Test Pattern Research Articles

Prostate-specific antigen testing patterns and prostate cancer stage at diagnosis in older Ohio cancer patients.

Prostate cancer (PCa) screening recommendations do not support prostate-specific antigen (PSA) screening for older men. Such screening often occurs, however. It is, therefore, important to understand how frequently and among which subgroups screening occurs, and the extent of distant stage PCa diagnoses among screened older men. Using the 2014-2016 linked Ohio Cancer Incidence Surveillance System (OCISS) and Medicare administrative database, we identified men 68 and older diagnosed with PCa and categorized their PSA testing in the three years preceding diagnosis as screening or diagnostic. We conducted multivariable logistic regression analysis to identify correlates of screening PSA and to determine whether screening PSA is independently associated with distant stage disease. Our study population included 3034 patients (median age: 73years). 62.1% of PCa patients underwent at least one screening-based PSA in the three years preceding diagnosis. Older age (75-84years: aOR [95% CI]: 0.84 [0.71, 0.99], ≥ 85: aOR: 0.27 [0.19, 0.38]), and frailty (aOR: 0.51 [0.37, 0.71]) were associated with lower screening. Screening was associated with decreased odds of distant stage disease (aOR: 0.55 [0.42, 0.71]). However, older age (75-84years: aOR: 2.43 [1.82, 3.25], ≥ 85: aOR: 10.57 [7.05, 15.85]), frailty (aOR: 5.00 [2.78, 9.31]), and being separated or divorced (aOR: 1.64 [1.01, 2.60]) were associated with increased distant stage PCa. PSA screening in older men is common, though providers appear to curtail PSA screening as age and frailty increase. Screened older men are diagnosed at earlier stages, but the harms of screening cannot be assessed.

Respiratory Viral Testing Rate Patterns in Young Children Attending Tertiary Care Across Western Australia: A Population-Based Birth Cohort Study.

An understanding of viral testing rates is crucial to accurately estimate the pathogen-specific hospitalisation burden. We aimed to estimate the patterns of testing for respiratory syncytial virus (RSV), influenza virus, parainfluenza virus (PIV) and human metapneumovirus (hMPV) by geographical location, age and time in children <5 years old in Western Australia. We conducted a population-based cohort study of children born between 1 January 2010 and 31 December 2021, utilising linked administrative data incorporating birth and death records, hospitalisations and respiratory viral surveillance testing records from state-wide public pathology data. We examined within-hospital testing rates using survival analysis techniques and identified independent predictors of testing using binary logistic regression. Our dataset included 46,553 laboratory tests for RSV, influenza, PIV, or hMPV from 355,021 children (52.5% male). Testing rates declined in the metropolitan region over the study period (RSV testing in infants: from 242.11/1000 child-years in 2012 to 155.47/1000 child-years in 2018) and increased thereafter. Conversely, rates increased in non-metropolitan areas (e.g., RSV in Goldfields: from 364.92 in 2012 to 504.37/1000 child-years in 2021). The strongest predictors of testing were age <12 months (adjusted odds ratio [aOR] = 2.25, 95% CI 2.20-2.31), preterm birth (<32 weeks: aOR = 2.90, 95% CI 2.76-3.05) and remote residence (aOR = 0.77, 95% CI 0.73-0.81). These current testing rates highlight the potential underestimation of respiratory virus hospitalisations by routine surveillance and the need for estimation of the true burden of respiratory virus admissions.

Comparative study on the thermal and tribological properties of PA12 and PA11 for coating applications

AbstractIn this study, the performance and potential applicability of polyamide‐12 (PA12) as an alternative to polyamide‐11 (PA11), which is currently used in the coating processes of sliding tools present in cardan shafts, was investigated. The advantages of PA12 powder instead of PA11 in cardan shafts' coating include ease of supply and cost‐effectiveness, while still achieving similar performance. Therefore, PA12 is a more economical choice for coating applications. The PA11 and PA12 neat polymers were characterized via differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA) and dynamic mechanical analysis (DMA). Based on the analyses, PA12 demonstrated substantial advantages over PA11. It showed a 16°C improvement in decomposition temperature and a 50% increase in crystallinity, enhancing stability under operational conditions, whereas PA11 exhibited approximately 6–7% higher values in crystallization and melting temperatures. The wettability behavior of the steel substrates coated with those polyamides was measured via contact angle analysis. Wear properties and morphologies of coatings were examined using a ball‐on disc test and scanning electron microscopy, respectively and comparatively. Furthermore, PA12 typically displays 30% lower wear rates and similar deformation patterns in tests, thereby presenting itself as a cost‐effective and widely accessible option for coating applications in comparison to PA11.

Test generation algorithm for QCA circuits targeting novel defects and its corresponding fault models

Considering the scaling limitations of current Complementary Metal Oxide Semiconductor (CMOS) technology, Quantum-dot-Cellular Automata (QCA) is emerging as one of the alternatives. QCA being at the molecular scale, defects are more likely to occur in it. Therefore, substantial development of QCA-oriented defects, its corresponding fault models and test generation is required. In this paper, a test generation algorithm for a QCA combinational circuit is proposed. The FAN (A Fanout Oriented) test generation algorithm is extended for QCA. The proposed Automatic Test Pattern Generator (ATPG) for QCA targets Single Stuck at Fault (SSF) set produced by novel Multiple Missing Cells (MMC) defects. The proposed ATPG is based on the QCA-oriented test generation properties and guided by proposed testability measures.The MCNC benchmark circuits are synthesized into QCA using proposed synthesis algorithms to check the effectiveness of the proposed ATPG. The ATPG is developed using C++ and tested on MCNC benchmark circuits. Further, ATPG-generated test vectors are validated at the QCA device level to demonstrate their correctness. The QCADesigner-E tool is used for the device-level implementation of the MCNC benchmark circuit.

Evaluation of Antimicrobial Resistance Patterns of Pseudomonas aeruginosa Strains Isolated among COVID-19 Patients in Brazil Typed by Fourier-Transform Infrared Spectroscopy.

This study aimed to characterize Pseudomonas aeruginosa strains isolated from hospitalized patients during the COVID-19 pandemic. This was achieved using phenotypic and molecular techniques, including their antimicrobial resistance profile and biofilm formation. Eighteen strains were isolated from a hospital in Rio de Janeiro, Brazil, and identified by VITEK®2, MALDI-TOF/MS (VITEK MS® and MALDI Biotyper®), and 16S rRNA sequencing. Fourier-transform infrared (FTIR) spectroscopy, antimicrobial susceptibility testing, and biofilm formation and disinfectant tolerance tests were applied to evaluate the virulence characteristics of the strains. VITEK®2 (≥99%), VITEK MS® (≥82.7%), and MALDI Biotyper® (score ≥ 2.01) accurately identified the P. aeruginosa strains, but 16S rRNA sequencing did not differentiate the species P. aeruginosa from P. paraeruginosa. FTIR typing identified three different clusters, but no correlation between the phenotypical or antimicrobial susceptibility testing patterns was found. Most strains exhibited resistance to various antimicrobials. The exceptions were sensitivity to amikacin and norfloxacin, and consequently, these could be considered potential treatment options. Most strains (n = 15, 83.3%) produced biofilms on polystyrene. Sodium hypochlorite treatment (0.5%/15 min) was shown to be the most effective disinfectant for biofilm elimination. P. aeruginosa biofilm formation and tolerance to disinfectants demonstrate the need for effective cleaning protocols to eliminate contamination by this organism in the hospital environment and medical equipment.

Perception of Pitch and Duration Pattern of Vowel /a/: A Comparison across Age and Gender in 5 to 9 Years Old Children

Abstract Objectives The present study aimed to develop pitch pattern test (PPT) and duration pattern test (DPT) using vowel and investigate the temporal ordering skills among typically developing children aged 5 to 9 years across genders. The study compared the performance of children on these tests across different age groups and gender. The study also investigated the relationship between performance on the DPT and PPT tasks using the vowel /a/. Materials and Methods Two verbal stimuli tests, DPT and PPT, were developed. For DPT, the vowel /a/ was used at 246 Hz and had two different durations of 500 and 250 ms for long and short stimuli, respectively, with a 300-ms interstimulus interval. For PPT, the vowel /a/ was used at 220 Hz for “low” stimuli and 261 Hz for “high” stimuli, both lasting 500 ms, with a 300-ms interstimulus duration and a 6-second intersequence duration.A cross-sectional study design was utilized in the study. A total of 100 typically developing school children aged between 5 and 9 years were divided into five age groups, each consisting of 10 males and 10 females. All children passed a hearing screening at 25 dB HL from 250 Hz to 4,000 Hz and had an average or above-average academic performance as reported by their teacher. All the children were tested using the developed tests. The order of administration of DPT and PPT was randomized. Children were instructed to listen to the sequence of vowel presentations and hum them in the same order. Results There was no significant difference between scores of males and females across all the age groups. On both tests, there was a significant improvement in the performance of the children with increase in age. There was a strong overall correlation between scores of DPT and PPT. Conclusion Both DPT and PPT, utilizing vowels as stimuli, did not exhibit a ceiling effect. This study highlighted a robust correlation between the two tests.

Diagnostic Power and Reproducibility of Objective Perimetry in Glaucoma.

An objective perimetry method provides four 30-2 style reports in 8 minutes. These comprise sensitivity and delay reports for both eyes. A combined report format shows comparable diagnostic power to two forms of automated perimetry. To compare objective perimetry with two forms of standard automated perimetry (SAP) in glaucoma. The study cohort contained 40 persons with glaucoma (PwG) and 94 normal control subjects. The PwG had both perimetric and pre-perimetric eyes. Multifocal pupillographic objective perimetry was performed with the objectiveField Analyser® (OFA®), which independently assesses the visual fields of both eyes concurrently. Its OFA30 test assessed the central ±30°, and the OFA15 test assessed the central ±15°, both providing 30-2 style reports. The OFA tests were repeated two weeks apart to assess test-retest variability (TRV). OFA was compared with Matrix and HFA-SITA fast 24-2 threshold testing. Diagnostic power was quantified as area under receiver operating characteristic curves (AUROC). Test durations, Mean Defects and Pattern Standard Deviations of the 4 tests were compared. At a median of 4.09±0.02 minutes/eye the OFA tests were quicker than SAP (all P≤0.0001), 2 minutes/eye if OFA per-region sensitivities and delays are considered separately. The %AUROCs for OFA, Matrix and HFA were not significantly different, averaging 93±3% (mean±SD) in perimetric eyes, and 73±6% in pre-perimetric eyes. For moderate to severe fields OFA TRV was less than published results for SAP. OFA30 mean defects were significantly correlated between repeats (r=0.91), and with OFA15 (r=0.93, both P<0.0001). OFA provides extra functional measures in the form of per-region delays, and between-eye asymmetries. Both the OFA wide-field and macular tests provided comparable diagnostic power to SAP and better TRV in damaged eyes.

A fast test compaction method using dedicated Pure MaxSAT solver embedded in DFT flow

Minimizing the testing cost is crucial in the context of the design for test (DFT) flow. In our observation, the test patterns generated by ATPG tools in test compression mode still contain redundancy. To tackle this obstacle, we propose a post-flow static test compaction method that utilizes a partial fault dictionary instead of a full fault dictionary to sharply reduce time and memory overhead, and leverages a dedicated Pure MaxSAT solver to re-compact the test patterns generated by ATPG tools. We also observe that ATPG tools offer a more comprehensive selection of candidate patterns for compaction in the “n-detect” mode, leading to superior compaction efficiency. In our experiments conducted on benchmark circuits ISCAS89, ITC99, and an open-source RISC-V CPU, we employed two methodologies. For commercial tool, we utilized a non-intrusive approach, while we adopted an intrusive method for open-source ATPG. Under the non-intrusive approach, our method achieved a maximum reduction of 34.69% in pattern count and a maximum 29.80% decrease in test cycles as evaluated by a leading commercial tool. Meanwhile, under the intrusive approach, our method attained a maximum 71.90% reduction in pattern count as evaluated by an open-source ATPG tool. Notably, fault coverage remained unchanged throughout the experiments. Furthermore, our approach demonstrates improved performance compared with existing methods.

Translating Test Responses to Images for Test-termination Prediction via Multiple Machine Learning Strategies

Failure diagnosis is a software-based, data-driven procedure. Collecting an excessive amount of fail data not only increases the overall test cost but can also potentially reduce diagnostic resolution. Thus, test-termination prediction is proposed to dynamically determine the appropriate failing test pattern to terminate testing, producing an amount of test data that is sufficient for an accurate diagnosis analysis. In this work, we describe a set of novel methods utilizing advanced machine learning techniques for efficient test-termination prediction. To implement this approach, we first generate images representing failing test responses from failure-log files. These images are then used to train a multi-layer convolutional neural network (CNN) incorporating a residual block. The trained CNN model leverages the images and known diagnostic results to determine the optimal test-termination strategy within the testing process, ensuring efficient and high-quality diagnosis. In addition to the integration of test response-to-image translation, our approach harnesses two cutting-edge learning strategies to enhance fail data and boost performance in subsequent tasks. The first strategy is transfer learning, which utilizes sample-label information from one circuit to guide the decision of whether to continue or stop testing for another circuit lacking labels. The second strategy involves the use of a generative deep model to generate fail data in the form of synthetic images. This technique increases the modeling effectiveness by expanding the volume of training samples. Experimental results conducted on actual failing chips and standard benchmarks validate that our proposed method surpasses existing approaches. Our method creates opportunities to harness the power of recent advances in machine learning for improving test and diagnosis efficiency.

Pattern Susceptibility of Antibiotics against an Aerobic Bacterial Isolated from Ear Infection in Khartoum Ear, Nose, and Throat Hospital

Abstract The main causalities of ear diseases are bacterial infection. This cross-sectional study desired to select the antibiotic susceptibility test pattern of an aerobic bacteria isolated from ear infections in Khartoum Ear, Nose, and Throat hospital between December and May 2016-2017. The study involved fifty ear swabs were collected from patients and cultivated. Bacterial isolates were determined using standard methods, including Gram stain and biochemical test according to CLSI Standards. Then Chromogen agar was employed as verification for identification. Antibiotic susceptibility Testing was conducted on bacterial isolates. According to Kirby-Bauer, the antimicrobial vulnerability testing was performed using the agar diffusion method. The study showed that 11(50%) of the bacterial isolate were resistant to Ampicillin, followed by 6 (27.3%) Cefotaxime and 3(13.6%) Cefalexin. While Pseudomonas spp were 18(100%) susceptible to Merponeme and Ciprofloxacin, followed by 17 (94.4%) Gentamicin and 16 (88.9%) Cefatoxime. The frequency of bacterial isolation was moderately high. The predominant bacteria were Pseudomonas spp, followed by Proteus spp. The isolates were highly resistant to Ampicillin, followed by Amoxicillin, Cefalixinm, Ciprofloxacin, and Gentamicin were found to be diligent against all bacteria.

Post-Diagnosis HCV RNA Testing Rates Prior to HCV Treatment Among People Living With HIV With HCV Antibody Positivity in the Asia-Pacific Region.

HCV RNA test determines current active infection and is a requirement prior to initiating HCV treatment. We investigated trends and factors associated with post-diagnosis HCV RNA testing rates prior to HCV treatment, and risk factors for first positive HCV RNA among people living with HIV (PLHIV) with HCV in the Asia-Pacific region. PLHIV with positive HCV antibody and in follow-up after 2010 were included. Patients were considered HCV-antibody positive if they ever tested positive for HCV antibody (HCVAb). Repeated measures Poisson regression model was used to analyse factors associated with post-diagnosis HCV RNA testing rates from positive HCVAb test. Factors associated with time to first positive HCV RNA from positive HCVAb test were analysed using Cox regression model. There were 767 HCVAb positive participants included (87% from LMICs) of whom 11% had HCV RNA tests. With 163 HCV RNA tests post positive HCVAb test, the overall testing rate was 5.05 per 100 person-years. Factors associated with increased testing rates included later calendar years of follow-up, HIV viral load ≥1000 copies/mL and higher income countries. Later calendar years of follow-up, ALT >5 times its upper limit of normal, and higher income countries were associated with shorter time to first positive HCV RNA test. Testing patterns indicated that uptake was predominantly in high income countries possibly due to different strategies used to determine testing in LMICs. Expanding access to HCV RNA, such as through lower-cost point of care assays, will be required to achieve elimination of HCV as a public health issue.

In‐Situ Rheology Measurements via Machine‐Learning Enhanced Direct‐Ink‐Writing

Direct ink writing, an extrusion‐based 3D printing method, is well suited for high‐mix low‐volume manufacturing. However, an iterative approach, using random selection or constant expert guidance, is still used to create printable inks and optimize printing parameters by expending significant amounts of time, materials, and effort. Herein, a machine learning (ML) model that estimates ink rheology in‐situ from a simple printed test pattern is reported. This ML model is trained with a rheologically diverse set of inks composed of different polymers. The model successfully correlated features of the simple printed test pattern to rheological properties, which could, in theory, inform both printed structures and future ink compositions. The behavior of this model is verified and analyzed with explainable artificial intelligence tools, linking printed feature importance to one's known physical understanding of the process.

Influence of viscosity and fiber reinforcement of resin composite on fracture strength and failure mode of restored molars.

To evaluate the fracture behavior of human molars with extensive MOD restorations using short-fiber-reinforced resin composite of varying viscosities. Human molars were randomly divided into seven groups (n = 12): intact teeth (control); restoration using conventional high-viscosity resin composite without (Filtek Z350XT, 3M) or with fibers (everX Posterior, GC); conventional low-viscosity resin composite without (Filtek Supreme Flowable, 3M) or with fibers (everX Flow Dentin Shade, GC); bulk-fill low-viscosity resin composite (Filtek Bulk Fill Flow, 3M) or with fibers (everX Flow Bulk Shade, GC). Restorations were performed on extensive MOD preparations, following the manufacturers' recommendations for each material. Specimens underwent fracture strength testing (N) and fracture pattern (%) categorized as repairable, possibly repairable, or non-repairable. Results were analyzed using a generalized linear model (N) and Fisher's exact test (%), with α = 0.05. Restorations performed with high-viscosity materials showed fracture strength values similar to the control and higher than those of restorations using low-viscosity resin composites (p < 0.0001), except for the bulk-fill low-viscosity resin composite with fibers (p > 0.05). Teeth restored using low-viscosity resin composite with fibers showed a higher % of repairable and possibly repairable fractures than the control (p = 0.0091). The viscosity of materials mediated the fracture strength, with restorations using high-viscosity resin composites promoting values similar to the intact tooth; however, the presence of fibers influenced the fracture pattern. Teeth with MOD cavities restored with high-viscosity resin composites showed similar fracture strength to intact teeth. Fiber-reinforced low-viscosity resin composite for the base of restoration resulted in a more repairable/possibly repairable fracture pattern.

Changing patterns of routine laboratory testing over time at children's hospitals.

Research into low-value routine testing at children's hospitals has not consistently evaluated changing patterns of testing over time. To identify changes in routine laboratory testing rates at children's hospitals over ten years and the association with patient outcomes. We performed a multi-center, retrospective cohort study of children aged 0-18 hospitalized with common, lower-severity diagnoses at 28 children's hospitals in the Pediatric Health Information Systems database. We calculated average annual testing rates for complete blood counts, electrolytes, and inflammatory markers between 2010 and 2019 for each hospital. A >2% average testing rate change per year was defined as clinically meaningful and used to separate hospitals into groups: increasing, decreasing, and unchanged testing rates. Groups were compared for differences in length of stay, cost, and 30-day readmission or ED revisit, adjusted for demographics and case mix index. Our study included 576,572 encounters for common, low-severity diagnoses. Individual hospital testing rates in each year of the study varied from 0.3 to 1.4 tests per patient day. The average yearly change in hospital-specific testing rates ranged from -6% to +7%. Four hospitals remained in the lowest quartile of testing and two in the highest quartile throughout all 10 years of the study. We grouped hospitals with increasing (8), decreasing (n = 5), and unchanged (n = 15) testing rates. No difference was found across subgroups in costs, length of stay, 30-day ED revisit, or readmission rates. Comparing resource utilization trends over time provides important insights into achievable rates of testing reduction.

Clinical and diagnostic features of long-COVID patients presenting with neurologic symptoms in Chicago.

Long COVID, a condition characterized by persistent symptoms after COVID-19 infection, is increasingly being recognized worldwide. Neurologic symptoms are frequently reported in survivors of COVID-19, making it crucial to better understand this phenomenon both on a societal scale and for the quality of life of these patients. Between January 1, 2020, and July 31, 2022, Illinois(IL) had a standardized cumulative death rate that ranked it 24th out of the 51 states in the United States (US). However, the US had one of the highest per capita COVID-19 death rates among large, high-income countries. [Bollyky T. et al. 2023] As a result of the increased number of COVID-19 infections, there was a rise in the number of patients experiencing Long COVID. At our neuro-infectious disease clinic in Chicago(IL), we observed an increasing number of patients presenting with cognitive and other neurologic symptoms after contracting COVID-19. Initially, we needed to provide these individuals with a better understanding of their condition and expected outcomes. We were thus motivated to further evaluate this group of patients for any patterns in presentation, neurologic findings, and diagnostic testing that would help us better understand this phenomenon. We aim to contribute to the growing body of research on Long COVID, including its presentation, diagnostic testing results, and outcomes to enlighten the long COVID syndrome. We hypothesize that the neurological symptoms resulting from long COVID persist for over 12 months. We conducted a retrospective analysis of clinical data from 44 patients with long-COVID. Cognitive symptoms were the most common presenting concern. Abnormalities in Montreal Cognitive Assessment, electroencephalogram, serum autoantibody testing, and cerebrospinal fluid were found in minority subsets of our cohort. At 12 months, most patients continue to experience neurologic symptoms, though more than half reported moderate or marked improvement compared to initial presentation. Although most of the patients in this study did not show a consistent occurrence of symptoms suggesting a cohesive underlying etiology, our clinical data demonstrated some features of Long COVID patients in Chicago (IL) that could lead to new research avenues, helping us better understand this syndrome that affects patients worldwide.

Real-World Biomarker Test Ordering Practices in Non-Small Cell Lung Cancer: Interphysician Variation and Association With Clinical Outcomes.

Patients with metastatic or advanced non-small cell lung cancer (NSCLC) need biomarker testing, including, in most cases, anaplastic lymphoma kinase (ALK), epidermal growth factor receptor (EGFR), and PD-L1, to identify options for targeted therapies and to optimally incorporate immune checkpoint inhibitors into therapeutic regimens. We sought to examine real-world patterns of biomarker testing, quantify interphysician practice variation, and correlate testing with clinical outcomes. We extracted real-world data from a nationwide electronic health record-derived deidentified database from 17,165 patients diagnosed with advanced NSCLC between 2018 and 2021 and receiving care in the community setting. We analyzed data using descriptive analyses, fixed- and mixed-effects logistic regression models, and proportional hazard models. Only 67% of all 17,165 patients and 77% of patients with nonsquamous, metastatic NSCLC had ALK, EGFR, and PD-L1 testing within 90 days of diagnosis. Later diagnosis year (2019-2021 compared with 2018) was associated with higher rates of ALK, EGFR, and PD-L1 testing; stage IIIB/C disease (compared with stage IV), squamous histology, and Black or African American race were associated with lower rates. Interphysician variation was substantial with a median odds ratio between physicians (adjusted for patient factors) of 1.78 for ALK, EGFR, and PD-L1 testing. Patients with nonsquamous, metastatic NSCLC had significantly prolonged survival if tested with all three biomarkers (median, 364 days for all three v 180 for none of the three; hazard ratio, 0.67; P < .001). Rates of biomarker testing appear suboptimal with substantial interphysician variation. Testing correlates with improved survival, although causality cannot be proven from this study. Additional work is needed to address the underlying causes of suboptimal test ordering.

Identification and Treatment of Lung Cancer Oncogenic Drivers in a Diverse Safety Net Setting

IntroductionAdvances in the testing and treatment of patients with non-small cell lung cancer (NSCLC) harboring oncogenic drivers have improved outcomes. Little is known about testing and treatment patterns in diverse patient populations. MethodsWe conducted a retrospective study in a diverse cohort of patients treated in the John Peter Smith safety net healthcare system. We determined patterns of blood- and tissue-based testing and treatment of patients with EGFR and ALK alterations. Cox proportional-hazards regression models were used to assess the impact of EGFR and ALK testing. ResultsA total of 220 patients were included, 97 (44%) were non-Hispanic White, 72 (33%) were Black, 28 (13%) were Hispanic, and 23 (10%) were Asian. EGFR and ALK testing increased over time from 55% and 52%, respectively, in 2017 to 87% and 82%, respectively, in 2021. Frequency of EGFR alterations were highest in Asian patients (45%) and comparable among other groups (6-13%). Frequency of ALK alterations were highest in Hispanic (13%), and Asian (11%) patients, and were 2% for both Black and non-Hispanic White patients. In a multivariate model, lack of testing was associated with worse survival (aHR 1.6; P = .003) and testing positive for EGFR (aHR 0.43; P = .01) or ALK (aHR 0.28; P = .04) was associated with improved survival. Race and ethnicity were not associated with survival differences. ConclusionAs molecular testing for oncogenic mutations in NSCLC increases, druggable alterations such as ALK and EGFR can be identified in all race-ethnicity groups and are associated with improved outcomes.

A GCPW slow‐wave transmission line with improved wavelength reduction technique by adopting capacitor array

AbstractThis letter presents a grounded coplanar waveguide (GCPW) slow‐wave transmission line (SWTL) with an improved wavelength reduction technique by adopting capacitor array. By cross‐interleaving additional capacitors between a signal line and side ground planes, the total capacitance in the capacitor array increases approximately two times compared to the conventional structure, allowing designers to choose a smaller signal conductor's width for higher inductance, thus, improving wavelength reduction performance while preserving the same characteristic impedance. At the 150 GHz frequency of interest, the proposed GCPW SWTL shows approximately 20% and 62.16% reduction in wavelength compared to the reported GCPW SWTL and regular CPW, respectively, with the same characteristic impedance. To prove the effectiveness of the proposed SWTL concept, the proposed GCPW SWTL test patterns are fabricated in a 65 nm CMOS process.

Validation of a Major and Clinically Relevant Nonmajor Bleeding Phenotyping Algorithm on Electronic Health Records.

Bleeding is an important health outcome of interest in epidemiological studies. We aimed to develop and validate rule-based algorithms to identify (1) major bleeding and (2) all clinically relevant bleeding (CRB) (composite of major and all clinically relevant nonmajor bleeding) within real-world electronic healthcare data. We took a random sample (n = 1630) of inpatient admissions to Singapore public healthcare institutions in 2019 and 2020, stratifying by hospital and year. We included patients of all age groups, sex, and ethnicities. Presence of major bleeding and CRB were ascertained by two annotators through chart review. A total of 630 and 1000 records were used for algorithm development and validation, respectively. We formulated two algorithms: sensitivity- and positive predictive value (PPV)-optimized algorithms. A combination of hemoglobin test patterns and diagnosis codes were used in the final algorithms. During validation, diagnosis codes alone yielded low sensitivities for major bleeding (0.16) and CRB (0.24), although specificities and PPV were high (>0.97). For major bleeding, the sensitivity-optimized algorithm had much higher sensitivity and negative predictive values (NPVs) (sensitivity = 0.94, NPV = 1.00), however false positive rates were also relatively high (specificity = 0.90, PPV = 0.34). PPV-optimized algorithm had improved specificity and PPV (specificity = 0.96, PPV = 0.52), with little reduction in sensitivity and NPV (sensitivity = 0.88, NPV = 0.99). For CRB events, our algorithms had lower sensitivities (0.50-0.56). The use of diagnosis codes alone misses many genuine major bleeding events. We have developed major bleeding algorithms with high sensitivities, which can ascertain events within populations of interest.

Burden of Multidrug-Resistant Gram-Negative Bacterial Infections in a Tertiary Care Hospital

Multidrug-resistant (MDR) Gram-negative bacterial infections have emerged as a major public health concern. The aim of the present study was to detect the rate of infections due to MDR Gram-negative bacteria (GNB) in a tertiary care hospital, the rate of Carbapenemases and AmpC-β-lactamases production and the Antimicrobial susceptibility test pattern (AST) among MDR GNB. The rate of MDR GNB during the study period was 25.70%. Urine samples showed the highest contribution to the total MDR GNB. Among the total MDR GNB isolates, 166 were randomly selected and included in the present study. A higher rate of MDR GNB was reported among male patients (61.5%) compared to the females (38.5%) and most of them were from the patients aged between 61-70 years (30.7%). The most prevalent MDR GNB was Klebsiella pneumoniae 80 (48.12%), followed by Escherichia coli 43 (25.9%). AST of MDR GNB revealed their significant resistance to β-lactamases/β-lactamases inhibitors, cephalosporins, fluoroquinolones and carbapenem drugs (98%). Of 123 MDR Enterobacterales, 83% of them were found to be Metallo β-lactamase (MBLs) producers by mCIM and eCIM methods. Of 43 MDR non-fermenters, 29 (67.4%) of them were found to be carbapenemase producers by MHT. About 29.51% of MDR GNB isolates were found to be AmpC producers by AmpC disk test. A reliable and rapid phenotypic method to detect carbapenemases and AmpC β-lactamases among MDR GNB in a routine microbiology laboratory method is clinically important to guide antibiotic therapy and implementation of effective infection control practices.