A Targeted LC-MRM3 Proteomic Approach for the Diagnosis of SARS-CoV-2 Infection in Nasopharyngeal Swabs.

Since its first appearance, severe acute respiratory syndrome coronavirus 2 quickly spread around the world and the lack of adequate PCR testing capacities, especially during the early pandemic, led the scientific community to explore new approaches such as mass spectrometry (MS). We developed a proteomics workflow to target several tryptic peptides of the nucleocapsid protein. A highly selective multiple reaction monitoring-cubed (MRM3) strategy provided a sensitivity increase in comparison to conventional MRM acquisition. Our MRM3 approach was first tested on an Amsterdam public health cohort (alpha-variant, 760 participants) detecting viral nucleocapsid protein peptides from nasopharyngeal swabs samples presenting a cycle threshold value down to 35 with sensitivity and specificity of 94.2% and 100.0%, without immunopurification. A second iteration of the MS-diagnostic test, able to analyze more than 400 samples per day, was clinically validated on a Leiden-Rijswijk public health cohort (delta-variant, 2536 participants) achieving 99.9% specificity and 93.1% sensitivity for patients with cycle threshold values up to 35. In this manuscript, we also developed and brought the first proof of the concept of viral variant monitoring in a complex matrix using targeted MS.

Validation of the VirCapSeq-VERT system for differential diagnosis, detection, and surveillance of viral infections.

IMPORTANCE: Broad range assay for accurate and sensitive diagnostics.

Retrospective validation of MetaSystems' deep-learning-based digital microscopy platform with assistance compared to manual fluorescence microscopy for detection of mycobacteria.

This study aimed to validate Metasystems' automated acid-fast bacilli (AFB) smear microscopy scanning and deep-learning-based image analysis module (Neon Metafer) with assistance on respiratory and pleural samples, compared to conventional manual fluorescence microscopy (MM). Analytical parameters were assessed first, followed by a retrospective validation study. In all, 320 archived auramine-O-stained slides selected non-consecutively [85 originally reported as AFB-smear-positive, 235 AFB-smear-negative slides; with an overall mycobacterial culture positivity rate of 24.1% (77/320)] underwent whole-slide imaging and were analyzed by the Metafer Neon AFB Module (version 4.3.130) using a predetermined probability threshold (PT) for AFB detection of 96%. Digital slides were then examined by a trained reviewer blinded to previous AFB smear and culture results, for the final interpretation of assisted digital microscopy (a-DM). Paired results from both microscopic methods were compared to mycobacterial culture. A scanning failure rate of 10.6% (34/320) was observed, leaving 286 slides for analysis. After discrepant analysis, concordance, positive and negative agreements were 95.5% (95%CI, 92.4%-97.6%), 96.2% (95%CI, 89.2%-99.2%), and 95.2% (95%CI, 91.3%-97.7%), respectively. Using mycobacterial culture as reference standard, a-DM and MM had comparable sensitivities: 90.7% (95%CI, 81.7%-96.2%) versus 92.0% (95%CI, 83.4%-97.0%) (P-value = 1.00); while their specificities differed 91.9% (95%CI, 87.4%-95.2%) versus 95.7% (95%CI, 92.1%-98.0%), respectively (P-value = 0.03). Using a PT of 96%, MetaSystems' platform shows acceptable performance. With a national laboratory staff shortage and a local low mycobacterial infection rate, this instrument when combined with culture, can reliably triage-negative AFB-smear respiratory slides and identify positive slides requiring manual confirmation and semi-quantification. IMPORTANCE: This manuscript presents a full validation of MetaSystems' automated acid-fast bacilli (AFB) smear microscopy scanning and deep-learning-based image analysis module using a probability threshold of 96% including accuracy, precision studies, and evaluation of limit of AFB detection on respiratory samples when the technology is used with assistance. This study is complementary to the conversation started by Tomasello et al. on the use of image analysis artificial intelligence software in routine mycobacterial diagnostic activities within the context of high-throughput laboratories with low incidence of tuberculosis.

Clinical validation of two volumetric absorptive microsampling devices to support home-based therapeutic drug monitoring of immunosuppression.

AIMS: Dried blood volumetric absorptive microsamples (VAMS) may facilitate home-based sampling to enhance therapeutic drug monitoring after transplantation. This study aimed to clinically validate a liquid chromatography-tandem mass spectrometry assay using 2 VAMS devices with different sampling locations (Tasso-M20 for the upper arm and Mitra for the finger). Patient preferences were also evaluated. METHODS: Clinical validation was performed for tacrolimus and mycophenolic acid by comparison of paired VAMS and venipuncture samples using Passing-Bablok regression and Bland-Altman analysis. Conversion of mycophenolic acid VAMS to serum concentrations was evaluated using haematocrit-dependent formulas and fixed correction factors defined a priori. Patients' perspectives, including useability, acceptability and feasibility, were also investigated using established questionnaires. RESULTS: Paired samples (n = 50) were collected from 25 kidney transplant recipients. Differences for tacrolimus whole-blood concentration were within ±20% for 86 and 88% of samples from the upper arm and fingerstick, respectively. Using correction factors of 1.3 for the upper-arm and 1.47 for finger-prick samples, 84 and 76% of the paired samples, respectively, were within ±20% for mycophenolic acid serum concentration. Patient experience surveys demonstrated limited pain and acceptable useability of the upper-arm device. CONCLUSIONS: Tacrolimus and mycophenolic acid can be measured using 2 common VAMS devices with similar analytical performance. Patients are supportive of home-based monitoring with a preference for the Tasso-M20 device.

Urine high-risk human papillomavirus testing as an alternative to routine cervical screening: A comparative diagnostic accuracy study of two urine collection devices using a randomised study design trial.

OBJECTIVE: To evaluate the sensitivity of human papillomavirus (HPV) tested urine to detect high-grade cervical precancer (cervical intraepithelial neoplasia grade 2+ [CIN2+]) using two urine collection devices. DESIGN: Randomised controlled trial. SETTING: St Mary's Hospital, Manchester, UK. POPULATION: Colposcopy attendees with abnormal cervical screening; a total of 480 participants were randomised. Matched urine and cervical samples were available for 235 and 230 participants using a first-void urine (FVU)-collection device and standard pot, respectively. METHODS: Urine was self-collected and mixed with preservative - randomised 1:1 to FVU-collection device (Novosanis Colli-pee® 10 mL with urine conservation medium [UCM]) or standard pot. Matched clinician-collected cervical samples were taken before colposcopy. HPV testing used Roche cobas® 8800. A questionnaire evaluated urine self-sampling acceptability. MAIN OUTCOME MEASURES: The primary outcome measured sensitivity of HPV-tested urine (FVU-collection device and standard pot) for CIN2+ detection. Secondary outcomes compared HPV-tested cervical and urine samples for CIN2+ and evaluated the acceptability of urine self-sampling. RESULTS: Urine HPV test sensitivity for CIN2+ was higher with the FVU-collection device (90.3%, 95% CI 83.7%-94.9%, 112/124) than the standard pot (73.4%, 95% CI 64.7%-80.9%, 91/124, p = 0.0005). The relative sensitivity of FVU-device-collected urine was 0.92 (95% CI 0.87-0.97, pMcN = 0.004) compared with cervical, considering that all women were referred after a positive cervical HPV test. Urine-based sampling was acceptable to colposcopy attendees. CONCLUSIONS: Testing of FVU-device-collected urine for HPV was superior to standard-pot-collected urine in colposcopy attendees and has promising sensitivity for CIN2+ detection. General population HPV testing of FVU-device-collected urine will establish its clinical performance and acceptability as an alternative to routine cervical screening.

Clinical validation of a multi-protein, serum-based assay for disease activity assessments in multiple sclerosis.

An 18-protein multiple sclerosis (MS) disease activity (DA) test was validated based on associations between algorithm scores and clinical/radiographic assessments (N = 614 serum samples; Train [n = 426; algorithm development] and Test [n = 188; evaluation] subsets). The multi-protein model was trained based on presence/absence of gadolinium-positive (Gd+) lesions and was also strongly associated with new/enlarging T2 lesions, and active versus stable disease (composite of radiographic and clinical evidence of DA) with improved performance (p < 0.05) compared to the neurofilament light single protein model. The odds of having ≥1 Gd+ lesions with a moderate/high DA score were 4.49 times that of a low DA score, and the odds of having ≥2 Gd+ lesions with a high DA score were 20.99 times that of a low/moderate DA score. The MSDA Test was clinically validated with improved performance compared to the top-performing single-protein model and can serve as a quantitative tool to enhance the care of MS patients.

Clinical validation of a ctDNA-Based Assay for Multi-Cancer Detection: An Interim Report from a Vietnamese Longitudinal Prospective Cohort Study of 2795 Participants.

The SPOT-MAS assay "Screening for the Presence Of Tumor by Methylation And Size" detects the five most common cancers in Vietnam by evaluating circulating tumor DNA in the blood. Here, we validated its performance in a prospective multi-center clinical trial, K-DETEK. Our analysis of 2795 participants from 14 sites across Vietnam demonstrates its ability to detect cancers in asymptomatic individuals with a positive predictive value of 60%, with 83.3% accuracy in detecting tumor location. We present a case report to support further using SPOT-MAS as a complementary method to achieve early cancer detection and provide the opportunity for early treatment.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2.

Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1.

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

Performance of a targeted methylation-based multi-cancer early detection test by race and ethnicity.

Disparities in cancer screening and outcomes based on factors such as sex, socioeconomic status, and race and ethnicity in the United States are well documented. A blood-based multi-cancer early detection (MCED) test that detects a shared cancer signal across multiple cancer types and also predicts the cancer signal origin was developed and validated in the Circulating Cell-free Genome Atlas study (CCGA; NCT02889978). CCGA is a prospective, multicenter, case-control, observational study with longitudinal follow-up (overall N = 15,254). In this pre-specified, exploratory, descriptive analysis, test performance was evaluated among racial and ethnic groups. Overall, 4077 participants comprised the independent validation set with confirmed cancer status (cancer: n = 2823; non-cancer: n = 1254). Participants were stratified into the following racial/ethnic groups: Black (non-Hispanic), Hispanic (all races), Other (non-Hispanic), Other/unknown and White (non-Hispanic). Cancer and non-cancer participants were predominantly White (n = 2316, 82.0% and n = 996, 79.4%, respectively). Across groups, specificity for cancer signal detection ranged from 98.1% [n = 103; 95% CI: 93.2-99.5%] to 100% [n = 85; 95% CI: 95.7-100.0%]. The sensitivity for cancer signal detection across groups ranged from 43.9% [n = 57; 95% CI: 31.8-56.7%] to 63.0% [n = 192; 95% CI: 56.0-69.5%] and generally increased with clinical stage. The MCED test had consistently high specificity and similar sensitivity across racial and ethnic groups, though results are limited by sample size for some groups. Results support the broad applicability of this MCED test and clinical implementation on a population scale as a complement to standard screening.

Clinical validation of translational antibody PBPK model using tissue distribution data generated with 89Zr-immuno-PET imaging.

The main objective of this manuscript was to validate the ability of the monoclonal antibody physiologically-based pharmacokinetic (PBPK) model to predict tissue concentrations of antibodies in the human. To accomplish this goal, preclinical and clinical tissue distribution and positron emission tomography imaging data generated using zirconium-89 (89Zr) labeled antibodies were obtained from the literature. First, our previously published translational PBPK model for antibodies was expanded to describe the whole-body biodistribution of 89Zr labeled antibody and the free 89Zr, as well as residualization of free 89Zr. Subsequently, the model was optimized using mouse biodistribution data, where it was observed that free 89Zr mainly residualizes in the bone and the extent of antibody distribution in certain tissues (e.g., liver and spleen) may be altered by labeling with 89Zr. The mouse PBPK model was scaled to rat, monkey, and human by simply changing the physiological parameters, and a priori simulations performed by the model were compared with the observed PK data. It was found that model predicted antibody PK in majority of the tissues in all the species superimposed over the observed data, and the model was also able to predict the PK of antibody in human tissues reasonably well. As such, the work presented here provides unprecedented evaluation of the antibody PPBK model for its ability to predict tissue PK of antibodies in the clinic. This model can be used for preclinical-to-clinical translation of antibodies and for prediction of antibody concentrations at the site-of-action in the clinic.

Analytical and Clinical Validation of Assays for Volumetric Absorptive Microsampling (VAMS) of Drugs in Different Blood Matrices: A Literature Review.

Volumetric absorptive microsampling (VAMS) is the newest and most promising sample-collection technique for quantitatively analyzing drugs, especially for routine therapeutic drug monitoring (TDM) and pharmacokinetic studies. This technique uses an absorbent white tip to absorb a fixed volume of a sample (10-50 µL) within a few seconds (2-4 s), is more flexible, practical, and more straightforward to be applied in the field, and is probably more cost-effective than conventional venous sampling (CVS). After optimization and validation of an analytical method of a drug taken by VAMS, a clinical validation study is needed to show that the results by VAMS can substitute what is gained from CVS and to justify implementation in routine practice. This narrative review aimed to assess and present studies about optimization and analytical validation of assays for drugs taken by VAMS, considering their physicochemical drug properties, extraction conditions, validation results, and studies on clinical validation of VAMS compared to CVS. The review revealed that the bio-analysis of many drugs taken with the VAMS technique was optimized and validated. However, only a few clinical validation studies have been performed so far. All drugs that underwent a clinical validation study demonstrated good agreement between the two techniques (VAMS and CVS), but only by Bland-Altman analysis. Only for tacrolimus and mycophenolic acid were three measurements of agreement evaluated. Therefore, VAMS can be considered an alternative to CVS in routine practice, especially for tacrolimus and mycophenolic acid. Still, more extensive clinical validation studies need to be performed for other drugs.

The development of "automated visual evaluation" for cervical cancer screening: The promise and challenges in adapting deep-learning for clinical testing: Interdisciplinary principles of automated visual evaluation in cervical screening.

There is limited access to effective cervical cancer screening programs in many resource-limited settings, resulting in continued high cervical cancer burden. Human papillomavirus (HPV) testing is increasingly recognized to be the preferable primary screening approach if affordable due to superior long-term reassurance when negative and adaptability to self-sampling. Visual inspection with acetic acid (VIA) is an inexpensive but subjective and inaccurate method widely used in resource-limited settings, either for primary screening or for triage of HPV-positive individuals. A deep learning (DL)-based automated visual evaluation (AVE) of cervical images has been developed to help improve the accuracy and reproducibility of VIA as assistive technology. However, like any new clinical technology, rigorous evaluation and proof of clinical effectiveness are required before AVE is implemented widely. In the current article, we outline essential clinical and technical considerations involved in building a validated DL-based AVE tool for broad use as a clinical test.

Clinical utiliy of a model-based piperacillin dose in neonates with early-onset sepsis.

AIMS: Early-onset sepsis (EOS) is a common disease in neonates with a high morbidity and mortality rate. Piperacillin/tazobactam has been used extensively and empirically for EOS treatment without clinically validated dosing regimens, although the population pharmacokinetics (PPK) of piperacillin in neonates has been reported. Therefore, we wanted to study the effectiveness and tolerance of a PPK model-based dosing regimen of piperacillin/tazobactam in EOS patients. METHODS: A prospective, single-centre, phase II clinical study of piperacillin/tazobactam in neonates with EOS was conducted. The dosing regimen (90 mg·kg-1 , q8h) was determined based on a previous piperacillin PPK model in young infants using NONMEM v7.4. The pharmacodynamics (PD) target (70%fT > MIC, free drug concentration above MIC during 70% of the dosing interval) attainment was calculated using NONMEM combined with an opportunistic sampling design. The clinical treatment data were collected. RESULTS: A total of 52 neonates were screened and 49 neonates completed their piperacillin/tazobactam treatment course and were included in this analysis. The median (range) values of postmenstrual age were 33.57 (range 26.14-41.29) weeks. Forty-seven (96%) neonates reached their PD target. Eight (16%) neonates experienced treatment failure clinically. The mean (SD, range) duration of treatment and length of hospitalization were 100.1 (62.2, 36.2-305.8) hours and 31 (30, 5-123) days. There were no obvious adverse events and no infection-related deaths occurred in the first month of life. CONCLUSIONS: A model-based dosing regimen of piperacillin/tazobactam was evaluated clinically, was tolerated well and was determined to be effective for EOS treatment.

Clinical validation of a multiplex droplet digital PCR for diagnosing suspected bloodstream infections in ICU practice: a promising diagnostic tool.

BACKGROUND: Droplet digital PCR (ddPCR) has emerged as a promising tool of pathogen detection in bloodstream infections (BSIs) in critical care medicine. However, different ddPCR platforms have variable sensitivity and specificity for diverse microorganisms at various infection sites. There is still a lack of prospective clinical studies aimed at validating and interpreting the discrepant ddPCR results for diagnosing BSI in intensive care unit (ICU) practice. METHODS: A prospective diagnostic study of multiplex ddPCR panels was conducted in a general ICU from May 21, 2021, to December 22, 2021. Paired blood cultures (BCs) and ddPCRs (2.5 h) were obtained synchronously to detect the 12 most common BSI pathogens and three antimicrobial resistance (AMR) genes. Firstly, ddPCR performance was compared to definite BSI. Secondly, clinical validation of ddPCR was compared to composite clinical diagnosis. Sensitivity, specificity, and positive and negative predictive values were calculated. Thirdly, the positive rate of AMR genes and related analysis was presented. RESULTS: A total of 438 episodes of suspected BSIs occurring in 150 critical patients were enrolled. BC and ddPCR were positive for targeted bacteria in 40 (9.1%) and 180 (41.1%) cases, respectively. There were 280 concordant and 158 discordant. In comparison with BCs, the sensitivity of ddPCR ranged from 58.8 to 86.7% with an aggregate of 72.5% in different species, with corresponding specificity ranging from 73.5 to 92.2% with an aggregate of 63.1%. Furthermore, the rate of ddPCR+/BC- results was 33.6% (147/438) with 87.1% (128 of 147) cases was associated with probable (n = 108) or possible (n = 20) BSIs. When clinically diagnosed BSI was used as true positive, the final sensitivity and specificity of ddPCR increased to 84.9% and 92.5%, respectively. In addition, 40 blaKPC, 3blaNDM, and 38 mecA genes were detected, among which 90.5% were definitely positive for blaKPC. Further, 65.8% specimens were predicted to be mecA-positive in Staphylococcus sp. according to all microbiological analysis. CONCLUSIONS: The multiplexed ddPCR is a flexible and universal platform, which can be used as an add-on complementary to conventional BC. When combined with clinical infection evidence, ddPCR shows potential advantages for rapidly diagnosing suspected BSIs and AMR genes in ICU practice.

Biomarkers for Early Cancer Diagnosis: Prospects for Success through the Lens of Tumor Genetics.

Thousands of candidate cancer biomarkers have been proposed, but so far, few are used in cancer screening. Failure to implement these biomarkers is attributed to technical and design flaws in the discovery and validation phases, but a major obstacle stems from cancer biology itself. Oncogenomics has revealed broad genetic heterogeneity among tumors of the same histology and same tissue (or organ) from different patients, while tumors of different tissue origins also share common genetic mutations. Moreover, there is wide intratumor genetic heterogeneity among cells within any single neoplasm. These findings seriously limit the prospects of finding a single biomarker with high specificity for early cancer detection. Current research focuses on developing biomarker panels, with data assessment by machine-learning algorithms. Whether such approaches will overcome the inherent limitations posed by tumor biology and lead to tests with true clinical value remains to be seen.

Assessing a New Prescreening Score for the Simplified Evaluation of the Clinical Quality and Relevance of eHealth Apps: Instrument Validation Study.

BACKGROUND: In 2020, more than 250 eHealth solutions were added to app stores each day, or 90,000 in the year; however, the vast majority of these solutions have not undergone clinical validation, their quality is unknown, and the user does not know if they are effective and safe. We sought to develop a simple prescreening scoring method that would assess the quality and clinical relevance of each app. We designed this tool with 3 health care stakeholder groups in mind: eHealth solution designers seeking to evaluate a potential competitor or their own tool, investors considering a fundraising candidate, and a hospital clinician or IT department wishing to evaluate a current or potential eHealth solution. OBJECTIVE: We built and tested a novel prescreening scoring tool (the Medical Digital Solution scoring tool). The tool, which consists of 26 questions that enable the quick assessment and comparison of the clinical relevance and quality of eHealth apps, was tested on 68 eHealth solutions. METHODS: The Medical Digital Solution scoring tool is based on the 2021 evaluation criteria of the French National Health Authority, the 2022 European Society of Medical Oncology recommendations, and other provided scores. We built the scoring tool with patient association and eHealth experts and submitted it to eHealth app creators, who evaluated their apps via the web-based form in January 2022. After completing the evaluation criteria, their apps obtained an overall score and 4 categories of subscores. These criteria evaluated the type of solution and domain, the solution's targeted population size, the level of clinical assessment, and information about the provider. RESULTS: In total, 68 eHealth solutions were evaluated with the scoring tool. Oncology apps (22%, 20/90) and general health solutions (23%, 21/90) were the most represented. Of the 68 apps, 32 (47%) were involved in remote monitoring by health professionals. Regarding clinical outcomes, 5% (9/169) of the apps assessed overall survival. Randomized studies had been conducted for 21% (23/110) of the apps to assess their benefit. Of the 68 providers, 38 (56%) declared the objective of obtaining reimbursement, and 7 (18%) out of the 38 solutions seeking reimbursement were assessed as having a high probability of reimbursement. The median global score was 11.2 (range 4.7-17.4) out of 20 and the distribution of the scores followed a normal distribution pattern (Shapiro-Wilk test: P=.33). CONCLUSIONS: This multidomain prescreening scoring tool is simple, fast, and can be deployed on a large scale to initiate an assessment of the clinical relevance and quality of a clinical eHealth app. This simple tool can help a decision-maker determine which aspects of the app require further analysis and improvement.

Clinical validation of the infant-driven feeding scales© in Turkey.

BACKGROUND: Supporting the development of feeding skills among preterm infants is an important component of neonatal care. The selection of appropriate and supportive feeding interventions begins with a comprehensive assessment of the infant's skills. PURPOSE: This study aimed to adapt the Infant-Driven Feeding Scales© (IDFS) to the Turkish language. METHODS: This was a methodological, observational, single-center cross-sectional study. The study included 80 infants born at a gestational age ≥ 32 weeks, consecutively admitted to a tertiary Neonatal Intensive Care Unit (NICU). Research data were collected using a premature infant descriptive information form (IDIF), IDFS, and LATCH Score for Breastfeeding Assessment. For the Turkish validity-reliability of the IDF, the translate-back translate method was used with the content validity index (CVI) assessed. RESULTS: The scale had CVI values between 0.90 and 1.00 with a mean CVI = 0.96. For measures 1 and 2, there were significant positive and high-level correlations between IFDS-R and IFDS-Q correlation values (r = 0.553-0.958; p = 0.001) and significant negative, low-level correlations between IFDS-R and IFDS-Q with the LATCH scale (r = 0.439-0.532; p = 0.001). According to inter-observer compatibility analyses, the kappa value was 0.94-1.00 for the first measure and 0.96-1.00 for the second measure (p = 0.001). There were negative significant correlations between IDFS-R points with gestational age and postmenstrual age (PMA) (p = 0.001), and gestational age and PMA were explanatory factors for 13.8% of IDFS-R points (F = 7.30, p = 0.001). CONCLUSIONS: The IDFS is recommended for use as a valid and reliable tool to ease the safe and successful development of oral feeding skills in preterm infants and to plan evidence-based interventions. IMPLICATIONS FOR PRACTICE: The IDFS appears to be a beneficial measurement device for use in assessing the state of readiness of preterm infants for oral feeding and for early determination of risks that may occur due to delayed feeding independence of infants.

Clinical and analytical evaluation of the RealTime High Risk HPV assay in Colli-Pee collected first-void urine using the VALHUDES protocol.

OBJECTIVE: Urine self-sampling has gained increasing interest for cervical cancer screening. In contrast to analytical performance, little information is available regarding the clinical accuracy for high-risk Human Papillomavirus (hrHPV) testing on urine. METHODS: VALHUDES is a diagnostic test accuracy study comparing clinical accuracy to detect high-grade cervical precancer (CIN2+) of HPV testing on self-collected compared to clinician-collected samples (NCT03064087). Disease outcome was assessed by colposcopy and histology. The Abbott RealTime High Risk HPV assay performance was evaluated on Colli-Pee collected first-void urine with cervical outcomes as comparator. RESULTS: As no assay cut-off for urine has been clinically validated, we used the predefined cut-off for cervical samples (CN ≤ 32). Using this cut-off, hrHPV testing was similarly sensitive (relative sensitivity 0.95; 95% CI: 0.88-1.01) and specific (relative specificity 1.03; 95% CI: 0.95-1.13) for detection of CIN2+ compared to testing cervical samples. In the subgroup of women of 30 years and older, similar relative sensitivity (0.97; 95% CI: 0.89-1.05) and specificity (1.02; 95% CI: 0.93-1.12) was found. Additionally, an exploratory cut-off (CN ≤ 33.86) was defined which further improved sensitivity and analytical test performance. CONCLUSION: HrHPV-DNA based PCR testing on home-collected first-void urine has similar accuracy for detecting CIN2+ compared to cervical samples taken by a clinician.

Cardiothoracic ratio measurement using artificial intelligence: observer and method validation studies.

BACKGROUND: Artificial Intelligence (AI) is a promising tool for cardiothoracic ratio (CTR) measurement that has been technically validated but not clinically evaluated on a large dataset. We observed and validated AI and manual methods for CTR measurement using a large dataset and investigated the clinical utility of the AI method. METHODS: Five thousand normal chest x-rays and 2,517 images with cardiomegaly and CTR values, were analyzed using manual, AI-assisted, and AI-only methods. AI-only methods obtained CTR values from a VGG-16 U-Net model. An in-house software was used to aid the manual and AI-assisted measurements and to record operating time. Intra and inter-observer experiments were performed on manual and AI-assisted methods and the averages were used in a method variation study. AI outcomes were graded in the AI-assisted method as excellent (accepted by both users independently), good (required adjustment), and poor (failed outcome). Bland-Altman plot with coefficient of variation (CV), and coefficient of determination (R-squared) were used to evaluate agreement and correlation between measurements. Finally, the performance of a cardiomegaly classification test was evaluated using a CTR cutoff at the standard (0.5), optimum, and maximum sensitivity. RESULTS: Manual CTR measurements on cardiomegaly data were comparable to previous radiologist reports (CV of 2.13% vs 2.04%). The observer and method variations from the AI-only method were about three times higher than from the manual method (CV of 5.78% vs 2.13%). AI assistance resulted in 40% excellent, 56% good, and 4% poor grading. AI assistance significantly improved agreement on inter-observer measurement compared to manual methods (CV; bias: 1.72%; - 0.61% vs 2.13%; - 1.62%) and was faster to perform (2.2 ± 2.4 secs vs 10.6 ± 1.5 secs). The R-squared and classification-test were not reliable indicators to verify that the AI-only method could replace manual operation. CONCLUSIONS: AI alone is not yet suitable to replace manual operations due to its high variation, but it is useful to assist the radiologist because it can reduce observer variation and operation time. Agreement of measurement should be used to compare AI and manual methods, rather than R-square or classification performance tests.