Long-Term Outcomes of Sacubitril/Valsartan in Heart Failure with Reduced Ejection Fraction and Coexisting End-Stage Renal Disease.

Sacubitril/valsartan (Entresto) has proven therapeutic effects in heart failure (HF) patients, but its impact on those with advanced chronic kidney disease (CKD) remains unclear, particularly in HF patients with coexisting end-stage renal disease (ESRD). This study aims to assess the long-term survival of patients with heart failure with reduced ejection fraction (HFrEF) and coexisting ESRD treated with sacubitril/valsartan. A retrospective cohort study included 2,860 HFrEF and ESRD patients between January 2008 and December 2020. After propensity score matching, data from a sacubitril/valsartan group (n = 61) and a candesartan or valsartan group (n = 117) were analyzed. Patients on sacubitril/valsartan for at least 9 months had significantly lower 5-year all-cause mortality (39.3%) compared with the non-sacubitril/valsartan group (54.7%) (HR 0.46; 95% CI, 0.25-0.82; P = 0.0094). Left ventricular ejection fraction (LVEF) improvement after 3 years in the sacubitril/valsartan group (14.51 ±18.98) was significantly greater than the non-sacubitril/valsartan group (6.91 ±18.44) (P = 0.0408). Average hospitalizations in sacubitril/valsartan and non-sacubitril/valsartan groups were 1.39 and 0.97, respectively (incidence rate ratio, 1.59; 95% CI, 0.90-2.82; P = 0.1106). Sacubitril/valsartan treatment demonstrated significantly lower 5-year mortality rates and greater LVEF improvement in HFrEF patients with coexisting ESRD compared with candesartan or valsartan. These findings suggest that sacubitril/valsartan is a beneficial treatment option for this patient population.

Integrating Artificial Intelligence for Advancing Multiple-Cancer Early Detection via Serum Biomarkers: A Narrative Review.

The concept and policies of multicancer early detection (MCED) have gained significant attention from governments worldwide in recent years. In the era of burgeoning artificial intelligence (AI) technology, the integration of MCED with AI has become a prevailing trend, giving rise to a plethora of MCED AI products. However, due to the heterogeneity of both the detection targets and the AI technologies, the overall diversity of MCED AI products remains considerable. The types of detection targets encompass protein biomarkers, cell-free DNA, or combinations of these biomarkers. In the development of AI models, different model training approaches are employed, including datasets of case-control studies or real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, and time-wise validation, are used. All of the factors show significant impacts on the predictive efficacy of MCED AIs. After the completion of AI model development, deploying the MCED AIs in clinical practice presents numerous challenges, including presenting the predictive reports, identifying the potential locations and types of tumors, and addressing cancer-related information, such as clinical follow-up and treatment. This study reviews several mature MCED AI products currently available in the market, detecting their composing factors from serum biomarker detection, MCED AI training/validation, and the clinical application. This review illuminates the challenges encountered by existing MCED AI products across these stages, offering insights into the continued development and obstacles within the field of MCED AI.

Trend of HPV Molecular Epidemiology in the Post-Vaccine Era: A 10-Year Study.

Cervical cancer, a major health concern among women worldwide, is closely linked to human papillomavirus (HPV) infection. This study explores the evolving landscape of HPV molecular epidemiology in Taiwan over a decade (2010-2020), where prophylactic HPV vaccination has been implemented since 2007. Analyzing data from 40,561 vaginal swab samples, with 42.0% testing positive for HPV, we reveal shifting trends in HPV genotype distribution and infection patterns. The 12 high-risk genotypes, in order of decreasing percentage, were HPV 52, 58, 16, 18, 51, 56, 39, 59, 33, 31, 45, and 35. The predominant genotypes were HPV 52, 58, and 16, accounting for over 70% of cases annually. The proportions of high-risk and non-high-risk HPV infections varied across age groups. High-risk infections predominated in sexually active individuals aged 30-50 and were mixed-type infections. The composition of high-risk HPV genotypes was generally stable over time; however, HPV31, 33, 39, and 51 significantly decreased over the decade. Of the strains, HPV31 and 33 are shielded by the nonavalent HPV vaccine. However, no reduction was noted for the other seven genotypes. This study offers valuable insights into the post-vaccine HPV epidemiology. Future investigations should delve into HPV vaccines' effects and their implications for cervical cancer prevention strategies. These findings underscore the need for continued surveillance and research to guide effective public health interventions targeting HPV-associated diseases.

A novel AIE material for sensing of Erythromycin in pure water by hydrogen bond in portable test strips and cellular imaging applications.

Erythromycin could be used to treat various bacterial infection, but it was harmful to the colonic microflora. Therefore, it is highly desirable to develop a fluorescence probe that could selectively and sensitively detect Erythromycin in pure water. In this work, a fluorescent probe named EHMC, which exhibited aggregation-induced emission (AIE) characteristic in solid state and water/EtOH binary solvent was developed for "turn on" sensing Erythromycin in pure water with high selectivity and sensitivity (detection limit: 1.78 × 10-8 M). Also, there are fewer interference from other antibiotics in the detection process of probe EHMC for Erythromycin. Moreover, probe EHMC could as a portable test strips for highly selective detection of Erythromycin and identification of different concentrations of Erythromycin. In addition, living cells imaging experiments displayed that probe EHMC could detect Erythromycin in A549 cells and BEAS-2B cells successfully. Combined with the theoretical calculation results The sensing mechanisms that the CO in Erythromycin and OH in EHMC formed intermolecular hydrogen bond and further formed new aggregates were confirmed by job' plot, 1H NMR, FT-IR, ESI-MS, DLS and TEM and DFT calculation.

Alternate Antimicrobial Therapies and Their Companion Tests.

New antimicrobial approaches are essential to counter antimicrobial resistance. The drug development pipeline is exhausted with the emergence of resistance, resulting in unsuccessful trials. The lack of an effective drug developed from the conventional drug portfolio has mandated the introspection into the list of potentially effective unconventional alternate antimicrobial molecules. Alternate therapies with clinically explicable forms include monoclonal antibodies, antimicrobial peptides, aptamers, and phages. Clinical diagnostics optimize the drug delivery. In the era of diagnostic-based applications, it is logical to draw diagnostic-based treatment for infectious diseases. Selection criteria of alternate therapeutics in infectious diseases include detection, monitoring of response, and resistance mechanism identification. Integrating these diagnostic applications is disruptive to the traditional therapeutic development. The challenges and mitigation methods need to be noted. Applying the goals of clinical pharmacokinetics that include enhancing efficacy and decreasing toxicity of drug therapy, this review analyses the strong correlation of alternate antimicrobial therapeutics in infectious diseases. The relationship between drug concentration and the resulting effect defined by the pharmacodynamic parameters are also analyzed. This review analyzes the perspectives of aligning diagnostic initiatives with the use of alternate therapeutics, with a particular focus on companion diagnostic applications in infectious diseases.

Risk Stratification for Herpes Simplex Virus Pneumonia Using Elastic Net Penalized Cox Proportional Hazard Algorithm with Enhanced Explainability.

Herpes simplex virus (HSV) pneumonia is a serious and often fatal respiratory tract infection that occurs in immunocompromised individuals. The early detection of accurate risk stratification is essential in identifying patients who are at high risk of mortality and may benefit from more aggressive treatment. In this study, we developed and validated a risk stratification model for HSV bronchopneumonia using an elastic net penalized Cox proportional hazard algorithm. We analyzed data from a cohort of 104 critically ill patients with HSV bronchopneumonia identified in Chang Gung Memorial Hospital, Linkou, Taiwan: one of the largest tertiary medical centers in the world. A total of 109 predictors, both clinical and laboratory, were identified in this process to develop a risk stratification model that could accurately predict mortality in patients with HSV bronchopneumonia. This model was able to differentiate the risk of death and predict mortality in patients with HSV bronchopneumonia compared to the APACHE II score in the early stage of ICU admissions. Both hazard ratio coefficient and selection frequency were used as the metrics to enhance the explainability of the informative predictors. Our findings suggest that the elastic net penalized Cox proportional hazard algorithm is a promising tool for risk stratification in patients with HSV bronchopneumonia and could be useful in identifying those at high risk of mortality.

Association between statin use and risk of gallstone disease and cholecystectomy: a meta-analysis of 590,086 patients.

Background: Statins have been reported to reduce the risk of gallstone disease. However, the impacts of different durations of statin use on gallstone disease have not been clarified. The aim of this study is toperform a systematic review with meta-analysis to update and to elucidate the association between statin use and the risk of gallstone disease and cholecystectomy. Methods: Medline, Embase and Cochrane Library were searched from the inception until August 2022 for relevant articles investigating the difference in the risk of gallstone disease between statin users and non-users (PROSPERO, ID: CRD42020182445). Meta-analyses were conducted using odds ratios (ORs) with corresponding 95% confidence intervals (CIs) to compare the risk of gallstone disease and cholecystectomy between statin user and nonusers. Results: Eight studies enrolling 590,086 patients were included. Overall, the use of statins was associated with a marginally significant lower risk of gallstone disease than nonusers (OR, 0.91; 95% CI [0.82-1.00]). Further subgroup analysis showed that short-term users, medium-term users, and long-term users were associated with a significantly higher risk (OR, 1.18; 95% CI [1.11-1.25]), comparable risk (OR, 0.93; 95% CI [0.83-1.04]), and significantly lower risk of gallstone diseases (OR, 0.78; 95% CI [0.68-0.90]) respectively, compared to nonusers. Conclusions: Patients with medium-term or long-term use of statins without discontinuation are at a lower risk of gallstone disease or cholecystectomy.

Antibiotic Resistance Diagnosis in ESKAPE Pathogens-A Review on Proteomic Perspective.

Antibiotic resistance has emerged as an imminent pandemic. Rapid diagnostic assays distinguish bacterial infections from other diseases and aid antimicrobial stewardship, therapy optimization, and epidemiological surveillance. Traditional methods typically have longer turn-around times for definitive results. On the other hand, proteomic studies have progressed constantly and improved both in qualitative and quantitative analysis. With a wide range of data sets made available in the public domain, the ability to interpret the data has considerably reduced the error rates. This review gives an insight on state-of-the-art proteomic techniques in diagnosing antibiotic resistance in ESKAPE pathogens with a future outlook for evading the "imminent pandemic".

Soliciting Social Support from Migrant Domestic Workers' Connections to Storytelling Networks during a Public Health Crisis.

Guided by communication infrastructure theory and social support theory, this study scrutinizes how the storytelling networks of marginalized communities, particularly migrant domestic workers (MDWs), provided social support amid the COVID-19 pandemic. Data obtained from in-depth interviews with 32 Indonesian MDWs in Hong Kong revealed that the community storytelling networks, comprising interpersonal relationships, community organizations, and media outlets, played an essential role in assisting the coping efforts of MDWs during the pandemic. These storytelling networks offered various types of social support, including informational, emotional, and instrumental or tangible assistance. However, these connections to the storytelling networks were also sources of the spread of misinformation. Theoretical and practical implications are further discussed.

Do proton pump inhibitors affect the effectiveness of chemotherapy in colorectal cancer patients? A systematic review with meta-analysis.

Proton pump inhibitors (PPI), one of the most commonly prescribed medications, carry a myriad of adverse events. For colorectal cancer (CRC) patients, it still remains unclear whether the concurrent use of proton pump inhibitors (PPI) would negatively affect chemotherapy. PubMed, Medline, Embase, and Cochrane Library were searched from inception to 10 June 2022, to identify relevant studies involving CRC patients receiving chemotherapy and reporting comparative survival outcomes between PPI users and non-users. Meta-analyses were performed using random-effects models. We identified 16 studies involving 8,188 patients (PPI = 1,789; non-PPI = 6,329) receiving either capecitabine-based or fluorouracil-based regimens. The overall survival (HR, 1.02; 95% CI, 0.91 to 1.15; I2 = 0%) and progression-free survival (HR, 1.15; 95% CI, 0.98 to 1.35; I2 = 29%) were similar between PPI users and non-users in patients taking capecitabine-based regimens, with low statis-tical heterogeneity. Although the subgroup analysis indicated that early-stage cancer patients taking capecitabine monotherapy with concurrent PPI had a significantly higher disease progression rate (HR, 1.96; 95% CI, 1.21 to 3.16; I2 = 0%) than those who did not use PPIs, both groups had comparable all-cause mortality (HR, 1.31; 95% CI, 0.75 to 2.29; I2 = 0%). On the other hand, there was little difference in both OS and PFS in both early- and end-stage patients taking capecitabine combination therapy between PPI users and non-users. Conversely, the use of concomitant PPI in patients taking fluorouracil-based regimens contributed to a marginally significant higher all-cause mortality (HR, 1.18; 95% CI, 1.00 to 1.40; I2 = 74%), but with high statistical heterogeneity. In conclusion, PPI has little survival influence on CRC patients treated with capecitabine-based regimens, especially in patients taking capecitabine combination therapy. Thus, it should be safe for clinicians to prescribe PPI in these patients. Although patients treated with fluorouracil-based regimens with concomitant PPI trended toward higher all-cause mortality, results were subject to considerable heterogeneity. Systematic Review Registration: identifier https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022338161.

Evaluation of three commercial kits effective identification of menstrual blood based on the D-dimer.

Blood or bloodstains are encountered frequently in forensic investigations. Presumptive and more confirmatory tests for peripheral blood are well established, however, similar methods for menstrual blood identification are less so. D-dimer is a fibrin degradation product that occurs at high concentration in menstrual blood and therefore a potential target to screen for this body fluid. We evaluated three rapid tests to determine if they can discriminate menstrual blood from peripheral remote from a laboratory setting. Their sensitivity, specificity and robustness were also assessed. The assays were: a latex agglutination (Dade Dimertest Latex Assay), SERATEC PMB test and OneStep D-dimer RapidCard InstaTest, both of which are based on lateral flow immunochromatographic analysis. Of the three, greater sensitivity was observed using the OneStep D-dimer RapidCard InstaTest, regardless of whether liquid or a stain was used. This test also detected a result using the smallest volume of menstrual blood, 0.003125 µL. Specificity testing was based on six different body fluids (urine, saliva, peripheral blood, semen, sweats and vaginal fluid) resulting in all 30 samples testing negative for the D-dimer using the OneStep D-dimer RapidCard InstaTest. Mixtures at ratios 1:1, 1:3 and 1:9 (menstrual blood: the other biofluid or PBS) were tested and the results showed that D-dimer could be detected for all samples using either the Dade Dimertest Latex Assay or the OneStep D-dimer RapidCard InstaTest. The body fluids were exposed to environmental stresses such as various temperature (-20 °C, 4 °C, room temperature and 37 °C for 30, 90, 180 and 360 days) and fluctuations in humidity (42%, 76% and 100% humidity at room temperature for 1, 3, 5, 10 and 20 days): all samples were D-dimer positive using the OneStep D-dimer RapidCard InstaTest though the strength decreased relative to the increase of storage time and temperature or humidity. All 6 postmortem blood samples gave a positive result for D-dimer using the OneStep D-dimer RapidCard InstaTest and 2 samples gave a positive response using the Dade Dimertest Latex Assay and the SERATEC PMB test; peripheral blood postmortem samples can show an increase in D-dimer. Menstrual blood was recovered from the pads under the sample wells after testing using the two immunochromatographic assays from which STR alleles could be amplified successfully. The results presented here support the application of these commercial kits for effective identification of menstrual blood.

Long short-term memory model - A deep learning approach for medical data with irregularity in cancer predication with tumor markers.

BACKGROUND: Machine learning (ML) has emerged as a superior method for the analysis of large datasets. Application of ML is often hindered by incompleteness of the data which is particularly evident when approaching disease screening data due to varied testing regimens across medical institutions. Here we explored the utility of multiple ML algorithms to predict cancer risk when trained using a large but incomplete real-world dataset of tumor marker (TM) values. METHODS: TM screening data were collected from a large asymptomatic cohort (n = 163,174) at two independent medical centers. The cohort included 785 individuals who were subsequently diagnosed with cancer. Data included levels of up to eight TMs, but for most subjects, only a subset of the biomarkers were tested. In some instances, TM values were available at multiple time points, but intervals between tests varied widely. The data were used to train and test various machine learning models to evaluate their robustness for predicting cancer risk. Multiple methods for data imputation were explored and models were developed for both single time-point as well as time-series data. RESULTS: The ML algorithm, long short-term memory (LSTM), demonstrated superiority over other models for dealing with irregular medical data. A cancer risk prediction tool was trained and validated for a single time-point test of a TM panel including up to four biomarkers (AUROC = 0.831, 95% CI: 0.827-0.835) which outperformed a single threshold method using the same biomarkers. A second model relying on time series data of up to four time-points for 5 TMs had an AUROC of 0.931. CONCLUSIONS: A cancer risk prediction tool was developed by training a LSTM model using a large but incomplete real-world dataset of TM values. The LSTM model was best able to handle irregular data compared to other ML models. The use of time-series TM data can further improve the predictive performance of LSTM models even when the intervals between tests vary widely. These risk prediction tools are useful to direct subjects to further screening sooner, resulting in earlier detection of occult tumors.

Rapid and Accurate Discrimination of Mycobacterium abscessus Subspecies Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Spectrum and Machine Learning Algorithms.

Mycobacterium abscessus complex (MABC) has been reported to cause complicated infections. Subspecies identification of MABC is crucial for adequate treatment due to different antimicrobial resistance properties amid subspecies. However, long incubation days are needed for the traditional antibiotic susceptibility testing (AST). Delayed effective antibiotics administration often causes unfavorable outcomes. Thus, we proposed a novel approach to identify subspecies and potential antibiotic resistance, guiding early and accurate treatment. Subspecies of MABC isolates were determined by secA1, rpoB, and hsp65. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) spectra were analyzed, and informative peaks were detected by random forest (RF) importance. Machine learning (ML) algorithms were used to build models for classifying MABC subspecies based on spectrum. The models were validated by repeated five-fold cross-validation to avoid over-fitting. In total, 102 MABC isolates (52 subspecies abscessus and 50 subspecies massiliense) were analyzed. Top informative peaks including m/z 6715, 4739, etc. were identified. RF model attained AUROC of 0.9166 (95% CI: 0.9072-0.9196) and outperformed other algorithms in discriminating abscessus from massiliense. We developed a MALDI-TOF based ML model for rapid and accurate MABC subspecies identification. Due to the significant correlation between subspecies and corresponding antibiotics resistance, this diagnostic tool guides a more precise and timelier MABC subspecies-specific treatment.

The Association between Baseline Proton Pump Inhibitors, Immune Checkpoint Inhibitors, and Chemotherapy: A Systematic Review with Network Meta-Analysis.

(1) Although emerging evidence suggests that proton pump inhibitor (PPI)-induced dysbiosis negatively alters treatment response to immune checkpoint inhibitors (ICIs) in cancer patients, no study systematically investigates the association between PPIs, ICIs, and chemotherapy; (2) Cochrane Library, Embase, Medline, and PubMed were searched from inception to 20 May 2022, to identify relevant studies involving patients receiving ICIs or chemotherapy and reporting survival outcome between PPI users and non-users. Survival outcomes included overall survival (OS) and progression-free survival (PFS). Network meta-analyses were performed using random-effects models. p-scores, with a value between 0 and 1, were calculated to quantify the treatment ranking, with a higher score suggesting a higher probability of greater effectiveness. We also conducted pairwise meta-analyses of observational studies to complement our network meta-analysis; (3) We identified 62 studies involving 26,484 patients (PPI = 8834; non-PPI = 17,650), including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC), melanoma, renal cell carcinoma (RCC), hepatocellular carcinoma (HCC), and squamous cell carcinoma (SCC) of the neck and head. Eight post-hoc analyses from 18 randomized-controlled trials were included in our network, which demonstrated that, in advanced NSCLC and UC, patients under ICI treatment with concomitant PPI (p-score: 0.2016) are associated with both poorer OS (HR, 1.49; 95% CI, 1.37 to 1.67) and poorer PFS (HR, 1.41; 95% CI, 1.25 to 1.61) than those without PPIs (p-score: 1.000). Patients under ICI treatment with concomitant PPI also had poorer OS (HR, 1.18; 95% CI, 1.07 to 1.31) and poorer PFS (HR, 1.30; 95% CI, 1.14 to 1.48) in comparison with those receiving chemotherapy (p-score: 0.6664), implying that PPIs may compromise ICI's effectiveness, making it less effective than chemotherapy. Our pairwise meta-analyses also supported this association. Conversely, PPI has little effect on patients with advanced melanoma, RCC, HCC, and SCC of the neck and head who were treated with ICIs; (4) "PPI-induced dysbiosis" serves as a significant modifier of treatment response in both advanced NSCLC and UC that are treated with ICIs, compromising the effectiveness of ICIs to be less than that of chemotherapy. Thus, clinicians should avoid unnecessary PPI prescription in these patients. "PPI-induced dysbiosis", on the other hand, does not alter the treatment response to ICIs in advanced melanoma, RCC, HCC, and SCC of the head and neck.

The Intraocular Pressure Lowering Effect of a Dual Kinase Inhibitor (ITRI-E-(S)4046) in Ocular Hypertensive Animal Models.

Purpose: The purpose of this study was to develop a preclinical compound, ITRI-E-(S)4046, a dual synergistic inhibitor of myosin light chain kinase 4 (MYLK4) and Rho-related protein kinase (ROCK), for reducing intraocular pressure (IOP). Methods: ITRI-E-(S)4046 is an amino-pyrazole derivative with physical and chemical properties suitable for ophthalmic formulation. In vitro kinase inhibition was evaluated using the Kinase-Glo Luminescent Kinase Assays. A comprehensive kinase selectivity analysis of ITRI-E-(S)4046 was performed using the KINOMEscan assay from DiscoverRx. The IOP reduction and tolerability of ITRI-E-(S)4046 were assessed in ocular normotensive rabbits, ocular normotensive non-human primates, and ocular hypertensive rabbits. In vivo studies were conducted to assess drug concentrations in ocular tissue. The adverse ocular effects of rabbit eyes were evaluated following the OECD405 guidelines. Results: ITRI-E-(S)4046 showed highly selective kinase inhibitory activity against ROCK1/2, MYLK4, and mitogen-activated protein kinase kinase kinase 19 (MAP3K19), with high specificity against protein kinase A, G, and C families. In ocular normotensive rabbits and non-human primates, the mean IOP reductions of 0.1% ITRI-E-(S)4046 eye drops were 29.8% and 28.5%, respectively. In hypertonic saline-induced and magnetic beads-induced ocular hypertensive rabbits, the mean IOP reductions of ITRI-E-(S)4046 0.1% eye drops were 46.9% and 22.0%, respectively. ITRI-E-(S)4046 was well tolerated with only temporary and minor signs of hyperemia. Conclusions: ITRI-E-(S)4046 is a novel type of highly specific ROCK1/2 and MYLK4 inhibitor that can reduce IOP in normotensive and hypertensive animal models. It has the potential to become an effective and well-tolerated treatment for glaucoma.

Timing of Adjuvant Radiotherapy After Keloid Excision: A Systematic Review and Meta-Analysis.

BACKGROUND: No consensus exists regarding the appropriate timing of adjuvant radiotherapy administration after surgical excision of keloids. OBJECTIVE: This study investigated the appropriate timing of adjuvant radiotherapy. MATERIALS AND METHODS: A systematic review and meta-analysis of randomized controlled trials and observational cohort studies was performed. A pooled estimate of the incidence rate was performed using a random-effects model. Subgroup analyses based on different anatomic region, biologically effective dose, keloid length, and radiotherapy regimen were also conducted. RESULTS: Sixteen observational cohort studies (1,908 keloid lesions) met the inclusion criteria. The incidence rate was significantly lower in the group treated with electron beam therapy more than 24 hours after surgery (3.80%; 95% confidence interval [CI], 1.78%-8.13%) than that in the group treated with the same therapy within 24 hours of surgery (37.16%; 95% CI, 20.80%-66.37%; p < .0001), but no significant difference was observed between the groups regarding brachytherapy and x-ray treatments. CONCLUSION: Immediate adjuvant radiotherapy did not significantly reduce the incidence rate of recurrent keloids.

Usefulness of multi-labelling artificial intelligence in detecting rhythm disorders and acute ST-elevation myocardial infarction on 12-lead electrocardiogram.

Aims: To develop an artificial intelligence-based approach with multi-labelling capability to identify both ST-elevation myocardial infarction (STEMI) and 12 heart rhythms based on 12-lead electrocardiograms (ECGs). Methods and results: We trained, validated, and tested a long short-term memory (LSTM) model for the multi-label diagnosis of 13 ECG patterns (STEMI + 12 rhythm classes) using 60 537 clinical ECGs from 35 981 patients recorded between 15 January 2009 and 31 December 2018. In addition to the internal test above, we conducted a real-world external test, comparing the LSTM model with board-certified physicians of different specialties using a separate dataset of 308 ECGs covering all 13 ECG diagnoses. In the internal test, the area under the curves (AUCs) of the LSTM model in classifying the 13 ECG patterns ranged between 0.939 and 0.999. For the external test, the LSTM model for multi-labelling of the 13 ECG patterns evaluated by AUC was 0.987 ± 0.021, which was superior to those of cardiologists (0.898 ± 0.113, P < 0.001), emergency physicians (0.820 ± 0.134, P < 0.001), internists (0.765 ± 0.155, P < 0.001), and a commercial algorithm (0.845 ± 0.121, P < 0.001). Of note, the LSTM model achieved an accuracy of 0.987, AUC of 0.997, and precision, recall, and F 1 score of 0.952, 0.870, and 0.909, respectively, in detecting STEMI. Conclusions: We demonstrated the usefulness of an LSTM model in the multi-labelling detection of both rhythm classes and STEMI in competitive testing against board-certified physicians. This AI tool exceeding the cardiologist-level performance in detecting STEMI and rhythm classes on 12-lead ECG may be useful in prioritizing chest pain triage and expediting clinical decision-making in healthcare.

Correction: A novel epigenetic modulating agent sensitizes pancreatic cells to a chemotherapy agent.

[This corrects the article DOI: 10.1371/journal.pone.0199130.].

Novel Toilet Paper-Based Point-Of-Care Test for the Rapid Detection of Fecal Occult Blood: Instrument Validation Study.

BACKGROUND: Colorectal cancer screening by fecal occult blood testing has been an important public health test and shown to reduce colorectal cancer-related mortality. However, the low participation rate in colorectal cancer screening by the general public remains a problematic public health issue. This fact could be attributed to the complex and unpleasant operation of the screening tool. OBJECTIVE: This study aimed to validate a novel toilet paper-based point-of-care test (ie, JustWipe) as a public health instrument to detect fecal occult blood and provide detailed results from the evaluation of the analytic characteristics in the clinical validation. METHODS: The mechanism of fecal specimen collection by the toilet-paper device was verified with repeatability and reproducibility tests. We also evaluated the analytical characteristics of the test reagents. For clinical validation, we conducted comparisons between JustWipe and other fecal occult blood tests. The first comparison was between JustWipe and typical fecal occult blood testing in a central laboratory setting with 70 fecal specimens from the hospital. For the second comparison, a total of 58 volunteers were recruited, and JustWipe was compared with the commercially available Hemoccult SENSA in a point-of-care setting. RESULTS: Adequate amounts of fecal specimens were collected using the toilet-paper device with small day-to-day and person-to-person variations. The limit of detection of the test reagent was evaluated to be 3.75 µg of hemoglobin per milliliter of reagent. Moreover, the test reagent also showed high repeatability (100%) on different days and high reproducibility (>96%) among different users. The overall agreement between JustWipe and a typical fecal occult blood test in a central laboratory setting was 82.9%. In the setting of point-of-care tests, the overall agreement between JustWipe and Hemoccult SENSA was 89.7%. Moreover, the usability questionnaire showed that the novel test tool had high scores in operation friendliness (87.3/100), ease of reading results (97.4/100), and information usefulness (96.1/100). CONCLUSIONS: We developed and validated a toilet paper-based fecal occult blood test for use as a point-of-care test for the rapid (in 60 seconds) and easy testing of fecal occult blood. These favorable characteristics render it a promising tool for colorectal cancer screening as a public health instrument.