Criteria2Query 3.0: Leveraging generative large language models for clinical trial eligibility query generation.

OBJECTIVE: Automated identification of eligible patients is a bottleneck of clinical research. We propose Criteria2Query (C2Q) 3.0, a system that leverages GPT-4 for the semi-automatic transformation of clinical trial eligibility criteria text into executable clinical database queries. MATERIALS AND METHODS: C2Q 3.0 integrated three GPT-4 prompts for concept extraction, SQL query generation, and reasoning. Each prompt was designed and evaluated separately. The concept extraction prompt was benchmarked against manual annotations from 20 clinical trials by two evaluators, who later also measured SQL generation accuracy and identified errors in GPT-generated SQL queries from 5 clinical trials. The reasoning prompt was assessed by three evaluators on four metrics: readability, correctness, coherence, and usefulness, using corrected SQL queries and an open-ended feedback questionnaire. RESULTS: Out of 518 concepts from 20 clinical trials, GPT-4 achieved an F1-score of 0.891 in concept extraction. For SQL generation, 29 errors spanning seven categories were detected, with logic errors being the most common (n = 10; 34.48 %). Reasoning evaluations yielded a high coherence rating, with the mean score being 4.70 but relatively lower readability, with a mean of 3.95. Mean scores of correctness and usefulness were identified as 3.97 and 4.37, respectively. CONCLUSION: GPT-4 significantly improves the accuracy of extracting clinical trial eligibility criteria concepts in C2Q 3.0. Continued research is warranted to ensure the reliability of large language models.

Clinical utility of plasma Aß42/40 ratio by LC-MS/MS in Alzheimer's disease assessment.

Introduction: Plasma Aß42/40 ratio can help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear. Methods: Aß42/40 ratio was measured by LC-MS/MS for 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and for 6,192 consecutive clinical specimens submitted for Aß42/40 testing. Results: High diagnostic sensitivity and negative predictive value (NPV) for Aß-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aß42/40 values for individuals with positive vs. negative Aß-PET results. Assuming a moderate prevalence of Aß-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%. Conclusion: High-throughput plasma Aß42/40 LC-MS/MS assays can help identify patients with low likelihood of AD pathology, which can reduce PET evaluations, allowing for cost savings.

The usage of population and disease registries as pre-screening tools for clinical trials, a systematic review.

OBJECTIVE: This systematic review aims to outline the use of population and disease registries for clinical trial pre-screening. MATERIALS AND METHODS: The search was conducted in the time period of January 2014 to December 2022 in three databases: MEDLINE, Embase, and Web of Science Core Collection. References were screened using the Rayyan software, firstly based on titles and abstracts only, and secondly through full text review. Quality of the included studies was assessed using the List of Included Studies and quality Assurance in Review tool, enabling inclusion of publications of only moderate to high quality. RESULTS: The search originally identified 1430 citations, but only 24 studies were included, reporting the use of population and/or disease registries for trial pre-screening. Nine disease domains were represented, with 54% of studies using registries based in the USA, and 62.5% of the studies using national registries. Half of the studies reported usage for drug trials, and over 478,679 patients were identified through registries in this review. Main advantages of the pre-screening methodology were reduced financial burden and time reduction. DISCUSSION AND CONCLUSION: The use of registries for trial pre-screening increases reproducibility of the pre-screening process across trials and sites, allowing for implementation and improvement of a quality assurance process. Pre-screening strategies seem under-reported, and we encourage more trials to use and describe their pre-screening processes, as there is a need for standardized methodological guidelines.

Leveraging machine learning for effective child maltreatment prevention: A case study of home visiting service assessments.

BACKGROUND: Early identification of children and families who may benefit from support is crucial for implementing strategies that can prevent the onset of child maltreatment. Predictive risk modeling (PRM) may offer valuable and efficient enhancements to existing risk assessment techniques. OBJECTIVE: To evaluate the PRM's effectiveness against the existing assessment tool in identifying children and families needing home visiting services. PARTICIPANTS AND SETTING: Children born in hospitals affiliated with the Bridges Maternal Child Health Network in Orange County, California, from 2011 to 2016 (N = 132,216). METHODS: We developed a PRM tool by integrating a machine learning algorithm with a linked dataset of birth records and child protection system (CPS) records. To align with the existing assessment tool (baseline model), we limited the predicting features to the information used by the existing tool. The need for home visiting services was measured by substantiated maltreatment allegation reported during the first three years of the child's life. RESULTS: Of the children born in Bridges Network hospitals between 2011 and 2016, 2.7 % experienced substantiated maltreatment allegations by the age of three. Within the top 30 % of children with high-risk scores, the PRM tool outperformed the baseline model, accurately identifying 75.3 %-84.1 % of all children who would experience maltreatment substantiation, surpassing the baseline model's performance of 46.2 %. CONCLUSIONS: Our study underscores the potential of PRM in enhancing the risk assessment tool used by a prevention program in a child welfare center in California. The findings provide valuable insights to practitioners interested in utilizing data for PRM development, highlighting the potential of machine learning algorithms to generate accurate predictions and inform targeted preventive services.

Development and Validation of a Risk Score for Mild Cognitive Impairment in Individuals with Type 2 Diabetes in China: A Practical Cognitive Prescreening Tool.

Aim: Numerous evidence suggests that diabetes increases the risk of cognitive impairment. This study aimed to develop and validate a multivariable risk score model to identify mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: This cross-sectional study included 1256 inpatients (age: 57.5 ± 11.2 years) with T2DM in a tertiary care hospital in China. MCI was diagnosed according to the criteria recommended by the National Institute on Aging-Alzheimer's Association Workgroup, and a MoCA score of 19-25 indicated MCI. Participants were randomly allocated into the derivation and validation sets at 7:3 ratio. Logistic regression models were used to identify predictors for MCI in the derivation set. A scoring system based on the predictors' beta coefficient was developed. Predictive ability of the risk score was tested by discrimination and calibration methods. Results: Totally 880 (285 with MCI, 32.4%) and 376 (167 with MCI, 33.8%) patients were allocated in the derivation and validation set, respectively. Age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease were identified as predictors for MCI and constituted the risk score. The AUCs (95% CI) of the risk score were 0.751 (0.717, 0.784) in derivation set and 0.776 (0.727, 0.824) in validation set. The risk score showed good apparent calibration of observed and predicted MCI probabilities and was capable of stratifying individuals into 3 risk categories by two cut-off points (low risk: ≤ 3, medium risk: 4-13, and high risk ≥ 14). Conclusion: The risk score based on age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease can effectively assess MCI risk in adults with T2DM at different age. It can serve as a practical prescreening tool for early detection of MCI in daily diabetes care.

Osteopenia and Osteoporosis Screening Detection: Calcaneal Quantitative Ultrasound with and without Calibration Factor Comparison to Gold Standard Dual X-ray Absorptiometry.

BACKGROUND: osteoporosis is a worldwide major health problem that normally diagnosed in advanced stages. So, an early detection at preclinical stage is now an interesting issue. A key factor to early diagnosis the disease is the used of noninvasive bone densitometry. Dual energy x-ray absorptiometry (DXA) is the gold standard techniques for the proposed. However, the high cost, non-widely available and exposed to ionizing radiation are still a drawback of the machine. Therefore, a cheaper, smaller and non-ionizing device such quantitative ultrasound (QUS) is now a favor alternative method, but the possibility of used QUS measurement instead of DXA is still limited due to their uncertainties. So, the aim of our study was to calibrated the QUS with the DXA to allowing the possible to establish a calibration factor (CF) to improve the measured value closer to the standard method. METHODOLOGY: 135 healthy men and women aged 30-88 years were recruited for lumbar spine/femoral neck DXA and calcaneal QUS scanning. The Pearson's correlation between T- and Z-score from the two systems were studied. Moreover, the sensitivity, specificity and percentage of diagnosed accuracy for both with and without CF were calculated. RESULTS: The significant correlation between the two systems showed a positive trajectory in highly correlation (r = 0.784-0.899). Analyses showed a higher sensitivity, specificity and reduced the misdiagnosed rates when applied the CF in QUS values. CONCLUSIONS: QUS results showed a significantly correlated with DXA results for both lumbar spine and femoral neck sites with some percentage differences. These differences can be reduced by applied an individual specific machine CF to improve a QUS results. As identification of high risk of osteopenia and osteoporosis to reduce the demand of DXA propose, using a QUS alternative method can be a reliable that provide a cheaper and lack of ionizing radiation.

Screening for contamination levels of select organic environmental chemicals in medical supplies used for human specimen collection.

Trace-level analysis of environmental chemicals in human specimens can be compromised by contamination introduced during sample collection and storage. Sampling devices and tools can be a source of contamination by plasticizers, additives and antimicrobials, which warrants the need for pre-screening of these products prior to use. In this study, we determined leaching of 121 environmental chemicals in 10% and 100% methanol from 24 types of human specimen collection and storage devices. Cryovials, serum tubes, cups, syringes, transfer pipettes, and gloves -commonly used for the collection of blood, urine, breast milk and stools - were screened for the presence of plasticizers, environmental phenols, and pesticides. Measurable levels of mono-ethyl phthalate (mEP) and triethyl phosphate (TEP) were leached from vials, plastic storage bags, gloves, and diapers, and parabens were leached from collection bottles, at amounts exceeding 100 ng/device. The amount leached from the devices varied depending on the lot numbers of the same product type. Storage time and temperature were found to influence the leaching rate of chemicals, with increased levels observed following prolonged storage and at high temperatures. The study underscores the importance of pre-screening for contamination in devices used for collection and storage of human specimens for biomonitoring studies.

Effectiveness of Carboplatin-Prescreening Intradermal Skin Tests to Reduce Unanticipated Immediate Hypersensitivity Reactions: A Comparative Study.

BACKGROUND: Carboplatin administration poses a risk of immediate hypersensitivity reactions (IHRs) that tend to increase with repeated administration and are mostly IgE-mediated. OBJECTIVE: This study evaluated the usefulness of carboplatin-prescreening intradermal skin tests (IDTs). METHODS: Carboplatin-prescreening IDTs were routinely conducted in patients with a history of receiving six or more carboplatin cycles beginning in January 2021. The primary objective was to assess disparities in the incidence of unanticipated IHRs to carboplatin administration. We compared patients in the intervention group (from 2021 to 2022) and those who did not undergo prescreening IDTs under the same conditions (preintervention group, from 2019 to 2020). Secondary objectives included evaluating the sensitivity and specificity of the prescreening IDT and the incidence of carboplatin IHR according to the number of infusion cycles. RESULTS: The intervention group was composed of 67 patients who were administered 347 carboplatin cycles whereas the preintervention group included 96 patients who were administered 464 carboplatin cycles. The risk of unanticipated carboplatin IHRs decreased by 83.2% in the intervention group compared with results in the preintervention group (preintervention group, 3.45%, n = 16 vs intervention group, 0.58%, n = 2; P = .005). The prescreening IDT showed a sensitivity and specificity of 77.78% and 99.41%, respectively. The risk of newly developed IHRs based on the number of carboplatin cycles was less than 1% (cycles 1-5), 2.11% (cycle 6), 3.90% (cycles 7-12), 2.90% (cycles 13-18), and 0.74% (cycles 19 and greater), respectively. CONCLUSIONS: Initiating carboplatin-prescreening IDTs from the seventh cycle on significantly reduced the risk of unanticipated IHRs.

Statistical considerations for some issues in clinical bridging studies evaluating companion diagnostic devices.

An in vitro diagnostic device (IVD) that is essential for the safe and effective use of a corresponding therapeutic product is commonly referred to as companion diagnostic device. Clinical trials using companion diagnostic devices (tests) together with therapies can yield the information necessary to address whether both products are safe and effective. A clinical trial ideally assesses safety and effectiveness of a therapy, where the clinical trial enrolls subjects based on the final market ready companion diagnostic test (CDx). However, such a requirement may be difficult to accomplish or impractical to achieve at the time of the clinical trial enrollment, due to unavailability of the CDx. Instead, clinical trial assay(s) (CTA), which are not the final marketable product, are often used in enrollment of patients in a clinical trial. When CTA is used for subject enrollment, a clinical bridging study provides a mechanism to bridge the clinical efficacy of the therapeutic product from CTA to CDx. This manuscript reviews some issues and challenges commonly associated with clinical bridging studies, including missing data, use of local tests for enrollment, prescreening before enrollment, and evaluation of CDx for low positive rate biomarkers, with particular focus on clinical trials using a binary endpoint and provide alternative statistical methodologies to assess effectiveness of CDx.

Patient Health Questionnaire-9 Item Pairing Predictiveness for Prescreening Depressive Symptomatology: Machine Learning Analysis.

BACKGROUND: Anhedonia and depressed mood are considered the cardinal symptoms of major depressive disorder. These are the first 2 items of the Patient Health Questionnaire (PHQ)-9 and comprise the ultrabrief PHQ-2 used for prescreening depressive symptomatology. The prescreening performance of alternative PHQ-9 item pairings is rarely compared with that of the PHQ-2. OBJECTIVE: This study aims to use machine learning (ML) with the PHQ-9 items to identify and validate the most predictive 2-item depressive symptomatology ultrabrief questionnaire and to test the generalizability of the best pairings found on the primary data set, with 6 external data sets from different populations to validate their use as prescreening instruments. METHODS: All 36 possible PHQ-9 item pairings (each yielding scores of 0-6) were investigated using ML-based methods with logistic regression models. Their performances were evaluated based on the classification of depressive symptomatology, defined as PHQ-9 scores ≥10. This gave each pairing an equal opportunity and avoided any bias in item pairing selection. RESULTS: The ML-based PHQ-9 items 2 and 4 (phq2&4), the depressed mood and low-energy item pairing, and PHQ-9 items 2 and 8 (phq2&8), the depressed mood and psychomotor retardation or agitation item pairing, were found to be the best on the primary data set training split. They generalized well on the primary data set test split with area under the curves (AUCs) of 0.954 and 0.946, respectively, compared with an AUC of 0.942 for the PHQ-2. The phq2&4 had a higher AUC than the PHQ-2 on all 6 external data sets, and the phq2&8 had a higher AUC than the PHQ-2 on 3 data sets. The phq2&4 had the highest Youden index (an unweighted average of sensitivity and specificity) on 2 external data sets, and the phq2&8 had the highest Youden index on another 2. The PHQ-2≥2 cutoff also had the highest Youden index on 2 external data sets, joint highest with the phq2&4 on 1, but its performance fluctuated the most. The PHQ-2≥3 cutoff had the highest Youden index on 1 external data set. The sensitivity and specificity achieved by the phq2&4 and phq2&8 were more evenly balanced than the PHQ-2≥2 and ≥3 cutoffs. CONCLUSIONS: The PHQ-2 did not prove to be a more effective prescreening instrument when compared with other PHQ-9 item pairings. Evaluating all item pairings showed that, compared with alternative partner items, the anhedonia item underperformed alongside the depressed mood item. This suggests that the inclusion of anhedonia as a core symptom of depression and its presence in ultrabrief questionnaires may be incompatible with the empirical evidence. The use of the PHQ-2 to prescreen for depressive symptomatology could result in a greater number of misclassifications than alternative item pairings.

To prescreen or not to prescreen for broadly neutralizing antibody sensitivity in HIV cure-related trials.

The use of broadly neutralizing antibodies (bNAbs) as a cure-related research strategy for human immunodeficiency virus (HIV) has gained attention from the scientific community. bNAbs are specialized antibodies that target HIV-1 by binding to proteins on the surface of the virus, preventing the infection of human cells. In HIV-1 clinical studies assessing the use of bNAbs, it has been common practice to prescreen potential participants for bNAb sensitivity. However, the use of pre-screening in HIV-1 bNAb clinical trials is a topic of ongoing debate, with regard to its potential benefits and limitations. In this paper, we examine the possible benefits and limitations of pre-screening for bNAb sensitivity in HIV-1 cure-related studies, and suggest alternative methods which may be more effective or efficient at saving costs and time. Ultimately, the decision to use pre-screening in HIV-1 bNAb clinical trials should be based on a careful assessment of the potential benefits and limitations of this approach, as well as the specific needs, goals, design, and population of the study in question.

Clinical utility of an antibody-free LC-MS method to detect brain amyloid deposition in cognitively unimpaired individuals from the screening visit of the A4 Study.

INTRODUCTION: This study explored the ability of plasma amyloid beta (Aß)42/Aß40 to identify brain amyloid deposition in cognitively unimpaired (CU) individuals. METHODS: Plasma Aß was quantified with an antibody-free high-performance liquid chromatography tandem mass spectrometry method from Araclon Biotech (ABtest-MS) in a subset of 731 CU individuals from the screening visit of the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study, to assess associations of Aß42/Aß40 with Aß positron emission tomography (PET). RESULTS: A model including Aß42/Aß40, age, apolipoprotein E ε4, and recruitment site identified Aß PET status with an area under the curve of 0.88 and an overall accuracy of 81%. A plasma-based pre-screening step could save up to 42% of the total number of Aß PET scans. DISCUSSION: ABtest-MS accurately identified brain amyloid deposition in a population of CU individuals, supporting its implementation in AD secondary prevention trials to reduce recruitment time and costs. Although a certain degree of heterogeneity is inherent to large and multicentric trials, ABtest-MS could be more robust to pre-analytical bias compared to other immunoprecipitation mass spectrometry methods. HIGHLIGHTS: Plasma amyloid beta (Aß)42/Aß40 accurately identified brain Aß deposition in cognitively unimpaired individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study.The inclusion of the recruitment site in the predictive models has a non-negligible effect.A plasma biomarker-based model could reduce recruitment costs in Alzheimer's disease secondary prevention trials.Antibody-free liquid chromatography mass spectrometry methods may be more robust to pre-analytical variability than other platforms.

Artificial Intelligence-Aided Diagnosis Solution by Enhancing the Edge Features of Medical Images.

Bone malignant tumors are metastatic and aggressive. The manual screening of medical images is time-consuming and laborious, and computer technology is now being introduced to aid in diagnosis. Due to a large amount of noise and blurred lesion edges in osteosarcoma MRI images, high-precision segmentation methods require large computational resources and are difficult to use in developing countries with limited conditions. Therefore, this study proposes an artificial intelligence-aided diagnosis scheme by enhancing image edge features. First, a threshold screening filter (TSF) was used to pre-screen the MRI images to filter redundant data. Then, a fast NLM algorithm was introduced for denoising. Finally, a segmentation method with edge enhancement (TBNet) was designed to segment the pre-processed images by fusing Transformer based on the UNet network. TBNet is based on skip-free connected U-Net and includes a channel-edge cross-fusion transformer and a segmentation method with a combined loss function. This solution optimizes diagnostic efficiency and solves the segmentation problem of blurred edges, providing more help and reference for doctors to diagnose osteosarcoma. The results based on more than 4000 osteosarcoma MRI images show that our proposed method has a good segmentation effect and performance, with Dice Similarity Coefficient (DSC) reaching 0.949, and show that other evaluation indexes such as Intersection of Union (IOU) and recall are better than other methods.

Clinical research staff perceptions on a natural language processing-driven tool for eligibility prescreening: An iterative usability assessment.

BACKGROUND: Participant recruitment is a barrier to successful clinical research. One strategy to improve recruitment is to conduct eligibility prescreening, a resource-intensive process where clinical research staff manually reviews electronic health records data to identify potentially eligible patients. Criteria2Query (C2Q) was developed to address this problem by capitalizing on natural language processing to generate queries to identify eligible participants from clinical databases semi-autonomously. OBJECTIVE: We examined the clinical research staff's perceived usability of C2Q for clinical research eligibility prescreening. METHODS: Twenty clinical research staff evaluated the usability of C2Q using a cognitive walkthrough with a think-aloud protocol and a Post-Study System Usability Questionnaire. On-screen activity and audio were recorded and transcribed. After every-five evaluators completed an evaluation, usability problems were rated by informatics experts and prioritized for system refinement. There were four iterations of system refinement based on the evaluation feedback. Guided by the Organizational Framework for Intuitive Human-computer Interaction, we performed a directed deductive content analysis of the verbatim transcriptions. RESULTS: Evaluators aged from 24 to 46 years old (33.8; SD: 7.32) demonstrated high computer literacy (6.36; SD:0.17); female (75 %), White (35 %), and clinical research coordinators (45 %). C2Q demonstrated high usability during the final cycle (2.26 out of 7 [lower scores are better], SD: 0.74). The number of unique usability issues decreased after each refinement. Fourteen subthemes emerged from three themes: seeking user goals, performing well-learned tasks, and determining what to do next. CONCLUSIONS: The cognitive walkthrough with a think-aloud protocol informed iterative system refinement and demonstrated the usability of C2Q by clinical research staff. Key recommendations for system development and implementation include improving system intuitiveness and overall user experience through comprehensive consideration of user needs and requirements for task completion.

A Tale of Two Institutions: COVID-19 Positive Rates in Asymptomatic Patients Pre-Screened for Spine Procedures and Surgeries in Los Angeles, California.

STUDY DESIGN: Retrospective cohort study. OBJECTIVES: The coronavirus disease (COVID-19), caused by the severe respiratory syndrome coronavirus 2 (SARS-CoV-2), has created an unprecedented global public health emergency. The aim of the current study was to report on COVID-19 rates in an asymptomatic population prior to undergoing spine procedures or surgeries at two large Los Angeles healthcare systems. METHODS: Elective spine procedures and surgeries from May 1, 2020 to January 31, 2021 were included. Results from SARS-CoV-2 virus RT-PCR nasopharyngeal testing within 72 hours prior to elective spine procedures were recorded. Los Angeles County COVID-19 rates were calculated using data sets from Los Angeles County Department of Public Health. Chi-squared test and Stata/IC were used for statistical analysis. RESULTS: A total of 4,062 spine procedures and surgeries were scheduled during this time period. Of these, 4,043 procedures and surgeries were performed, with a total of 19 patients testing positive. Nine positive patients were from UCLA, and 10 from USC. The overall rate of positive tests was low at .47% and reflected similarities with Los Angeles County COVID-19 rates over time. CONCLUSIONS: The current study shows that pre-procedure COVID-19 testing rates remains very low, and follows similar patterns of community rates. While pre-procedure testing increases the safety of elective procedures, universal COVID-19 pre-screening adds an additional barrier to receiving care for patients and increases cost of delivering care. A combination of pre-screening, pre-procedure self-quarantine, and consideration of overall community COVID-19 positivity rates should be further studied.

Self-performed Five Times Sit-To-Stand test at home as (pre-)screening tool for frailty in cancer survivors: Reliability and agreement assessment.

AIMS AND OBJECTIVES: The self-performance of a Five-Times-Sit-To-Stand (FTSTS)-test, without the usual supervision by a medical professional, provides valuable opportunities for clinical practice and research. This study aimed: (1) to determine the validity of the self-performed FTSTS test in comparison to a supervised reference test and (2) to determine the reliability of a self-performed FTSTS test by cancer survivors. BACKGROUND: Early detection of frailty in cancer survivors may enable prehabilitation interventions before surgery or intensive treatment, improving cancer outcomes. DESIGN: A repeated measures reliability and agreement study, with one week in between measures, was performed. METHODS: Cancer survivors (n = 151) performed two FTSTS tests themselves. One additional reference FTSTS test was supervised by a physical therapist. The intraclass correlation coefficient (ICC), structural error of measurement (SEM) and minimally important clinical difference (MID) were calculated comparing a self-performed FTSTS test to the reference test, and comparing two self-performed FTSTS tests. The Guidelines for Reporting Reliability and Agreement Studies (GRASS) have been used. RESULTS: Mean age of cancer survivors was 65.6 years (SD = 9.3), 54.6% were female, median time since diagnosis was 2 years [IQR = 1], and tumour type varied (e.g., breast cancer (31.8%), prostate cancer (17.2%), gastrointestinal cancer (11.9%) and haematological cancer (11.9%)). Validity of the self-performed FTSTS test at home was acceptable in comparison with the reference test (ICC = .74; SEM = 3.2; MID = 3.6) as was the reliability of the self-performed FTSTS test (ICC = .70; SEM = 2.2; MID = 3.8). CONCLUSIONS: The self-performed FTSTS test is a valid and reliable measure to assess lower body function and has potential to be used as objective (pre-)screening tool for frailty in cancer survivors. RELEVANCE TO CLINICAL PRACTICE: The self-performed FTSTS test at home may indicate the cancer survivors in need of prehabilitation in advance of surgery or intensive treatment. The feasibility, short amount of time needed and potential cost-effectiveness of the self-performed FTSTS test can make it a valuable contribution to personalised care and precision medicine.

Clinical performance and robustness evaluation of plasma amyloid-ß42/40 prescreening.

INTRODUCTION: Further evidence is needed to support the use of plasma amyloid ß (Aß) biomarkers as Alzheimer's disease prescreening tools. This study evaluated the clinical performance and robustness of plasma Aß42 /Aß40 for amyloid positivity prescreening. METHODS: Data were collected from 333 BioFINDER and 121 Alzheimer's Disease Neuroimaging Initiative study participants. Risk and predictive values versus percentile of plasma Aß42 /Aß40 evaluated the actionability of plasma Aß42 /Aß40 , and simulations modeled the impact of potential uncertainties and biases. Amyloid PET was the brain amyloidosis reference standard. RESULTS: Elecsys plasma Aß42 /Aß40 could potentially rule out amyloid pathology in populations with low-to-moderate amyloid positivity prevalence. However, simulations showed small measurement or pre-analytical errors in Aß42 and/or Aß40 cause misclassifications, impacting sensitivity or specificity. The minor fold change between amyloid PET positive and negative cases explains the biomarkers low robustness. DISCUSSION: Implementing plasma Aß42 /Aß40 for routine clinical use may pose significant challenges, with misclassification risks. HIGHLIGHTS: Plasma Aß42 /Aß40 ruled out amyloid PET positivity in a setting of low amyloid-positive prevalence. Including (pre-) analytical errors or measurement biases caused misclassifications. Plasma Aß42 /Aß40 had a low inherent dynamic range, independent of analytical method. Other blood biomarkers may be easier to implement as robust prescreening tools.

Clinical utility of plasma Aß42/40 ratio by LC-MS/MS in Alzheimer's disease assessment.

INTRODUCTION: Plasma Aß42/40 ratio can be used to help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear. METHODS: Aß42/40 ratio was measured by LC-MS/MS in 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and 6,192 consecutive clinical specimens submitted for Aß42/40 testing. RESULTS: High diagnostic sensitivity and negative predictive value (NPV) for Aß-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aß42/40 values for individuals with positive vs negative Aß-PET results. Assuming a moderate prevalence of Aß-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%. DISCUSSION: Using high-throughput plasma Aß42/40 LC-MS/MS assays can help reduce PET evaluations in patients with low likelihood of AD pathology, allowing for cost savings.

The application value of the Modified Early Warning Score combined with age and injury site scores in the evaluation of injuries in emergency trauma patients.

Objective: To explore the application value of the Modified Early Warning Score (MEWS) combined with age and injury site scores in predicting the criticality of emergency trauma patients. Methods: The traditional MEWS was modified by combining it with age and injury site scores to form a new MEWS combined scoring standard. The clinical data were collected from a total of 372 trauma patients from the emergency department of the Nantong First People's Hospital between June and December 2019. A retrospective analysis was conducted, and the patients were scored using the MEWS combined with age and injury site scores. The patients were grouped according to their prognoses and clinical outcomes. A statistical analysis was conducted based on the ranges of the combined scores, and the results of the combined scores of the different groups were compared. Results: Among the 372 patients, the average score was 3.68 ± 1.25 points in the survival group, 8.33 ± 2.24 points in the death within 24 h group, and 8.38 ± 1.51 points in the death within 30 days of hospitalization group, and the differences were statistically significant (p < 0.05). The average score was 2.74 ± 0.69 points in the outpatient treatment group, 4.19 ± 0.72 points in the emergency stay group, 5.40 ± 0.70 points in the specialist inpatient group, 8.71 ± 2.31 points in the ICU group, and 7.82 ± 1.66 points in the specialist unplanned transfer to ICU group, with the differences between the groups being statistically significant (p < 0.05). The average length of hospital stay for patients with a joint score within the range of 6-8 points was 10.86 ± 2.47 days, with a direct ICU admission rate of 22.00% and an unplanned ICU admission rate of 16.00%. Patients with a joint score >8 points had an average length of hospital stay of 27.05 ± 4.85 days, with a direct ICU admission rate of 66.67% and an unplanned ICU admission rate of 33.33%. Conclusion: Age and injury site are important high-risk indicators for trauma assessment, and using them in combination with the MEWS could improve the assessment of emergency patients with trauma, increasing the accuracy of pre-screening triage and reducing rescue time. Therefore, this joint scoring method might be worthy of clinical promotion and application.

Prescreening of tumor samples for tumor-centric transcriptome analyses of lung adenocarcinoma.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) enables the systemic assessment of intratumoral heterogeneity within tumor cell populations and in diverse stromal cells of the tumor microenvironment. Gain of treatment resistance during tumor progression or drug treatment are important subjects of tumor-centric scRNA-seq analyses, which are hampered by scarce tumor cell portions. To guarantee the inclusion of tumor cells in the data analysis, we developed a prescreening strategy for lung adenocarcinoma. METHODS: We obtained candidate genes that were differentially expressed between normal and tumor cells, excluding stromal cells, from the scRNA-seq data. Tumor cell-specific expression of the candidate genes was assessed via real-time reverse transcription-polymerase chain reaction (RT-PCR) using lung cancer cell lines, normal vs. lung cancer tissues, and lymph node biopsy samples with or without metastasis. RESULTS: We found that CEA cell adhesion molecule 5 (CEACAM5) and high mobility group box 3 (HMGB3) were reliable markers for RT-PCR-based prescreening of tumor cells in lung adenocarcinoma. CONCLUSIONS: The prescreening strategy using CEACAM5 and HMGB3 expression facilitates tumor-centric scRNA-seq analyses of lung adenocarcinoma.