Sensitivity Rate Research Articles

A supervised machine learning model for identifying predictive factors for recommending head and neck cancer surgery.

New patient referrals are often processed by practice coordinators with little-to-no medical background. Treatment delays due to incorrect referral processing, however, have detrimental consequences. Identifying variables that are associated with a higher likelihood of surgical oncological resection may improve patient referral processing and expedite the time to treatment. The study objective is to develop a supervised machine learning (ML) platform that identifies relevant variables associated with head and neck surgical resection. A retrospective cohort study was conducted on 64 222 patient datapoints from the SEER database. The random forest ML model correctly classified patients who were offered head and neck surgery with an 81% accuracy rate. The sensitivity and specificity rates were 86% and 71%. The positive and negative predictive values were 85% and 73%. ML modeling accurately predicts head and neck cancer surgery recommendations based on patient and cancer information from a large population-based dataset. ML adjuncts for referral processing may decrease the time to treatment for patients with cancer.

Performance comparison of 6 in-hospital patient monitoring systems in the detection and alarm of ventricular cardiac arrhythmias

BackgroundPatient monitoring devices are critical in alerting potential cardiac arrhythmias during hospitalization; however, there are concerns of alarm fatigue due to high false alarm rates. ObjectiveTo evaluate sensitivity and false alarm rate of hospital-based continuous electrocardiographic (ECG) monitoring technologies. MethodsSix commonly-used multiparameter bedside monitoring systems available in the United States were evaluated: B125M (GE HealthCare), ePM10 and iPM12 (Mindray), Efficia and IntelliVue (Philips), and Life Scope (Nihon Kohden). Sensitivity was tested using ECG recordings containing 57 true ventricular tachycardia (VT) events. False positive rate testing used 205 patient-hours of ECG recordings containing no cardiac arrhythmias. Signals from ECG recordings were fed to devices simultaneously; high-severity arrhythmia alarms were tracked. Sensitivity to true VT events and false positive rates were determined. Differences were assessed using Fisher’s exact tests (sensitivity) and Z-tests (false positive rates). ResultsB125M raised 56 total alarms for 57 annotated VT events and had the highest sensitivity (98%, P<0.05), followed by iPM12 (84%), Life Scope (81%), Efficia (79%), ePM10 (77%), and IntelliVue (75%). B125M raised 20 false alarms, significantly lower (P<0.0001) than iPM12 (284), Life Scope (292), IntelliVue (304), ePM10 (324), and Efficia (493). The most common false alarm was VT, followed by non-sustained VT. ConclusionWe found significant performance differences among multiparameter bedside ECG monitoring systems using previously-collected recordings. B125M had the highest sensitivity in detecting true VT events and lowest false alarm rate. These results can assist in minimizing alarm fatigue and optimizing patient safety by careful selection of in-hospital continuous monitoring technology.

Role of Endoscopic Ultrasound in Staging and Vascular Assessment of Pancreatic Cancer.

Introduction Computed tomography (CT) of the abdomen with contrast stands as the gold standard for assessing pancreatic cancer, encompassing both staging and vascular analysis. However, not all patients are suitable candidates for contrast-enhanced CT (CECT) scans due to factors such as contrast agent allergies, pregnancy, renal impairment, radiation risks, and limited tissue sampling capability in CECT scans of the abdomen. In light of these challenges, this study evaluated the diagnostic capabilities of endoscopic ultrasound (EUS) compared to CECT for staging and vascular assessment of pancreatic cancer. Methods Fifty patients diagnosed with pancreatic cancer underwent evaluations using both CECT scans and EUS, focusing on staging and vascular invasion assessment. Vascular evaluation was carried out using a categorization system based on EUS findings, classifying them into three types based on the tumor-vessel relationship: Type 1 indicating clear invasion or encasement of a vessel by a tumoror contact with a vessel wall exceeding 180 degrees, Type 2 representing abutment, wherein a tumor contacts a vessel wall but at an angle less than 180 degrees, and Type 3 implying clear non-invasion, where a discernible distance exists between a tumor and a vessel. In this categorization, Type 1 and Type 2 indicated signs of vascular invasion, while Type 3 indicated vascular non-invasion. These findings were subsequently compared to the results from CECT scans. The endoscopist performing EUS was blinded to the CT outcomes prior to the examination. Results Regarding pancreatic cancer staging, EUS exhibited remarkable sensitivity, specificity, and accuracy rates of 100% according to the T criterion.As for vascular invasion assessment,EUS demonstrated sensitivity, specificity, and accuracy of 100%, 95.93%, and 96%, respectively, for venous invasion. For arterial invasion, the figures were 95.65% sensitivity, 100% specificity, and an overall accuracy of 99.5%. Conclusion EUS is an effective modality for evaluating both staging and vascular invasion in pancreatic cancer, boasting exceptional sensitivity, specificity, and accuracy rates. The findings are robust enough to consider EUS a viable alternative to CT scans in evaluation, with the added advantage of EUS offering tissue sampling capability.

Development of an Autonomous Component Testing System with Reliability Improvement Using Computer Vision and Machine Learning

This study evaluated computer vision-based models, including Histogram Analysis, Logistic Regression, Sift-SVM, and Deep learning models, in an autonomous testing system developed for smartphone camera modules. System performance was assessed in a practical factory setting with workers operating the system, and metrics such as processing time, sensitivity, specificity, accuracy, and defect rate were evaluated. Based on the results, the Sift-SVM model demonstrated the greatest potential for enhancing the reliability of the system with a processing time of 0.01578 seconds, a sensitivity of 99.811%, and a reduction in the failure rate to 1888 PPM. The study findings suggest that Sift-SVM has the potential to be practically applied in the industry, thus improving the speed and accuracy of automatic defect detection in manufacturing and reducing the defect rate.

Metagenomic next-generation sequencing, instead of procalcitonin, could guide antibiotic usage in patients with febrile acute necrotizing pancreatitis: a multicenter, prospective cohort study.

The effectiveness of procalcitonin-based algorithms in guiding antibiotic usage for febrile acute necrotizing pancreatitis (ANP) remains controversial. Metagenomic next-generation sequencing (mNGS) has been applied to diagnose infectious diseases. The authors aimed to evaluate the effectiveness of blood mNGS in guiding antibiotic stewardship for febrile ANP. The prospective multicenter clinical trial was conducted at seven hospitals in China. Blood samples were collected during fever (T ≥38.5°C) from ANP patients. The effectiveness of blood mNGS, procalcitonin, and blood culture in diagnosing pancreatic infection was evaluated and compared. Additionally, the real-world utilization of antibiotics and the potential mNGS-guided antimicrobial strategy in febrile ANP were also analyzed. From May 2023 to October 2023, a total of 78 patients with febrile ANP were enrolled and 30 patients (38.5%) were confirmed infected pancreatic necrosis (IPN). Compared with procalcitonin and blood culture, mNGS showed a significantly higher sensitivity rate (86.7% vs. 56.7% vs. 26.7%, P <0.001). Moreover, mNGS outperformed procalcitonin (89.5 vs. 61.4%, P <0.01) and blood culture (89.5 vs. 69.0%, P <0.01) in terms of negative predictive value. Blood mNGS exhibited the highest accuracy (85.7%) in diagnosing IPN and sterile pancreatic necrosis, significantly superior to both procalcitonin (65.7%) and blood culture (61.4%). In the multivariate analysis, positive blood mNGS (OR=60.2, P <0.001) and lower fibrinogen level (OR=2.0, P <0.05) were identified as independent predictors associated with IPN, whereas procalcitonin was not associated with IPN, but with increased mortality (Odds ratio=11.7, P =0.006). Overall, the rate of correct use of antibiotics in the cohort was only 18.6% (13/70) and would be improved to 81.4% (57/70) if adjusted according to the mNGS results. Blood mNGS represents important progress in the early diagnosis of IPN, with particular importance in guiding antibiotic usage for patients with febrile ANP.

Antimicrobial resistance survey and whole-genome analysis of nosocomial P. Aeruginosa isolated from eastern Province of China in 2016–2021

BackgroundPseudomonas aeruginosa is a major Gram-negative pathogen that can exacerbate lung infections in the patients with cystic fibrosis, which can ultimately lead to death.MethodsFrom 2016 to 2021, 103 strains of P. aeruginosa were isolated from hospitals and 20 antibiotics were used for antimicrobial susceptibility determination. Using next-generation genome sequencing technology, these strains were sequenced and analyzed in terms of serotypes, ST types, and resistance genes for epidemiological investigation.ResultsThe age distribution of patients ranged from 10 days to 94 years with a median age of 69 years old. The strains were mainly isolated from sputum (72 strains, 69.9%) and blood (14 strains, 13.6%). The size of these genomes ranged from 6.2 Mb to 7.4 Mb, with a mean value of 6.5 Mb. In addition to eight antibiotics that show inherent resistance to P. aeruginosa, the sensitivity rates for colistin, amikacin, gentamicin, ceftazidime, piperacillin, piperacillin-tazobactam, ciprofloxacin, meropenem, aztreonam, imipenem, cefepime and levofloxacin were 100%, 95.15%, 86.41%, 72.82%, 71.84%, 69.90%, 55.34%, 52.43%, 50.49%, 50.49%, 49.51% and 47.57% respectively, and the carriage rate of MDR strains was 30.69% (31/101). Whole-genome analysis showed that a total of 50 ST types were identified, with ST244 (5/103) and ST1076 (4/103) having a more pronounced distribution advantage. Serotype predictions showed that O6 accounted for 29.13% (30/103), O11 for 23.30% (24/103), O2 for 18.45% (19/103), and O1 for 11.65% (12/103) of the highest proportions. Notably, we found a significantly higher proportion of ExoU in P. aeruginosa strains of serotype O11 than in other cytotoxic exoenzyme positive strains. In addition to this, a total of 47 crpP genes that mediate resistance to fluoroquinolones antibiotics were found distributed on 43 P. aeruginosa strains, and 10 new variants of CrpP were identified, named 1.33, 1.34, 1.35, 1.36, 1.37, 1.38, 1.39, 1.40, 1.41 and 7.1.ConclusionsWe investigated the antibiotic susceptibility of clinical isolates of P. aeruginosa and genomically enriched the diversity of P. aeruginosa for its prophylactic and therapeutic value.

Brain tumor classification from MRI scans: a framework of hybrid deep learning model with Bayesian optimization and quantum theory-based marine predator algorithm.

Brain tumor classification is one of the most difficult tasks for clinical diagnosis and treatment in medical image analysis. Any errors that occur throughout the brain tumor diagnosis process may result in a shorter human life span. Nevertheless, most currently used techniques ignore certain features that have particular significance and relevance to the classification problem in favor of extracting and choosing deep significance features. One important area of research is the deep learning-based categorization of brain tumors using brain magnetic resonance imaging (MRI). This paper proposes an automated deep learning model and an optimal information fusion framework for classifying brain tumor from MRI images. The dataset used in this work was imbalanced, a key challenge for training selected networks. This imbalance in the training dataset impacts the performance of deep learning models because it causes the classifier performance to become biased in favor of the majority class. We designed a sparse autoencoder network to generate new images that resolve the problem of imbalance. After that, two pretrained neural networks were modified and the hyperparameters were initialized using Bayesian optimization, which was later utilized for the training process. After that, deep features were extracted from the global average pooling layer. The extracted features contain few irrelevant information; therefore, we proposed an improved Quantum Theory-based Marine Predator Optimization algorithm (QTbMPA). The proposed QTbMPA selects both networks' best features and finally fuses using a serial-based approach. The fused feature set is passed to neural network classifiers for the final classification. The proposed framework tested on an augmented Figshare dataset and an improved accuracy of 99.80%, a sensitivity rate of 99.83%, a false negative rate of 17%, and a precision rate of 99.83% is obtained. Comparison and ablation study show the improvement in the accuracy of this work.

Exploration of PCL-5 symptom validity indices for detection of exaggerated and feigned PTSD

ABSTRACT Introduction There are very few symptom validity indices directly examining overreported posttraumatic stress disorder (PTSD) symptomatology, and, until recently, there were no symptom validity indices embedded within the PTSD Checklist for the DSM-5 (PCL-5), which is one of the most commonly used PTSD measures. Given this, the current study sought to develop and cross-validate symptom validity indices for the PCL-5. Method Multiple criterion groups comprised of Veteran patients were utilized (N = 210). Patients were determined to be valid or invalid responders based on Personality Asessment Inventory symptom validity indices. Three PCL-5 symptom validity indices were then examined: the PCL-5 Symptom Severity scale (PSS), the PCL-5 Extreme Symptom scale (PES), and the PCL-5 Rare Items scale (PRI). Results Area under the curve statistics ranged from .78 to .85. The PSS and PES both met classification accuracy statistic goals, with the PES achieving the highest sensitivity rate (.39) when maintaining specificity at .90 or above across all criterion groups. When an ad hoc analysis was performed, which included only patients with exceptionally strong evidence of invalidity, sensitivity rates increased to .60 for the PES while maintaining specificity at .90. Conclusions These findings provide preliminary support for new PTSD symptom validity indices embedded within one of the most frequently used PTSD measures.

Precursors and Effects of Self-reported Parental Reflective Functioning: Links to Parental Attachment Representations and Behavioral Sensitivity.

Parental reflective functioning is thought to provide a missing link between caregivers' own attachment histories and their ensuing parenting behaviors. The current study sought to extend research on this association involving 115 parents, both mothers and fathers, of 5-to-6-year-old preschoolers using the German version of the Parental Reflective Functioning Questionnaire (PRFQ). Our study was the first to combine Adult Attachment Interview classifications of parental attachment, behavioral observations of parental sensitivity and PRFQ ratings while drawing on a sizable father subsample. We found theoretically consistent significant relations between all measures, while our results particularly highlighted the role of dismissing attachment for decreases in parenting quality on both cognitive and behavioral levels as the dismissing status differentially affected specific components of self-reported parental reflective functioning and observed sensitivity. Interestingly, these patterns were largely comparable in mothers and fathers. Exploratory mediation analyses further suggested that decreased parental reflective functioning may partially mediate the relationship between parents' dismissing attachment and decreased parental sensitivity. Thus, for prevention and intervention programs targeting parental sensitivity and thus children's long term healthy mental development, the interplay between parental reflective functioning and parents' own attachment history emerges as a key mechanism. Finally, our study served as a further validation of the PRFQ given the caveat that the pre-mentalizing subscale may need further revision in the German version.

In Vitro Antibacterial Activity of Ceftobiprole and Comparator Compounds against Nation-Wide Bloodstream Isolates and Different Sequence Types of MRSA.

Bloodstream infections by bacteria, especially multidrug-resistant bacteria, remain a worldwide public health concern. We evaluated the antibacterial activity of ceftobiprole and comparable drugs against different bloodstream isolates and different sequence types of methicillin-resistant Staphylococcus aureus (MRSA) in China. We found that MRSA, methicillin-susceptible Staphylococcus aureus (MSSA), and methicillin-susceptible coagulase-negative Staphylococcus (MSCNS) displayed ceftobiprole sensitivity rates of >95%, which are similar to the rates for linezolid, daptomycin, and vancomycin. Of the tested MRCNS strains, 90.4% were sensitive to ceftobiprole. The sensitivities of ST59, ST398, and ST22 MRSA to ceftobiprole were higher than that of ST239. Ceftobiprole's MIC50/90 value against Enterococcus faecalis was 0.25/2 mg/L, whereas Enterococcus faecium was completely resistant to this drug. Ceftobiprole exhibited no activity against ESBL-positive Enterobacterales, with resistance rates between 78.6% and 100%. For ESBL-negative Enterobacterales, excluding Klebsiella oxytoca, the sensitivity to ceftobiprole was comparable to that of ceftazidime, ceftriaxone, and cefepime. The MIC50/90 value of ceftobiprole against Pseudomonas aeruginosa was 2/16 mg/L, and for Acinetobacter baumannii, it was 32/>32 mg/L. Thus, ceftobiprole shows excellent antimicrobial activity against ESBL-negative Enterobacterales and Pseudomonas aeruginosa (comparable to that of ceftazidime, ceftriaxone, and cefepime); however, it is not effective against ESBL-positive Enterobacterales and Acinetobacter baumannii. These results provide important information to clinicians.

Clinical Impact of Proton Pump Inhibitor and Potassium-Competitive Acid Blocker for Predicting the Curability of Endoscopic Resection in Ulcerative Early Gastric Cancer

Introduction: Endoscopic diagnosis is essential for predicting the curability of early gastric cancer (EGC; R0 resection) before treatment, but the relationship between ulcerative lesions and clinical outcomes remains unclear. We aimed to investigate the effect of proton pump inhibitor (PPI) or potassium-competitive acid blocker (P-CAB) on the morphological changes of ulcerative EGCs and its relevance to the clinical outcomes. Methods: Altogether, 143 patients with differentiated ulcerative EGC that were resected by endoscopic submucosal dissection were retrospectively identified and divided into the following two cohorts depending on their PPI/P-CAB administration status: PPI/P-CAB (n = 76) and non-PPI/P-CAB (n = 67) cohorts. Furthermore, in each cohort, the patients were further divided into the improved and unimproved subgroups based on the ulcerative changes. Results: In the PPI/P-CAB cohort, the deep submucosal invasion and lymphovascular invasion rates were significantly higher in the unimproved subgroup than in the improved subgroup, resulting in a significantly lower R0 resection rate. Contrarily, no significant differences were found between the two subgroups in the non-PPI/P-CAB cohort. The significance of PPI/P-CAB administration was observed only in the ulcerative EGCs with open-type atrophy (R0 resection rate; improved vs. unimproved, 90.9% vs. 48.0%, p = 0.001). When the finding of improved ulcer with PPI/P-CAB administration was used as the indication of endoscopic resection in ulcerative EGCs with open-type atrophy, high sensitivity (78.9%) and accuracy (76.3%) rates for the curability were observed, which were higher than those of conventional endoscopic diagnosis alone (p = 0.021). Conclusion: PPI or P-CAB administration might contribute to the potential selection of ulcerative EGCs, enabling endoscopic curative resection.

Mite allergen sensitization patterns in Turkish children: Age-related changes and molecular correlations.

Mites are ubiquitous aeroallergens found worldwide. Elucidating individual mite allergen sensitization patterns provides critical insights for managing allergic diseases. This study aimed to investigate molecular allergen (MA) sensitization patterns across different age groups and explore cluster relationships among mite-sensitized children. We analyzed 76 children who exhibited sensitization to at least one of the 17 distinct mite MAs through microarray testing. Dermatophagoides farinae exhibited a slightly higher prevalence of sensitization compared with Dermatophagoides pteronyssinus. Der p 1/2 and Der f 1/2 demonstrated an almost 40% sensitization rate, while Der p 10/Blo t 10, Der p 20, Der p 23, and Gly d 2/Lep d 2 displayed an approximately 20% sensitization rate. Sensitization levels and ratios increased significantly with age for Der p 23 but showed numerical rises for other MAs, except for Der p 10/Blo t 10. The presence of various types of atopic diseases had only a minimal impact on sensitization profiles. Strong correlations emerged between Der f 2 and Der p 2, Der p 10 and Blo t 10, Der p 21 and Blo t 5, as well as Gly d 2 and Lep d 2. Hierarchical cluster analysis substantiated these relationships. Der p 10 and its homolog Blo t 10-sensitive patients (15/76) were mostly seen as mono sensitization(12/15). Ten patients exhibited monosensitization to Der p 20, suggesting a possible association with scabies infection. In children, mite sensitization diversity and levels increased with age. The presence of significant correlations/cluster relationships among these sensitizations underscores homologies among specific MAs.

Abstract WP70: Novel Weighted FANG-D Scale Scoring to Detect Large Vessel Occlusion

Objective: To determine if a novel weighted FANG-D scoring scale (NWFSS) increases sensitivity and specificity rates of large vessel occlusion (LVO) as compared to those reported with the original FANG-D scale scoring. Methodology: The present study used an observational, descriptive design to identify the important variables (field cut, aphasia, neglect, gaze preference, and dense hemiparesis) associated with the likelihood of detecting LVO. We used the FANG-D scale in patients admitted through the emergency department (ED) of a comprehensive stroke center (CSC), from December 2022 through April 2023. The NIHSS was performed and compared with the NWFSS for analysis. Each component was required to have a score ≥ 2(moderate to severe deficits) except dense hemiparesis which required a score ≥3 (significant weakness) to receive one point on the FANG-D scale. A total score of 2 or higher on FANG-D indicated a positive result suggesting LVO. If aphasia or neglect were present with a NIHSS of≥2, it was considered a positive FANG-D score. Results: A total of 311 patients were included in the study for analysis with a mean age of 67 ±16.4 years of whom 56.6% were female. The sensitivity and specificity rates were 85.7% (Confidence Interval (CI) =72.8%-94.1%) and 90.5% (CI= 86.2%-93.7%) respectively for positive predictive value of NWFSS to identify LVO. The sensitivity and specificity of the NIHSS has been reported as 86% and 60% respectively for LVO detection. The previous FANG-D study group used lower values in calculating the FANG-D scores and reported a sensitivity rate of 98% and specificity of 76.7%. Conclusion: The NWFSS has high specificity and is reliable for LVO prediction. While the NIHSS assesses eleven items sensitive for stroke diagnosis, it may take up to 10 minutes to complete and is not specific for LVO, whereas the FANG-D assesses 5items critical to LVO detection and is simple and fast with completion in &lt;1 minute, minimizing time to intervention. Our study occurred in the ED, but this scale scoring method could be tested in the prehospital setting. The use of a scale with higher specificity for LVO could improve patient outcomes and resource utilization by faster routing of patients to CSCs capable of performing mechanical thrombectomy.

Acute Intermittent Hypoxia Did Not Alter Pain Sensitivity or Pain Intensity Ratings for Individuals with Chronic Low Back Pain: A Pilot Study.

The purpose of this pilot study was to explore whether AIH produces changes in pain sensitivity or in reports of self-reported pain intensity for individuals with low back pain. In a quasi-experimental, cross-over design we compared participants (n = 9) exposed to normal room air and hypoxia using a commercially available gas blender. The treatment period consisted of 5 consecutive days of randomly assigned to AIH or room air. For the participants initially randomized to AIH there was cross-over to receive 5 more consecutive days of room air. Therefore, this design allowed for between group and within subject assessment of AIH effects. Pain sensitivity was assessed with quantitative sensory testing (QST) for posterior superior iliac spine pressure threshold, plantar thermal threshold, and peak pain ratings. Self-reported pain intensity for low back pain was assessed via the Brief Pain Inventory. There were no between group differences for AIH and room air in pain sensitivity or self-reported pain intensity. In the within subject analyses larger effect sizes favoring AIH were detected for plantar measures of pain sensitivity but not for self-reported pain intensity. This study, while presenting null findings, describes an initial step in determining whether AIH can be used to increase pain relief. Based on this pilot study we offer guidance for future research including study design, AIH dosage, participant selection, and using AIH in combination with non-pharmacologic treatments.

Antimicrobial Susceptibility Patterns of Salmonella Typhi and Salmonella Paratyphi in Tertiary Care Hospitals

Background: Salmonella typhi and Salmonella paratyphi are significant causes of enteric fever, posing substantial public health challenges globally. Monitoring their antimicrobial susceptibility patterns is crucial for guiding treatment strategies and combating antimicrobial resistance, particularly in tertiary care hospitals where severe cases are managed. Aim: To determine the antibiogram profile of Salmonella typhi and Salmonella paratyphi isolated from blood cultures of paediatrics patients presenting in Lady Reading Hospital Peshawar. Methodology: The study examined the prevalence, clinical characteristics, and antibiotic susceptibility patterns of Salmonella typhi and Salmonella paratyphi infections among 530 participants aged 13 to 18 years presenting in Lady Reading Hospital Peshawar. Over the course of two years using a prospective observational cohort design. Recruitment, clinical evaluations, and laboratory validation using accepted methods were all part of the data gathering process. Testing for antibiotic susceptibility was done, and statistical analysis was done using SPSS version 28. Both informed consent and ethical approval were obtained. Results: The research included 530 instances of enteric fever, of which 318 cases (or 60%) were due to Salmonella typhi and 212 cases (or 40%) to Salmonella Paratyphi. There were 40.25% female cases and 59.75% male cases among them. The age group of 15–16 years old accounted for the largest percentage of cases (38.68%), followed by 13–14 years old (33.02%) and 17–18 years old (28.30%). Different patterns emerged from antimicrobial susceptibility tests; drugs such as ampicillin (66.04%), azithromycin (74.26%), cefixime (87.47%), ceftriaxone (92.77%), chloramphenicol (91.51%), ciprofloxacin (92.40%), and co-trimoxazole (55.03%) showed substantial susceptibility rates. Compared to Salmonella typhi, Salmonella paratyphi showed notably greater sensitivity rates for azithromycin (94.47%) and ceftriaxone (95.45%). Practical implication: This research provided the community with important advantages and practical consequences. The study helps healthcare professionals choose efficient treatment plans by identifying the antibiotic susceptibility patterns of Salmonella typhi and Salmonella paratyphi, particularly in tertiary care facilities. Conclusion: This study highlights the importance of continuous surveillance and species-specific treatment strategies to combat antimicrobial resistance and improve patient outcomes in enteric fever, particularly in tertiary care settings. Keywords:Antimicrobial susceptibility, Salmonella typhi, Salmonella Paratyphi, Tertiary care hospitals

Improving strain hardening behavior in nano-intermetallic reinforced aluminum in-situ composites through an optimized twostep thermal processing method; sintering and uniaxial forging

Excellent strain hardening capabilities are known to be the unique strategies to hold the key towards a good strength-ductility balance in Al−base composites. Herein, in-situ Fe-aluminide (FeAl) reinforced Al−matrix composites (Al/Fe-aluminide) were fabricated by a twostep thermal processing method: sintering (900 °C/1 h), and uniaxial forging (400 °C, deformation up to 20%). The reinforcements were formed in-situ by the exothermal reaction between the host Al matrix and Fe2O3 nanoparticles during sintering Measured strain rate sensitivity (m= 0.035)and strain rate recovery rate (ηr)highlighted that deformation during forging enhances strain hardening ability of the composites. Comprehensive characterization reveals high density of geometrically necessary dislocation (ρG∼1×1015m−2) usually persists near the grain boundaries (GBs) and the triple junctions of highly textured FCC−Al grains. Microtextural and Kernel average misorientation (KAM) measurements highlighted existence of strong deformation texture of Bras {110}<112> and Goss {110}<001>2 in FCC−Al matrix induce strong resistance to plastic deformation. While nanoindentation response based on plastic flow corresponding to activation volume (V*∼42b3) revealed that activities of GB interface−dislocation interaction induced strain accumulation at the FCC−Al GB interface zones involved in a thermally activated process promotes the evolution of ρGdistribution during straining sustain larger strains. The results reveal that the simultaneous attainment of both these processes improves global strain hardening behavior which is advantageous for the enhancement of resistance to failure.

Authentication of the botanical origin of monofloral honey by dielectric barrier discharge ionization high resolution mass spectrometry (DBDI-HRMS). Breaching the 6 s barrier of analysis time

Rapid volatile profiling of monofloral honey with dielectric barrier discharge ionization high resolution mass spectrometry (DBDI-HRMS) enabled the authentication of the studied honeys’ floral sources in as little as 6 s in a solventless manner. The overarching goal of this study was the set-up of a rapid and cost effective tool for the determination of the botanical origin of monofloral honey that can be easily accessed i) by beekeepers to authenticate and, thus, enhance the value of their own honey and ii) by the food industry for quality checks. To this aim, the volatile compounds of two independent batches of honeys with seven different botanical origins (acacia, dandelion, chestnut, rhododendron, citrus, sunflower, and linden) were captured by DBD-HRMS. A total of 112 monofloral honeys were analyzed by three different operators. Using the spectral data of the first batch of honeys, we built up and compared the performances of three different classification algorithms: least absolute shrinkage and selection operator (LASSO), partial least squares discriminant analysis (PLS-DA), and random forest (RF). The performances of the three classifiers were verified by repeated cross-validation, permutation test, resubstitution into the training set, and then finally validated with a second, independent set of honeys by a different, inexperienced operator. The outcomes of the tests were expressed by the area under the curve (AUC), Kappa statistic, overall accuracy, and sensitivity and specificity rates. The misclassification rates of the built classifiers were evaluated by computing different key indicators, and the repeatability of the analytical method was also verified by cosine similarity. These insights are relevant for future adoption of the method in routine work. We determined that the RF classifier was the most powerful in predicting the floral source of the honeys. The RF classifier produced high performance values when predicting an independent batch of samples analyzed by a different, inexperienced operator (AUC 82.91 %, overall accuracy 81.25 %, Kappa 77.78 %, sensitivity 81.05 %, and specificity 96.76 %). The misclassified honeys were those characterized by the presence of other nectars and or pollens, as previously pointed to by the sensory panelists This proof-of-principle work warrants a future large-scale study to validate and challenge the method with honeys from different harvests and of different geographical origins.

Revisiting the Malignant Masquerade at the Liver Hilum: Have We Made Progress?

Distinguishing malignant from benign causes of obstruction at the liver hilum can pose a diagnostic dilemma. This study aimed to determine factors that predict benign causes of hilar obstruction and long-term outcomes after resection. Consecutive patients who underwent surgery for hilar obstruction at a single institution between 1997 and 2022 were retrospectively analyzed. Median follow-up was 26months (range 0-281months). Among 182 patients who underwent surgery for hilar obstruction, 25 (14%) patients were found to have benign disease. Median CA19-9 level after normalization of serum bilirubin was 80U/mL (range 1-5779) and 21U/mL (range 1-681) among patients with malignant and benign strictures, respectively (p = 0.001). Cross-sectional imaging features associated with malignancy were lobar atrophy, soft tissue mass/infiltration, and vascular involvement (all p < 0.05). Factors not correlated with malignancy were jaundice upon presentation, peak serum bilirubin, sex, and race. Preoperative bile duct brushing or biopsy had sensitivity and specificity rates of 82% and 55%, respectively. Among patients who underwent resection with curative intent, grade 3-4 complications occurred in 55% and 29% of patients with malignant and benign strictures, respectively (p = 0.028). Postoperative long-term complications of chronic portal hypertension and recurrent cholangitis occurred in ≥ 10% of patients with both benign and malignant disease (p = non-significant). Strictures at the liver hilum continue to present diagnostic and management challenges. Postoperative complications and long-term sequelae of portal hypertension and recurrent cholangitis develop in a significant number of patients after resection of both benign and malignant strictures.

Sepsis Prediction at Emergency Department Triage Using Natural Language Processing: Retrospective Cohort Study.

Despite its high lethality, sepsis can be difficult to detect on initial presentation to the emergency department (ED). Machine learning-based tools may provide avenues for earlier detection and lifesaving intervention. The study aimed to predict sepsis at the time of ED triage using natural language processing of nursing triage notes and available clinical data. We constructed a retrospective cohort of all 1,234,434 consecutive ED encounters in 2015-2021 from 4 separate clinically heterogeneous academically affiliated EDs. After exclusion criteria were applied, the final cohort included 1,059,386 adult ED encounters. The primary outcome criteria for sepsis were presumed severe infection and acute organ dysfunction. After vectorization and dimensional reduction of triage notes and clinical data available at triage, a decision tree-based ensemble (time-of-triage) model was trained to predict sepsis using the training subset (n=950,921). A separate (comprehensive) model was trained using these data and laboratory data, as it became available at 1-hour intervals, after triage. Model performances were evaluated using the test (n=108,465) subset. Sepsis occurred in 35,318 encounters (incidence 3.45%). For sepsis prediction at the time of patient triage, using the primary definition, the area under the receiver operating characteristic curve (AUC) and macro F1-score for sepsis were 0.94 and 0.61, respectively. Sensitivity, specificity, and false positive rate were 0.87, 0.85, and 0.15, respectively. The time-of-triage model accurately predicted sepsis in 76% (1635/2150) of sepsis cases where sepsis screening was not initiated at triage and 97.5% (1630/1671) of cases where sepsis screening was initiated at triage. Positive and negative predictive values were 0.18 and 0.99, respectively. For sepsis prediction using laboratory data available each hour after ED arrival, the AUC peaked to 0.97 at 12 hours. Similar results were obtained when stratifying by hospital and when Centers for Disease Control and Prevention hospital toolkit for adult sepsis surveillance criteria were used to define sepsis. Among septic cases, sepsis was predicted in 36.1% (1375/3814), 49.9% (1902/3814), and 68.3% (2604/3814) of encounters, respectively, at 3, 2, and 1 hours prior to the first intravenous antibiotic order or where antibiotics where not ordered within the first 12 hours. Sepsis can accurately be predicted at ED presentation using nursing triage notes and clinical information available at the time of triage. This indicates that machine learning can facilitate timely and reliable alerting for intervention. Free-text data can improve the performance of predictive modeling at the time of triage and throughout the ED course.

Improved prostate cancer diagnosis using a modified ResNet50-based deep learning architecture

Prostate cancer, the most common cancer in men, is influenced by age, family history, genetics, and lifestyle factors. Early detection of prostate cancer using screening methods improves outcomes, but the balance between overdiagnosis and early detection remains debated. Using Deep Learning (DL) algorithms for prostate cancer detection offers a promising solution for accurate and efficient diagnosis, particularly in cases where prostate imaging is challenging. In this paper, we propose a Prostate Cancer Detection Model (PCDM) model for the automatic diagnosis of prostate cancer. It proves its clinical applicability to aid in the early detection and management of prostate cancer in real-world healthcare environments. The PCDM model is a modified ResNet50-based architecture that integrates faster R-CNN and dual optimizers to improve the performance of the detection process. The model is trained on a large dataset of annotated medical images, and the experimental results show that the proposed model outperforms both ResNet50 and VGG19 architectures. Specifically, the proposed model achieves high sensitivity, specificity, precision, and accuracy rates of 97.40%, 97.09%, 97.56%, and 95.24%, respectively.