for isolation status was 5.62 (95% CI, 3.54-8.93) in all patients. We did not find a significant association between in-hospital mortality and the duration of COVID-19 (aOR, 0.9; 95% CI, 0.52-1.56) or isolation status (aOR, 1.62; 95% CI, 0.71-3.68). CONCLUSION: Our study showed that ED screening or isolation policies in response to the COVID-19 pandemic could lead to delays in DTE time. Timely evaluation and treatment of emergency patients during pandemics are essential to prevent potential delays that may impact their clinical outcomes.

Recent Trends in Lateral Flow Immunoassays with Optical Nanoparticles.

Rapid, accurate, and convenient diagnosis is essential for effective disease management. Various detection methods, such as enzyme-linked immunosorbent assay, have been extensively used, with lateral flow immunoassay (LFIA) recently emerging as a major diagnostic tool. Nanoparticles (NPs) with characteristic optical properties are used as probes for LFIA, and researchers have presented various types of optical NPs with modified optical properties. Herein, we review the literature on LFIA with optical NPs for the detection of specific targets in the context of diagnostics.

Effects of Smart Advanced Life Support protocol implementation including CPR coaching during out-of-hospital cardiac arrest.

PURPOSE: The aim of this study was to compare out-of-hospital cardiac arrest (OHCA) outcomes before and after implementation of Smart Advanced Life Support (SALS) protocol incorporating changes in cardiopulmonary resuscitation (CPR) assistance and coaching by physicians via real-time video calls. METHODS: A prospective before-and-after multi-regional observational study was conducted between January 2014 and December 2018. In January 2016, emergency medical service (EMS) providers adopted an integrated CPR coaching by physicians via real-time video call via SALS to treat patients with OHCA focusing on high-quality cardiopulmonary resuscitation. Propensity score matching was performed to match patients. Patients' outcomes using conventional protocol were then compared with those of patients using the SALS protocol. RESULTS: Among 26,349 OHCA cases, 2351 patients and 7261 patients were enrolled during the pre-intervention and the post-intervention periods, respectively. Multivariate analysis showed that SALS was independently associated with favorable neurological outcomes [odds ratio (OR): 2.20; 95% confidence interval (CI): 1.62-2.99]. A total of 2096 patients were propensity score-matched and the two groups were well balanced. In the matched cohort, the use of SALS protocol was still associated with increased prehospital return of spontaneous circulation (ROSC) (OR: 3.83, 95% CI: 2.80-5.26), survival to discharge (OR: 1.68; 95% CI: 1.20-2.34), and favorable neurological outcomes (OR: 1.83; 95% CI: 1.19-2.82). CONCLUSION: A multidisciplinary SALS protocol for the resuscitation of patients with OHCA was associated with increased prehospital ROSC, survival to discharge, and good neurologic outcomes compared with traditional resuscitation protocol.

Overlimiting Current in Nonuniform Arrays of Microchannels: Recirculating Flow and Anticrystallization.

Overlimiting current (OLC) through electrolytes interfaced with perm-selective membranes has been extensively researched for understanding fundamental nano-electrokinetics and developing efficient engineering applications. This work studies how a network of microchannels in a nonuniform array, which mimics a natural pore configuration, can contribute to OLC. Here, micro/nanofluidic devices are fabricated with arrays of parallel microchannels with nonuniform size distributions, which are faced with a perm-selective membrane. All cases maintain the same surface and bulk conduction to allow probing of the sensitivity only by the nonuniformity. Rigorous experimental and theoretical investigation demonstrates that overlimiting conductance has a maximum value depending on the nonuniformity. Furthermore, in operando visualization reveals that the nonuniform arrays induce flow loops across the microchannel network enhancing advective transport. This recirculating flow eliminates local salt accumulations so that it can effectively suppress undesirable salt crystallization. Therefore, these results can significantly advance not only the fundamental understanding of the driving mechanism of the OLC but also the design rule of electrochemical membrane applications.

Highly Bright Silica-Coated InP/ZnS Quantum Dot-Embedded Silica Nanoparticles as Biocompatible Nanoprobes.

Quantum dots (QDs) have outstanding optical properties such as strong fluorescence, excellent photostability, broad absorption spectra, and narrow emission bands, which make them useful for bioimaging. However, cadmium (Cd)-based QDs, which have been widely studied, have potential toxicity problems. Cd-free QDs have also been studied, but their weak photoluminescence (PL) intensity makes their practical use in bioimaging challenging. In this study, Cd-free QD nanoprobes for bioimaging were fabricated by densely embedding multiple indium phosphide/zinc sulfide (InP/ZnS) QDs onto silica templates and coating them with a silica shell. The fabricated silica-coated InP/ZnS QD-embedded silica nanoparticles (SiO2@InP QDs@SiO2 NPs) exhibited hydrophilic properties because of the surface silica shell. The quantum yield (QY), maximum emission peak wavelength, and full-width half-maximum (FWHM) of the final fabricated SiO2@InP QDs@SiO2 NPs were 6.61%, 527.01 nm, and 44.62 nm, respectively. Moreover, the brightness of the particles could be easily controlled by adjusting the amount of InP/ZnS QDs in the SiO2@InP QDs@SiO2 NPs. When SiO2@InP QDs@SiO2 NPs were administered to tumor syngeneic mice, the fluorescence signal was prominently detected in the tumor because of the preferential distribution of the SiO2@InP QDs@SiO2 NPs, demonstrating their applicability in bioimaging with NPs. Thus, SiO2@InP QDs@SiO2 NPs have the potential to successfully replace Cd-based QDs as highly bright and biocompatible fluorescent nanoprobes.

Giant Magnetoresistive Nanosensor Analysis of Circulating Tumor DNA Epidermal Growth Factor Receptor Mutations for Diagnosis and Therapy Response Monitoring.

BACKGROUND: Liquid biopsy circulating tumor DNA (ctDNA) mutational analysis holds great promises for precision medicine targeted therapy and more effective cancer management. However, its wide adoption is hampered by high cost and long turnaround time of sequencing assays, or by inadequate analytical sensitivity of existing portable nucleic acid tests to mutant allelic fraction in ctDNA. METHODS: We developed a ctDNA Epidermal Growth Factor Receptor (EGFR) mutational assay using giant magnetoresistive (GMR) nanosensors. This assay was validated in 36 plasma samples of non-small cell lung cancer patients with known EGFR mutations. We assessed therapy response through follow-up blood draws, determined concordance between the GMR assay and radiographic response, and ascertained progression-free survival of patients. RESULTS: The GMR assay achieved analytical sensitivities of 0.01% mutant allelic fraction. In clinical samples, the assay had 87.5% sensitivity (95% CI = 64.0-97.8%) for Exon19 deletion and 90% sensitivity (95% CI = 69.9-98.2%) for L858R mutation with 100% specificity; our assay detected T790M resistance with 96.3% specificity (95% CI = 81.7-99.8%) with 100% sensitivity. After 2 weeks of therapy, 10 patients showed disappearance of ctDNA by GMR (predicted responders), whereas 3 patients did not (predicted nonresponders). These predictions were 100% concordant with radiographic response. Kaplan-Meier analysis showed responders had significantly (P < 0.0001) longer PFS compared to nonresponders (N/A vs. 12 weeks, respectively). CONCLUSIONS: The GMR assay has high diagnostic sensitivity and specificity and is well suited for detecting EGFR mutations at diagnosis and noninvasively monitoring treatment response at the point-of-care.

Association between length of stay in the emergency department and outcomes in out-of-hospital cardiac arrest.

OBJECTIVE: Several studies have previously reported that a prolonged emergency department length of stay (EDLOS) is associated with poor outcomes in critically ill patients. This study was performed to investigate the relationship between the EDLOS and the neurologic outcome at 28 days in out-of-hospital cardiac arrest (OHCA) patients. METHODS: We conducted a retrospective analysis of prospectively collected data from OHCA patients who achieved the return of spontaneous circulation (ROSC) in the EDs of three urban tertiary teaching hospitals from December 2013 to October 2020. Patients were divided into four groups according to the EDLOS, according to the quartile distribution: EDLOS <107 min, EDLOS 107-176 min, EDLOS 176-275 min, and EDLOS ≥275 min. Comparisons of outcomes among the groups and multivariable logistic regression analysis were performed. RESULTS: A total of 807 patients were included in the analysis. The proportions of patients with a good neurologic outcome at 28 days in the groups with EDLOS <107 min, EDLOS 107-176 min, EDLOS 176-275 min, and EDLOS ≥275 min were 37.0%, 29.8%, 26.9, and 20.4%, respectively (p < 0.001). In the multivariable analysis, the odds ratios for a poor neurologic outcome at 28 days in the groups with EDLOS 107-176 min, EDLOS 176-275 min, and EDLOS ≥275 min compared with the group with EDLOS <107 min were 1.19 (95% CI, 0.67-2.13), 1.73 (95% CI, 0.95-3.21), and 1.91 (95% CI, 1.03-3.57), respectively. CONCLUSIONS: An EDLOS longer than 275 min after the ROSC was independently associated with a poor neurologic outcome at 28 days.

Association of the duration of on-scene advanced life support with good neurological recovery in out-of-hospital cardiac arrest.

BACKGROUND: As advanced life support (ALS) provided by emergency medical services (EMS) on scene becomes more common, the scene time interval (STI) for which EMS providers stay on scene tends to lengthen. We investigated the relationship between the STI and neurological outcome of patients at hospital discharge when ALS was provided by EMS on scene. METHODS: We conducted a retrospective analysis of prospectively collected out-of-hospital cardiac arrest (OHCA) data between August 2015 and December 2018. A restricted cubic spline curve was used to investigate the relationship between the STI and neurologic outcome, and patients were divided into two groups based on the cut-off value obtained through receiver operating characteristic (ROC) analysis. Comparisons of outcomes between the two groups were performed before and after propensity score matching. RESULTS: 4548 patients were included in the analysis. In ROC analysis, the optimal cut-off value for STI was 19 min. For the group with an STI <19 min, survival admission, survival discharge, and good neurologic outcome at hospital discharge were all higher than for the group with STI ≥19 min before and after propensity score matching. The multivariable model also showed that the STI ≥19 min was significantly associated with poor neurologic outcome at hospital discharge compared with the STI <19 min (adjusted odds ratio, 2.00; 95% CI, 1.40-2.88). CONCLUSIONS: A duration of on-scene ALS more than 19 min was associated with a poor neurologic outcome of patients at hospital discharge in OHCA.

The index of oxygenation to respiratory rate as a prognostic factor for mortality in Sepsis.

OBJECTIVES: An index combining respiratory rate and oxygenation (ROX) has been introduced, and the ROX index is defined as the ratio of oxygen saturation by pulse oximetry/fraction of inspired oxygen to respiratory rate. In sepsis, hypoxemia and tachypnea are commonly observed. We performed this study to investigate the association between the ROX index and 28-day mortality in patients with sepsis or septic shock. METHODS: This retrospective study included 2862 patients. The patients were divided into three groups according to the ROX index: Group I (ROX index >20), Group II (ROX index >10 and ≤ 20), and Group III (ROX index ≤10). RESULTS: The median ROX index was significantly lower in the nonsurvivors than in the survivors (12.8 and 18.2, respectively) (p < 0.001). The 28-day mortality rates in Groups I, II and III were 14.5%, 21.3% and 34.4%, respectively (p < 0.001). In the multivariable Cox regression analysis, Group III had an approximately 40% higher risk of death than Group I during the 28-day period (hazard ratio = 1.41, 95% confidence interval 1.13-1.76). The area under the curve of the ROX index was significantly higher than that of the quick Sequential Organ Failure Assessment score (p < 0.001). CONCLUSIONS: The ROX index was lower in nonsurvivors than in survivors, and a ROX index less than or equal to 10 was an independent prognostic factor for 28-day mortality in patients with sepsis or septic shock. Therefore, the ROX index could be used as a prognostic marker in sepsis.

Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models.

BACKGROUND: We performed this study to establish a prediction model for 1-year neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients who achieved return of spontaneous circulation (ROSC) immediately after ROSC using machine learning methods. METHODS: We performed a retrospective analysis of an OHCA survivor registry. Patients aged ≥ 18 years were included. Study participants who had registered between March 31, 2013 and December 31, 2018 were divided into a develop dataset (80% of total) and an internal validation dataset (20% of total), and those who had registered between January 1, 2019 and December 31, 2019 were assigned to an external validation dataset. Four machine learning methods, including random forest, support vector machine, ElasticNet and extreme gradient boost, were implemented to establish prediction models with the develop dataset, and the ensemble technique was used to build the final prediction model. The prediction performance of the model in the internal validation and the external validation dataset was described with accuracy, area under the receiver-operating characteristic curve, area under the precision-recall curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Futhermore, we established multivariable logistic regression models with the develop set and compared prediction performance with the ensemble models. The primary outcome was an unfavorable 1-year neurological outcome. RESULTS: A total of 1,207 patients were included in the study. Among them, 631, 139, and 153 were assigned to the develop, the internal validation and the external validation datasets, respectively. Prediction performance metrics for the ensemble prediction model in the internal validation dataset were as follows: accuracy, 0.9620 (95% confidence interval [CI], 0.9352-0.9889); area under receiver-operator characteristics curve, 0.9800 (95% CI, 0.9612-0.9988); area under precision-recall curve, 0.9950 (95% CI, 0.9860-1.0000); sensitivity, 0.9594 (95% CI, 0.9245-0.9943); specificity, 0.9714 (95% CI, 0.9162-1.0000); PPV, 0.9916 (95% CI, 0.9752-1.0000); NPV, 0.8718 (95% CI, 0.7669-0.9767). Prediction performance metrics for the model in the external validation dataset were as follows: accuracy, 0.8509 (95% CI, 0.7825-0.9192); area under receiver-operator characteristics curve, 0.9301 (95% CI, 0.8845-0.9756); area under precision-recall curve, 0.9476 (95% CI, 0.9087-0.9867); sensitivity, 0.9595 (95% CI, 0.9145-1.0000); specificity, 0.6500 (95% CI, 0.5022-0.7978); PPV, 0.8353 (95% CI, 0.7564-0.9142); NPV, 0.8966 (95% CI, 0.7857-1.0000). All the prediction metrics were higher in the ensemble models, except NPVs in both the internal and the external validation datasets. CONCLUSION: We established an ensemble prediction model for prediction of unfavorable 1-year neurological outcomes in OHCA survivors using four machine learning methods. The prediction performance of the ensemble model was higher than the multivariable logistic regression model, while its performance was slightly decreased in the external validation dataset.

Analysis of Factors Affecting Emergency Physicians' Attitudes toward Deceased Organ & Tissue Donation.

BACKGROUND: This study aimed to investigate differences in knowledge, and attitudes toward deceased organ and tissue donation of emergency physicians. Additionally, we analyzed factors affecting the attitudes toward deceased organ and tissue donation. METHODS: We conducted a survey of specialists and residents registered with the Korean Society of Emergency Medicine in December 2020. The respondents' sex, age, position, personal registration for organ donation, experience of soliciting organ donation, participation in related education, knowledge, and attitude about brain death organ donation, and attitude toward stopping life-sustaining treatments were investigated. According to the characteristics of the respondents (specialists or residents, experience and education on organ and tissue donation), their knowledge and attitude toward deceased organ donation were compared. Stepwise hierarchical multiple regression analysis was used to investigate the factors affecting the attitudes toward deceased organ and tissue donation. RESULTS: Of the total 428 respondents, there were 292 emergency medicine specialists and 136 medical residents. Specialists and those who registered or wished to donate organs had higher knowledge and attitude scores regarding deceased organ and tissue donation. Those who had experience recommending organ and tissue donation more than 6 times had higher knowledge scores on deceased organ and tissue donation and higher overall scores in attitude. Those who received education from the Korean Organ Donation Agency had higher knowledge scores. Specialists, and those who wished to donate or had registered as organ donors and had a higher life-sustaining treatment attitude score and knowledge about deceased organ and tissue donation, had more positive attitudes toward deceased organ and tissue donation. CONCLUSION: For more potential deceased organ and tissue donors to be referred for donation, there should be continuous education for emergency physicians on brain-dead organ and tissue donation-related knowledge and procedures. In addition, institutional or systematic improvements that can lead to organ donation when deciding on the withdrawal of life-sustaining treatment should be considered.

Silver-Assembled Silica Nanoparticles in Lateral Flow Immunoassay for Visual Inspection of Prostate-Specific Antigen.

Prostate-specific antigen (PSA) is the best-known biomarker for early diagnosis of prostate cancer. For prostate cancer in particular, the threshold level of PSA <4.0 ng/mL in clinical samples is an important indicator. Quick and easy visual detection of the PSA level greatly helps in early detection and treatment of prostate cancer and reducing mortality. In this study, we developed optimized silica-coated silver-assembled silica nanoparticles (SiO2@Ag@SiO2 NPs) that were applied to a visual lateral flow immunoassay (LFIA) platform for PSA detection. During synthesis, the ratio of silica NPs to silver nitrate changed, and as the synthesized NPs exhibited distinct UV spectra and colors, most optimized SiO2@Ag@SiO2 NPs showed the potential for early prostate cancer diagnosis. The PSA detection limit of our LFIA platform was 1.1 ng/mL. By applying each SiO2@Ag@SiO2 NP to the visual LFIA platform, optimized SiO2@Ag@SiO2 NPs were selected in the test strip, and clinical samples from prostate cancer patients were successfully detected as the boundaries of non-specific binding were clearly seen and the level of PSA was <4 ng/mL, thus providing an avenue for quick prostate cancer diagnosis and early treatment.

Metal Nano/Microparticles for Bioapplications.

Nano/micro particles are considered to be the most valuable and important functional materials in the field of materials science and engineering [...].

Synthesis and Application of Silica-Coated Quantum Dots in Biomedicine.

Quantum dots (QDs) are semiconductor nanoparticles with outstanding optoelectronic properties. More specifically, QDs are highly bright and exhibit wide absorption spectra, narrow light bands, and excellent photovoltaic stability, which make them useful in bioscience and medicine, particularly for sensing, optical imaging, cell separation, and diagnosis. In general, QDs are stabilized using a hydrophobic ligand during synthesis, and thus their hydrophobic surfaces must undergo hydrophilic modification if the QDs are to be used in bioapplications. Silica-coating is one of the most effective methods for overcoming the disadvantages of QDs, owing to silica's physicochemical stability, nontoxicity, and excellent bioavailability. This review highlights recent progress in the design, preparation, and application of silica-coated QDs and presents an overview of the major challenges and prospects of their application.

Developing neural network models for early detection of cardiac arrest in emergency department.

BACKGROUND: Automated surveillance for cardiac arrests would be useful in overcrowded emergency departments. The purpose of this study is to develop and test artificial neural network (ANN) classifiers for early detection of patients at risk of cardiac arrest in emergency departments. METHODS: This is a single-center electronic health record (EHR)-based study. The primary outcome was the development of cardiac arrest within 24 h after prediction. Three ANN models were trained: multilayer perceptron (MLP), long-short-term memory (LSTM), and hybrid. These were compared to other classifiers including the modified early warning score (MEWS), logistic regression, and random forest. We used AUROC, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the comparison. RESULTS: During the study period, there were a total of 374,605 ED visits and 2,910,321 patient status updates. The ANN models (MLP, LSTM, and hybrid) achieved higher AUROC (AUROC: 0.929, 0.933, and 0.936; 95% confidential interval: 0.926-0.932, 0.930-0.936, and 0.933-0.939, respectively) compared to the non-ANN models, and the hybrid model exhibited the best performance. The ANN classifiers displayed higher performance in most of the test characteristics when the threshold levels of the classifiers were fixed to display the same positive result as those at the three MEWS thresholds (score ≥ 3, ≥4, and ≥5), and when compared with each other. CONCLUSIONS: The ANN improves upon MEWS and conventional machine learning algorithms for the prediction of cardiac arrests in emergency departments. The hybrid ANN model utilizing both baseline and sequence information achieved the best performance.

Moderate to severe hyperphosphataemia as an independent prognostic factor for 28-day mortality in adult patients with sepsis.

BACKGROUND: Ischaemic tissue injury caused by tissue hypoperfusion is one of the major consequences of sepsis. Phosphate concentrations are elevated in ischaemic tissue injury. This study was performed to investigate the association of phosphate concentrations with mortality in patients with sepsis. METHODS: This was a retrospective cohort study of patients with sepsis conducted at an urban, tertiary care emergency department (ED) in Korea. Patients with sepsis arriving between March 2010 and April 2017 were stratified into four groups according to the initial phosphate concentration at presentation to the ED: group I (hypophosphataemia, phosphate <2 mg/dL), group II (normophosphataemia, phosphate 2-4 mg/dL), group III (mild hyperphosphataemia, phosphate 4-6 mg/dL), group IV (moderate to severe hyperphosphataemia, phosphate ≥6 mg/dL). Multivariable Cox proportional hazard regression analyses were performed to evaluate the independent association of initial phosphate concentration with 28-day mortality. RESULTS: Of the 3034 participants in the study, the overall mortality rate was 21.9%. The 28-day mortality rates were group I (hypophosphataemia) 14.6%, group II 17.4% (normophosphataemia), group III (mild hyperphosphataemia) 29.2% and group IV (moderate to severe hyperphosphataemia) 51.4%, respectively (p<0.001). In the multivariable analyses, patients with severe hyperphosphataemia had a significantly higher risk of death than those with normal phosphate levels (HR 1.59; 95% CI 1.23 to 2.05). Mortality in the other groups was not significantly different from mortality in patients with normophosphataemia. CONCLUSIONS: Moderate to severe hyperphosphataemia was associated with 28-day mortality in patients with sepsis. Phosphate level could be used as a prognostic indicator in sepsis.

Molecular profiling of single circulating tumor cells from lung cancer patients.

Circulating tumor cells (CTCs) are established cancer biomarkers for the "liquid biopsy" of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non-small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.