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Phase four of the Alzheimers Disease Neuroimaging Initiative (ADNI4) magnetic resonance imaging (MRI) protocols aim to maintain longitudinal consistency across two decades of data acquisition, while adopting new technologies. Here we describe and justify the studys design and targeted biomarkers. The ADNI4 MRI protocol includes nine MRI sequences. Some sequences require the latest hardware and software system upgrades and are continuously rolled out as they become available at each site. The main sequence additions/changes in ADNI4 are: (1) compressed sensing (CS) T1-weighting, (2) pseudo-continuous arterial spin labeling (ASL) on all three vendors (GE, Siemens, Philips), (3) multiple-post-labeling-delay ASL, (4) 1 mm3 isotropic 3D fluid-attenuated inversion recovery, and (5) CS 3D T2-weighted. ADNI4 aims to help the neuroimaging community extract valuable imaging biomarkers and provide a database to test the impact of advanced imaging strategies on diagnostic accuracy and disease sensitivity among individuals lying on the cognitively normal to impaired spectrum. HIGHLIGHTS: A summary of MRI protocols for phase four of the Alzheimers Disease Neuroimaging Initiative (ADNI 4). The design and justification for the ADNI 4 MRI protocols. Compressed sensing and multi-band advances have been applied to improve scan time. ADNI4 protocols aim to streamline safety screening and therapy monitoring. The ADNI4 database will be a valuable test bed for academic research.

Magnetic Resonance Imaging or MRI is a valuable diagnostic tool using strong magnets and radio waves to produce detailed three dimensional images of particularly soft tissue organs. MRI accidents are the least frequent among all medical accidents. However, if safety guidelines are not strictly followed, MRI can be dangerous for both the patient and staff. Strict protocols, patient screening and both patient and staff education are critical to ensure patient and staff safety. This article reviews risks related to MRI scanning and highlights the key information that all staff need to be vigilant about to ensure the safety of all people in the MRI environment. [ABSTRACT FROM AUTHOR]

Background: Patients with ileostomies may develop intestinal failure and high stoma output. Chyme reinfusion (CR) was considered an alternative to parenteral nutrition. The Insides System, a closed system for CR, was introduced to allow complete patient control and management. In this paper the authors used the system for 3 years and aimed to describe its use in clinical practice. Methods: A cohort of patients considered for the system was included in the study. They were followed from screening until discontinuation of the system. Data on health-related quality of life were collected, and journal audits were performed. Results: A total of 14 patients were included in the results. Two did not receive the system, four answered the questionnaires one time or less and four had the system discontinued before discharge. Answers from the remaining four patients were inconclusive. The audit revealed that evaluating patient compliance and motivation was key before introducing the system. With the system in place, pain and discomfort levels were found to be important for the patients. Conclusion: The Insides System was feasible in a clinical practice setting. However, comprehensive screening was necessary, with specialised nurses playing a key role. [ABSTRACT FROM AUTHOR]

BACKGROUND: This study investigated the potential of phosphorylated plasma Tau217 ratio (pTau217R) and plasma amyloid beta (Aβ) 42/Aβ40 in predicting brain amyloid levels measured by positron emission tomography (PET) Centiloid (CL) for Alzheimer's disease (AD) staging and screening. METHODS: Quantification of plasma pTau217R and Aβ42/Aβ40 employed immunoprecipitation‐mass spectrometry. CL prediction models were developed on a cohort of 904 cognitively unimpaired, preclinical and early AD subjects and validated on two independent cohorts. RESULTS: Models integrating pTau217R outperformed Aβ42/Aβ40 alone, predicting amyloid levels up to 89.1 CL. High area under the receiver operating characteristic curve (AUROC) values (89.3% to 94.7%) were observed across a broad CL range (15 to 90). Utilizing pTau217R‐based models for low amyloid levels reduced PET scans by 70.5% to 78.6%. DISCUSSION: pTau217R effectively predicts brain amyloid levels, surpassing cerebrospinal fluid Aβ42/Aβ40's range. Combining it with plasma Aβ42/Aβ40 enhances sensitivity for low amyloid detection, reducing unnecessary PET scans and expanding clinical utility. CLINICALTRIALS.GOV IDENTIFIERS: NCT02956486 (MissionAD1), NCT03036280 (MissionAD2), NCT04468659 (AHEAD3‐45), NCT03887455 (ClarityAD) Highlights: Phosphorylated plasma Tau217 ratio (pTau217R) effectively predicts amyloid‐PET Centiloid (CL) across a broad spectrum.Integrating pTau217R with Aβ42/Aβ40 extends the CL prediction upper limit to 89.1 CL.Combined model predicts amyloid status with high accuracy, especially in cognitively unimpaired individuals.This model identifies subjects above or below various CL thresholds with high accuracy.pTau217R‐based models significantly reduce PET scans by up to 78.6% for screening out individuals with no/low amyloid. [ABSTRACT FROM AUTHOR]

Purpose: 68Ga-PSMA-11 is recommended for the selection of patients for treatment in the package insert for 177Lu-PSMA-617. We aimed to compare imaging properties and post-treatment outcomes from radioligand therapy (RLT) of patients selected with 68Ga-PSMA-11 and 18F-DCFPyL. Methods: We retrospectively evaluated 80 patients undergoing PSMA RLT, who had pretreatment imaging using either 68Ga-PSMA-11 or 18F-DCFPyL. For both groups, we compared the biodistribution and lesion uptake and the PSA response to treatment. Results: Both agents had comparable biodistribution. Patients initially imaged with 18F-DCFPyL had a higher PSA response (66% vs. 42%), and more patients had a PSA50 response (72% vs. 43%) compared to patients imaged with 68Ga-PSMA-11. Conclusion: 18F-DCFPyL and 68Ga-PSMA-11 had comparable biodistribution and lesion uptake. Patients imaged with 18F-DCFPyL demonstrated clinical benefit to PSMA RLT comparable to those imaged with 68Ga-PSMA-11, and either agent can be used for screening patients. [ABSTRACT FROM AUTHOR]

Purpose68Ga-PSMA-11 is recommended for the selection of patients for treatment in the package insert for 177Lu-PSMA-617. We aimed to compare imaging properties and post-treatment outcomes from radioligand therapy (RLT) of patients selected with 68Ga-PSMA-11 and 18F-DCFPyL.MethodsWe retrospectively evaluated 80 patients undergoing PSMA RLT, who had pretreatment imaging using either 68Ga-PSMA-11 or 18F-DCFPyL. For both groups, we compared the biodistribution and lesion uptake and the PSA response to treatment.ResultsBoth agents had comparable biodistribution. Patients initially imaged with 18F-DCFPyL had a higher PSA response (66% vs. 42%), and more patients had a PSA50 response (72% vs. 43%) compared to patients imaged with 68Ga-PSMA-11.Conclusion18F-DCFPyL and 68Ga-PSMA-11 had comparable biodistribution and lesion uptake. Patients imaged with 18F-DCFPyL demonstrated clinical benefit to PSMA RLT comparable to those imaged with 68Ga-PSMA-11, and either agent can be used for screening patients.

Background: Identifying individuals with depressive symptomatology (DS) promptly and effectively is of paramount importance for providing timely treatment. Machine learning models have shown promise in this area; however, studies often fall short in demonstrating the practical benefits of using these models and fail to provide tangible real-world applications. Objective: This study aims to establish a novel methodology for identifying individuals likely to exhibit DS, identify the most influential features in a more explainable way via probabilistic measures, and propose tools that can be used in real-world applications. Methods: The study used 3 data sets: PROACTIVE, the Brazilian National Health Survey (Pesquisa Nacional de Saúde [PNS]) 2013, and PNS 2019, comprising sociodemographic and health-related features. A Bayesian network was used for feature selection. Selected features were then used to train machine learning models to predict DS, operationalized as a score of ≥10 on the 9-item Patient Health Questionnaire. The study also analyzed the impact of varying sensitivity rates on the reduction of screening interviews compared to a random approach. Results: The methodology allows the users to make an informed trade-off among sensitivity, specificity, and a reduction in the number of interviews. At the thresholds of 0.444, 0.412, and 0.472, determined by maximizing the Youden index, the models achieved sensitivities of 0.717, 0.741, and 0.718, and specificities of 0.644, 0.737, and 0.766 for PROACTIVE, PNS 2013, and PNS 2019, respectively. The area under the receiver operating characteristic curve was 0.736, 0.801, and 0.809 for these 3 data sets, respectively. For the PROACTIVE data set, the most influential features identified were postural balance, shortness of breath, and how old people feel they are. In the PNS 2013 data set, the features were the ability to do usual activities, chest pain, sleep problems, and chronic back problems. The PNS 2019 data set shared 3 of the most influential features with the PNS 2013 data set. However, the difference was the replacement of chronic back problems with verbal abuse. It is important to note that the features contained in the PNS data sets differ from those found in the PROACTIVE data set. An empirical analysis demonstrated that using the proposed model led to a potential reduction in screening interviews of up to 52% while maintaining a sensitivity of 0.80. Conclusions: This study developed a novel methodology for identifying individuals with DS, demonstrating the utility of using Bayesian networks to identify the most significant features. Moreover, this approach has the potential to substantially reduce the number of screening interviews while maintaining high sensitivity, thereby facilitating improved early identification and intervention strategies for individuals experiencing DS. [ABSTRACT FROM AUTHOR]

The objective of this study was to identify the prevalence and self-recognition for indicators of inflammation suggestive of periodontal disease in military personnel of both genders. The military personnel was recruited to conduct a dental census for the entire population of the Admiral Wandenkolk Training Center of the Brazilian Navy, totaling 409 volunteers. Two groups were formed for further analysis: Group 1- containing exclusively women and Group 2- containing exclusively men. A total of 409 clinical examinations were performed and the questionnaires were analyzed. The results showed that, regarding the military participants, 40.1% were female and 59.9% were male; 87% used dental floss, of which 56% used it daily; 77% brushed three times a day or more; 74.3% reported that they visited the dentist regularly, and the proportion of women who regularly visited the dentist significantly exceeded the proportion of men who did (C.I. 95%; p

Background: The main objective of the present study was to compare the diagnostic performance of the commercial LightMix Modular Monkeypox Virus (MPXV) qPCR (TIB Molbiol, Germany) assay with the in-house nonvariola orthopox/monkeypox generic real-time PCR assay (ICMR-NIV, Pune) for the screening of (MPXV) cases at Medical Research Institute (MRI) in Sri Lanka. Furthermore, clinical and sociodemographic data of suspected /confirmed cases received at MRI for the MPXV screening were also analyzed. Methods: The diagnostic performance of the commercial LightMix Modular MPXV qPCR assay with the in-house nonvariola orthopox/monkeypox generic real-time PCR assay for the screening of suspected MXPV cases was evaluated using standard methods with minor modifications. Socio-demographic and clinical profiles of suspected and confirmed MPXV cases were also analyzed. Results: The commercial LightMix Modular MPXV assay was able to detect MPXV with 100% sensitivity and specificity with non-variola orthopox/monkeypox generic rtPCR assay. During the period of study, from the total of 25 samples tested, only 2 were MPXV-positive (males). The most common symptoms of suspected MPXV cases were lesions or rashes (92%). Conclusions: With the continually increasing number of cases, access to MPXV testing should be made more widely available. The commercial LightMix Modular MPXV (TIB Molbiol) qPCR assay offers comparable performance to the non-variola orthopox/monkeypox generic real time PCR assay for MPXV detection during the present outbreak.

Background: Community pharmacists play an intermediary role between prescribing physicians and patients in the United Arab Emirates (UAE) and thus are responsible for ensuring that patients receive optimal cardiovascular disease (CVD) pharmaceutical care. Methods: we used a cross-sectional design to assess the perceptions and practices of community pharmacists concerning pharmaceutical care for patients with CVD. A trained researcher visited randomly selected community pharmacies and used a structured questionnaire to conduct in-person interviews with pharmacists. The questionnaire collected demographic data and information on perceptions and practices regarding CVD pharmaceutical care. Results: Five hundred and fifty-one participants were recruited. The average participant age (mean ± SD) was 35 ± 2.7 years. The average perception score regarding CVD prevention and management was 75.6% (95% confidence interval [CI] 77.1%-74.2%), and the average practice score for CVD prevention and management was 87.1% (95% CI 76.5%-79.6%). Bivariate analysis revealed that gender (p = 0.001), education level (p < 0.001), pharmacy position (p = 0.004), work experience (p < 0.001), number of patients served per day (p < 0.001) and being trained on CVD prevention and management (p < 0.001) were significantly associated with perceptions about the prevention and management of CVD. Better practice scores were seen among older participants (OR 1.01; 95% CI 1-1.019), postgraduates (OR 1.77; 95% CI 1.66-1.89), workers at chain pharmacies (OR 1.24; 95% CI 1.11-1.39), pharmacists in charge (OR 1.22; 95% CI 1.01-1.47), pharmacists with >10 years of experience (OR 11.3; 95% CI 6.01-15.62), pharmacists with 6-10 years of experience (OR 4.42; 95% CI 3.90-5) and pharmacists trained on CVD prevention and management (OR 1.29; 95% CI 1.15-1.46). Conclusion: Pharmacy practitioners working in community pharmacies in the UAE actively engage in delivering pharmaceutical care to patients, playing a role in CVD management and prevention. However, they showed low levels of involvement in other healthcare services, specifically in screening and measuring patients' weight, glucose levels, and blood pressure, monitoring treatment responses, maintaining medical records, and reviewing medication refill histories. Activities such as educating patients, providing medication counseling, offering support for treatment adherence, and fostering collaborative relationships with other healthcare providers should be encouraged among UAE community pharmacists to ensure the provision of high-quality patient care. [ABSTRACT FROM AUTHOR]

Objectives: As safety‐net clinics, dental school clinics are uniquely positioned to evaluate the unmet social need. There is evidence that patients treated in a safety‐net type clinic, such as dental schools, report experiencing one or more of the determinants of health. However, there is limited evidence describing screening for Social Determinants of Health (SDOH) in dental clinics. The purpose of this study is to gain knowledge of the types of social determinants of health that exist in a dental school clinic and how it is reflected in the geographic region of the school. Methods: This cross‐sectional prospective study used a 20‐item questionnaire assessed unmet social needs in a predoctoral clinic. The questionnaire contained multiple choice and binary yes/no questions, organized under SDOH domains: housing, food, transportation, utilities, childcare, employment, education, finances, and personal safety. Socioeconomic and demographic information was captured. The questionnaire was administered via iPad using Qualtrics XM. The data were descriptively and quantitatively analyzed at a significance level of p ≤ 0.05. Results: There were 175 respondents with a 93.6% response rate, males (49.7%), females (49.1%), and 1.1% nonbinary. Overall, 135 (77.1%) respondents reported having at least one unmet social need. The greatest number of unmet needs was in the domains of employment and finances, with 44% and 41.7% respectively. Respondents who were unable to work stated they often or sometimes worried about running out of food before getting money to buy more, (p = 0.0002), and or the food didn't last before there was money to get more (p = 0.00007). A comparison of annual incomes of respondents earning less than $40K with those earning $40K or more, demonstrated statistically significant differences in unmet social needs for housing (p < 0.0001), food (p = 0.0003, p < 0.0001), utilities (p = 0.0484), employment (p = 0.0016), education (p < 0.0001), and finances (p < 0.0001). Conclusion: Screening patients in the dental clinic was an efficient way to uncover the level of unmet social needs. Annual household income was a predominant driver of unmet social needs: with the greatest number of unmet needs existing in the domains of employment and finances. The results suggest that screening for social determinants of health dental school clinics could be incorporated into routine patient data collection. [ABSTRACT FROM AUTHOR]

Background: Community pharmacists play an intermediary role between prescribing physicians and patients in the United Arab Emirates (UAE) and thus are responsible for ensuring that patients receive optimal cardiovascular disease (CVD) pharmaceutical care.Methods: we used a cross-sectional design to assess the perceptions and practices of community pharmacists concerning pharmaceutical care for patients with CVD. A trained researcher visited randomly selected community pharmacies and used a structured questionnaire to conduct in-person interviews with pharmacists. The questionnaire collected demographic data and information on perceptions and practices regarding CVD pharmaceutical care.Results: Five hundred and fifty-one participants were recruited. The average participant age (mean ± SD) was 35 ± 2.7 years. The average perception score regarding CVD prevention and management was 75.6% (95% confidence interval [CI] 77.1%–74.2%), and the average practice score for CVD prevention and management was 87.1% (95% CI 76.5%–79.6%). Bivariate analysis revealed that gender (p = 0.001), education level (p < 0.001), pharmacy position (p = 0.004), work experience (p < 0.001), number of patients served per day (p < 0.001) and being trained on CVD prevention and management (p < 0.001) were significantly associated with perceptions about the prevention and management of CVD. Better practice scores were seen among older participants (OR 1.01; 95% CI 1–1.019), postgraduates (OR 1.77; 95% CI 1.66–1.89), workers at chain pharmacies (OR 1.24; 95% CI 1.11–1.39), pharmacists in charge (OR 1.22; 95% CI 1.01–1.47), pharmacists with >10 years of experience (OR 11.3; 95% CI 6.01–15.62), pharmacists with 6–10 years of experience (OR 4.42; 95% CI 3.90–5) and pharmacists trained on CVD prevention and management (OR 1.29; 95% CI 1.15–1.46).Conclusion: Pharmacy practitioners working in community pharmacies in the UAE actively engage in delivering pharmaceutical care to patients, playing a role in CVD management and prevention. However, they showed low levels of involvement in other healthcare services, specifically in screening and measuring patients’ weight, glucose levels, and blood pressure, monitoring treatment responses, maintaining medical records, and reviewing medication refill histories. Activities such as educating patients, providing medication counseling, offering support for treatment adherence, and fostering collaborative relationships with other healthcare providers should be encouraged among UAE community pharmacists to ensure the provision of high-quality patient care.

Background: This study examines whether phosphorylated plasma Tau217 ratio (pTau217R) can predict tau accumulation in different brain regions, as measured by positron emission tomography (PET) standardized uptake value ratio (SUVR), for staging Alzheimer's disease (AD)., Methods: Plasma pTau217R was measured using immunoprecipitation-mass spectrometry. Models for predicting tau PET SUVR, developed with 144 early AD individuals using [ 18 F]MK6240, were validated in two validation sets, VS1 (98 early AD) and VS2 (47 preclinical/early AD with a different tracer, flortaucipir (Tauvid)), all amyloid-beta positive (Aβ+)., Results: The pTau217R-based model predicted tau levels up to an SUVR of 2 in multiple brain regions, effectively assessing tau status at different tau levels with receiver operating characteristic (ROC) curve areas of 0.84-0.95 in VS1 and 0.71-0.88 in VS2 (using a different tracer). It reduced PET scan needs by 65% while maintaining 95% sensitivity., Discussion: PTau217R reliably predicts regional tau accumulation in early AD, reducing reliance on tau PET scans and broadening its clinical application., Clinical Trial Registration Number: NCT03887455 (ClarityAD) HIGHLIGHTS: Developed a model using plasma pTau217R to predict tau levels across brain regions. pTau217R model outperformed models based on clinical, MRI, and other blood biomarkers. The model reliably predicted tau levels exceeding tau positivity and higher thresholds. Screening with pTau217R could reduce tau PET scans by 65% at 95% sensitivity. pTau217R model aids in disease staging and monitoring in early AD., (© 2024 Eisai Inc. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Joseph A Boscarino,1 Richard E Adams,2 Thomas G Urosevich,3 Stuart N Hoffman,4 H Lester Kirchner,1 Xin Chu,5 Weixing Shi,5 Joseph J Boscarino,6 Ryan J Dugan,1 Carrie A Withey,1 Charles R Figley7 1Department Population Health Sciences, Geisinger Clinic, Danville, PA, 17822, USA; 2Department Sociology, Kent State University, Kent, OH, 44242, USA; 3Ophthalmology Service, Geisinger Clinic, Mount Pocono, PA, 18344, USA; 4Department Sleep Medicine, Geisinger Clinic, Danville, PA, 17822, USA; 5Obesity Institute, Geisinger Clinic, Danville, PA, 17822, USA; 6Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, STC 7, Tampa, FL, 33606, USA; 7School of Social Work, Tulane University, New Orleans, LA, 70112, USACorrespondence: Joseph A BoscarinoDepartment Population Health Sciences, Geisinger Clinic, 100 N. Academy Ave., 44-00, Danville, PA, 17822, USATel +1 570-214-9825Email joseph.boscarino@gmail.comIntroduction: Since veteran suicide is a concern and our knowledge of predictive factors is still limited, our objective was to assess risk factors for suicide, including genetic factors, among deployed veterans.Methods: For this study, we surveyed 1730 veterans who were outpatients in a multi-hospital system in Pennsylvania. Altogether, 1041 veterans (60%) provided a DNA sample. The genetic risk variants investigated were within loci previously associated with PTSD and substance misuse, including CRHR1, CHRNA5, RORA, and FKBP5 genetic variations, which were used to calculate a polygenic risk score (range=0– 8, mean=3.6, SD=1.4).Results: Most veterans (56.2%) were deployed to Vietnam while significant numbers were deployed to Iraq, Afghanistan, and other post-Vietnam conflicts. Overall, 95.1% of the veterans were male, their mean age was 56.2 (SD=12), and 95.6% were Caucasian. Among the veterans, 24% had high combat exposure. The prevalence of lifetime suicidal thoughts was 11.3%. Additionally, 5.7% ever developed a suicide plan or attempted suicide in their lifetimes. Among those with a history of a lifetime suicide attempt or suicide plan, the PTSD genetic risk score was significantly higher (OR=3.96 vs 3.55, p=0.033), but for suicidal thoughts, this association was not significant (p=0.717). In multivariable analysis (MVA) logistic regression, significant predictors of attempting suicide or having a suicide plan were history of depression (OR=5.04, p< 0.001), PTSD genetic risk score (OR=1.25, p=0.036), history of childhood abuse/neglect (OR=2.24, p=0.009), and lifetime marijuana use (OR= 1.56, p=0.020). Conversely, rural residence was protective for suicide risk (OR=0.49; p=0.031). For suicidal thoughts, in the MVA genetic risk score was not significant (p=0.697), but history of child abuse/neglect (p< 0.001), history of depression (p> 0.001), low psychological resilience (p=0.004), and lifetime marijuana use (p=0.022) were significant.Discussion: In this study, we identified genetic risk variants and other predictors for suicide among veterans that may have implications for future screening and clinical care. Further research is advised.Keywords: veterans, warzone deployment, suicide, genetic factors, patient screening, precision medicine

The spread of coronavirus disease 2019 posed a public health crisis beginning in January 2020, affecting hospitals and health care personnel worldwide and disrupting perioperative services. Organization leaders at Xijing Hospital, Xi'an, China, developed a mitigation system for the OR that involved creating a pandemic response team to identify and implement appropriate infection control practices to prevent virus transmission. The leaders addressed managing the daily surgery schedule through patient screening and a focus on the urgency and volume of procedures. They required increased use of personal protective equipment and more stringent cleaning and disinfection protocols and ensured that the physical and mental health of staff members were monitored and prioritized. This article describes how leaders implemented these enhanced processes to protect personnel from infection as they continued to provide patient care. It also describes how high‐risk procedures involving patients with confirmed or suspected infections were managed and discusses lessons learned. [ABSTRACT FROM AUTHOR]

Background: Primary liver cancer has high mortality and morbidity worldwide. However, the characteristic of gut microbiota profile and its correlation with inflammation status in liver cancer patients remains largely unknown, and a gut microbiome-based diagnostic model for liver cancer is still absent. Methods: Here, we provided a comprehensive analysis based on fecal 16S rRNA sequencing and clinical data in a cohort consisting of 40 healthy volunteers, 143 hepatocellular carcinoma (HCC) patients, and 46 cholangiocarcinoma (CCA) patients. Results: Our results indicated a distinct shift of gut microbiota composition between two primary liver cancer types and compared with healthy volunteers. Based on the diversity constitute of gut microbiome taxonomy and random forest algorithm, eight genera with mean abundance above 0.1% were selected to construct the classification model with half of the randomly selected cohort. Based on this signature, high diagnostic accuracy in the validation cohort to classify liver cancer types (AUC = 0.989, 0.967, 0.920 for Control, HCC, CCA separately) was achieved. Further analysis showed increased Gram-negative bacteria and elevated inflammatory response markers in CCA group versus HCC group. The correlation analysis between inflammatory response markers and composition of gut microbiome revealed decreased potentially beneficial genus and increased opportunistic pathogens positively correlated with adverse prognostic inflammatory response markers. Conclusion: Generally, our study established the gut microbiome-based signature for liver cancer prediction and screening and revealed that gut microbiome characteristic in primary liver cancer was correlated with adverse inflammatory response markers in liver cancer. [ABSTRACT FROM AUTHOR]

Phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI4) magnetic resonance imaging (MRI) protocols aim to maintain longitudinal consistency across two decades of data acquisition, while adopting new technologies. Here we describe and justify the study's design and targeted biomarkers. The ADNI4 MRI protocol includes nine MRI sequences. Some sequences require the latest hardware and software system upgrades and are continuously rolled out as they become available at each site. The main sequence additions/changes in ADNI4 are: (1) compressed sensing (CS) T1-weighting, (2) pseudo-continuous arterial spin labeling (ASL) on all three vendors (GE, Siemens, Philips), (3) multiple-post-labeling-delay ASL, (4) 1 mm 3 isotropic 3D fluid-attenuated inversion recovery, and (5) CS 3D T2-weighted. ADNI4 aims to help the neuroimaging community extract valuable imaging biomarkers and provide a database to test the impact of advanced imaging strategies on diagnostic accuracy and disease sensitivity among individuals lying on the cognitively normal to impaired spectrum. HIGHLIGHTS: A summary of MRI protocols for phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI 4). The design and justification for the ADNI 4 MRI protocols. Compressed sensing and multi-band advances have been applied to improve scan time. ADNI4 protocols aim to streamline safety screening and therapy monitoring. The ADNI4 database will be a valuable test bed for academic research., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: This study investigated the potential of phosphorylated plasma Tau217 ratio (pTau217R) and plasma amyloid beta (Aβ) 42/Aβ40 in predicting brain amyloid levels measured by positron emission tomography (PET) Centiloid (CL) for Alzheimer's disease (AD) staging and screening., Methods: Quantification of plasma pTau217R and Aβ42/Aβ40 employed immunoprecipitation-mass spectrometry. CL prediction models were developed on a cohort of 904 cognitively unimpaired, preclinical and early AD subjects and validated on two independent cohorts., Results: Models integrating pTau217R outperformed Aβ42/Aβ40 alone, predicting amyloid levels up to 89.1 CL. High area under the receiver operating characteristic curve (AUROC) values (89.3% to 94.7%) were observed across a broad CL range (15 to 90). Utilizing pTau217R-based models for low amyloid levels reduced PET scans by 70.5% to 78.6%., Discussion: pTau217R effectively predicts brain amyloid levels, surpassing cerebrospinal fluid Aβ42/Aβ40's range. Combining it with plasma Aβ42/Aβ40 enhances sensitivity for low amyloid detection, reducing unnecessary PET scans and expanding clinical utility., Gov Identifiers: NCT02956486 (MissionAD1), NCT03036280 (MissionAD2), NCT04468659 (AHEAD3-45), NCT03887455 (ClarityAD) HIGHLIGHTS: Phosphorylated plasma Tau217 ratio (pTau217R) effectively predicts amyloid-PET Centiloid (CL) across a broad spectrum. Integrating pTau217R with Aβ42/Aβ40 extends the CL prediction upper limit to 89.1 CL. Combined model predicts amyloid status with high accuracy, especially in cognitively unimpaired individuals. This model identifies subjects above or below various CL thresholds with high accuracy. pTau217R-based models significantly reduce PET scans by up to 78.6% for screening out individuals with no/low amyloid., (© 2024 Eisai Inc. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Home dialysis therapies have limited uptake in most regions despite recognized benefits such as increasing patients' independence, and several domains of quality of life with cost savings in some systems., Objective: To perform a scoping review of published literature to identify tools and guides used in systematically screening and assessing patient suitability for home dialysis. A secondary objective was to explore barriers and enablers associated with the home dialysis assessment process. It is important to identify gaps in current research to pose pertinent questions for future work in the field., Design: Online databases Embase, Medline (Ovid), and CINAHL were used to identify articles published between January 2007 to May 2023. A total of 23 peer-reviewed primary and secondary studies that investigated screening or selection for patients > 18 years old with kidney failure for home dialysis met the study inclusion criteria., Results: The studies consisted of secondary studies (n = 10), observational studies (n = 8), and survey-based studies (n = 5). The major themes identified that influence patient screening and assessment for home dialysis candidacy included: screening tools and guidelines (n = 8), relative contraindications (n = 4), patient or program education (n = 9), and socioeconomic factors (n = 2)., Limitations: Consistent with the scoping review methodology, the methodological quality of included studies was not assessed. The possible omission of evidence in languages other than English is a limitation., Conclusion: This scoping review identified tools and factors that potentially guide the assessment process for home dialysis candidacy. Patient screening and assessment for home dialysis requires a comprehensive evaluation of clinical, psychosocial, and logistical factors. Further research is required to validate and refine existing tools to establish standardized patient screening criteria and evaluation processes. Up-to-date training and education for healthcare providers and patients are needed to improve the utilization of home dialysis and ensure optimal outcomes., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

This paper presents a study about screening large radiological image streams produced in hospitals for earlier detection of lung nodules. Being one of the most difficult classification tasks in the literature, the objective is to measure how well state-of-the-art classifiers can screen out the images stream to keep as many positive cases as possible in an output stream to be inspected by clinicians. The authors performed several experiments with different image resolutions and training datasets from different sources, always taking ResNet-152 as the base neural network. Results over existing datasets show that, contrary to other diseases like pneumonia, detecting nodules is a hard task when using only radiographies. Indeed, final diagnosis by clinicians is usually performed with much more precise images like computed tomographies. [ABSTRACT FROM AUTHOR]

Introduction: Our goal was to explore whether emergency department (ED) patients would disclose their sexual orientation in a research evaluation and to examine demographic and clinical characteristics of patients by self-identified sexual orientation.Methods: Participants (n=177) presented for psychiatric treatment at three urban EDs in New York City, Rochester, NY, and Philadelphia, PA. Participants were interviewed in the context of a larger study of a standardized suicide risk assessment. We assessed participants’ willingness to answer questions regarding sexual orientation along three dimensions: a self-description of sexual orientation, a self-description of sexual attraction, and the gender of any prior sexual partners.Results: No participants (0/177) refused to respond to the categorical question about sexual orientation, 168/177 (94.9%) agreed to provide information about prior sexual partners, and 100/109 (91.7%) provided information about current sexual attraction toward either gender. Of all 177 participants, 154 (87.0%) self-identified as heterosexual, 11 (6.2%) as bisexual, 10 (5.6%) as gay or lesbian, and 2 (1.1%) indicated they were not sure. As compared with heterosexual patients, lesbian, gay and bisexual (LGB) patients were significantly younger and more likely to be non-white, but did not differ significantly in terms of education, income, employment, or religious affiliation or participation. Further, LGB participants did not differ from self-identified heterosexual participants for lifetime suicide attempt rate or lifetime history of any mood, substance-related, psychotic spectrum, or other Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) Axis I disorder. Of self-identified heterosexual participants 5.6% (5/89) reported sexual attraction as other than ‘only opposite sex,’ and 10.3% (15/142) of sexually active ‘heterosexual’ participants reported previous same-gender sexual partners.Conclusion: Assessing patients’ sexual orientation in the ED by a three-question approach appeared feasible in the ED and acceptable to ED patients. However, since many patients have sexual experiences not suggested by simple labels, self-report of sexual identity alone may not inform clinicians of health risks inherent in same or opposite gender sexual contact. [West J Emerg Med. 2015;16(1):–0.]

Objective: To evaluate factors in predicting the treatment outcome of ultrasound-guided high-intensity focused ultrasound (USgHIFU) ablation for uterine fibroids with a non-perfused volume ratio (NPVR) of at least 80%.Methods: One thousand patients with uterine fibroids who received USgHIFU were enrolled. Thirty-two independent variables of four dimensions of data set, including general information of patients, clinical symptoms, laboratory tests, and fibroid imaging characteristics, were used to investigate the potential predictors of the NPVR of at least 80% by multivariate logistic regression. NPVR was the gold standard for evaluating the efficiency of HIFU ablation, and a NPVR of at least 80% was considered sufficient ablation, while partial ablation was defined as having an NPVR of

T cell receptor (TCR) T cell therapies target tumor antigens in a human leukocyte antigen (HLA)-restricted manner. Biomarker-defined therapies require validation of assays suitable for determination of patient eligibility. For clinical trials evaluating TCR T cell therapies targeting melanoma-associated antigen A4 (MAGE-A4), screening in studies NCT02636855 and NCT04044768 assesses patient eligibility based on: (1) high-resolution HLA typing and (2) tumor MAGE-A4 testing via an immunohistochemical assay in HLA-eligible patients. The HLA/MAGE-A4 assays validation, biomarker data, and their relationship to covariates (demographics, cancer type, histopathology, tissue location) are reported here. HLA-A∗02 eligibility was 44.8% (2,959/6,606) in patients from 43 sites across North America and Europe. While HLA-A∗02:01 was the most frequent HLA-A∗02 allele, others (A∗02:02, A∗02:03, A∗02:06) considerably increased HLA eligibility in Hispanic, Black, and Asian populations. Overall, MAGE-A4 prevalence based on clinical trial enrollment was 26% (447/1,750) across 10 solid tumor types, and was highest in synovial sarcoma (70%) and lowest in gastric cancer (9%). The covariates were generally not associated with MAGE-A4 expression, except for patient age in ovarian cancer and histology in non-small cell lung cancer. This report shows the eligibility rate from biomarker screening for TCR T cell therapies and provides epidemiological data for future clinical development of MAGE-A4-targeted therapies., Competing Interests: T.W., J.-M.N., S.R., C.K., M.C., R.B., K.H., A.L., A.C., R.W., L.Q., J.P.S., C.M., F.B., E.E., P.B., and D.W. are or were employees of Adaptimmune at the time of the study and may own stock/stock options in Adaptimmune. M.V.K., S.V.R., K.S., and K.A. are employees of CellCarta NV, Antwerp, Belgium, and were involved in the development and validation of the MAGE-A4 IHC assay. G.B.J. received consulting fees from AbbVie, Daiichi Sankyo, Eli Lilly, Genzyme, Gilead, Merck Sharp & Dohme, Novartis, Regeneron; expenses from Regeneron; research funding from AstraZeneca, BeiGene, Bristol Myers Squibb, Daiichi Sankyo, Exelixis, Genentech, Incyte, Merck Sharp & Dohme, Novartis, Regeneron. M.O.B. received grant support from Merck, Takara Bio; quality improvement support from Novartis; is on the advisory board of Adaptimmune, Bristol Myers Squibb, GlaxoSmithKline, IDEAYA, Instil Bio, Iovance, La Roche Possey, Medison, Merck, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma; oral presentations given for Bristol Myers Squibb, Merck, Novartis, Pfizer, Sanofi. J.M.C. received grant/research support from AbbVie, Adaptimmune, Array, AstraZeneca, Bayer, Bristol Myers Squibb, CBMG, Genentech, GlaxoSmithKline, Grid Therapeutics, Medpacto, Moderna, Spectrum; consultant for Amgen, Corbus, G1 Therapeutics, Novartis, Omega, Sanofi, Turning Point, Vivacitas; speaker’s bureau for AstraZeneca. J.F.G. was compensated consultant or received honoraria from AI Proteins, AstraZeneca, Blueprint Medicines, Bristol Myers Squibb, Curie Therapeutics, Genentech/Roche, Gilead, iTeos, Jounce, Karyopharm, Loxo/Lilly, Merck, Merus Pharmacueticals, Mirati, Moderna, Novartis, Novocure, Nuvalent, Pfizer, Silverback Therapeutics, Takeda; research support from Genentech/Roche, Novartis, Takeda; institutional research support from Adaptimmune, Alexo, Array Biopharma, Bristol Myers Squibb, Blueprint Medicines, Jounce, Merck, Moderna, Novartis, Palleon, Tesaro; equity in AI Proteins; and has an immediate family member who is an employee with equity at Ironwood Pharmaceuticals. V.M. received consulting fees from Affimed, AstraZeneca, Bayer, Bristol Myers Squibb, Janssen, Roche, Syneos; was principal investigator – institutional funding from AbbVie, AceaBio, Adaptimmune, ADC Therapeutics, Aduro, Agenus, Amcure, Amgen, Astellas, AstraZeneca, Bayer, BeiGene, BioInvent International AB, Bristol Myers Squibb, Boehringer, Boston, Celgene, Daichii Sankyo, DEBIOPHARM, Eisai, e-Terapeutics, Exelisis, Forma Therapeutics, Genmab, GlaxoSmithKline, Harpoon, Hutchison, Immutep, Incyte, Inovio, Iovance, Janssen, Kyowa Kirin, Lilly, Loxo, MedSir, Menarini, Merck, Merus, Millennium, MSD, Nanobiotix, Nektar, Novartis, Odonate Therapeutics, Pfizer, Pharma Mar, PharmaMar, Principia, PsiOxus, Puma, Regeneron, Rigontec, Roche, Sanofi, Sierra Oncology, Synthon, Taiho, Takeda, Tesaro, Transgene, Turning Point Therapeutics, Upshersmith. M.J. received research funding (institutional) from AbbVie, Acerta, Adaptimmune, Amgen, Apexigen, Arcus Biosciences, Array BioPharma, Artios Pharma, AstraZeneca, Atreca, BeiGene, BerGenBio, BioAtla, Black Diamond, Boehringer Ingelheim, Bristol Myers Squibb, Calithera Biosciences, Carisma Therapeutics, Checkpoint Therapeutics, City of Hope National Medical Center, Corvus Pharmaceuticals, Curis, CytomX, Daiichi Sankyo, Dracen Pharmaceuticals, Dynavax, Eli Lilly, Elicio Therapeutics, EMD Serono, EQRx, Erasca, Exelixis, Fate Therapeutics, Genentech/Roche, Genmab, Genocea Biosciences, GlaxoSmithKline, Gritstone Oncology, Guardant Health, Harpoon, Helsinn Healthcare SA, Hengrui Therapeutics, Hutchison MediPharma, IDEAYA Biosciences, IGM Biosciences, Immunitas Therapeutics, Immunocore, Incyte, Janssen, Jounce Therapeutics, Kadmon Pharmaceuticals, Kartos Therapeutics, Loxo Oncology, Lycera, Memorial Sloan Kettering, Merck, Merus, Mirati Therapeutics, Mythic Therapeutics, NeoImmune Tech, Neovia Oncology, Novartis, Numab Therapeutics, Nuvalent, OncoMed Pharmaceuticals, Palleon Pharmaceuticals, Pfizer, PMV Pharmaceuticals, Rain Therapeutics, RasCal Therapeutics, Regeneron Pharmaceuticals, Relay Therapeutics, Revolution Medicines, Ribon Therapeutics, Rubius Therapeutics, Sanofi, Seven and Eight Biopharmaceuticals/Birdie Biopharmaceuticals, Shattuck Labs, Silicon Therapeutics, Stem CentRx, Syndax Pharmaceuticals, Takeda Pharmaceuticals, Tarveda, TCR2 Therapeutics, Tempest Therapeutics, Tizona Therapeutics, TMUNITY Therapeutics, Turning Point Therapeutics, University of Michigan, Vyriad, WindMIL Therapeutics, Y-mAbs Therapeutics; had a consulting/advisory role (institutional) for AbbVie, Amgen, Arcus Biosciences, Arrivent, Astellas, AstraZeneca, Black Diamond, Boehringer Ingelheim, Calithera Biosciences, Daiichi Sankyo, EcoR1, Genentech/Roche, Genmab, Genocea Biosciences, Gilead Sciences, GlaxoSmithKline, Gritstone Oncology, Ideaya Biosciences, Immunocore, iTeos, Janssen, Jazz Pharmaceuticals, Merck, Mirati Therapeutics, Molecular Axiom, Normunity, Novartis, Oncorus, Pyramid Biosciences, Regeneron Pharmaceuticals, Revolution Medicines, Sanofi-Aventis, SeaGen, Synthekine, Takeda Pharmaceuticals, Turning Point Therapeutics, VBL Therapeutics. D.S.H. received travel, accommodations, expenses from AACR, ASCO, CLCC, Bayer, Genmab, SITC, Telperian; had consulting, speaker, or advisory role with 28Bio, AbbVie, Acuta, Adaptimmune, Alkermes, Alpha Insights, Amgen, Affini-T, Astellas, Aumbiosciences, Axiom, Baxter, Bayer, Boxer Capital, BridgeBio, CARSgen, CLCC, COG, COR2ed, Cowen, EcoR1, Erasca, Fate Therapeutics, F. Hoffmann-La Roche, Genentech, Gennao Bio, Gilead, GLG, Group H, Guidepoint, HCW Precision Oncology, Immunogenesis, InduPro, Janssen, Liberium, MedaCorp, Medscape, Numab, Oncologia Brasil, ORI Capital, Pfizer, Pharma Intelligence, POET Congress, Prime Oncology, Projects in Knowledge, Quanta, RAIN, Ridgeline, SeaGen, Stanford, STCube, Takeda, Tavistock, Trieza Therapeutics, Turning Point Therapeutics, WebMD, YingLing Pharma, Ziopharm; has other ownership interests in Molecular Match (advisor), OncoResponse (founder, advisor), Telperian (founder, advisor); received institutional research/grant funding from AbbVie, Adaptimmune, Adlai-Nortye, Amgen, AstraZeneca, Bayer, Biomea, Bristol Myers Squibb, Daiichi Sankyo, Deciphera, Eisai, Eli Lilly, Endeavor, Erasca, F. Hoffmann-La Roche, Fate Therapeutics, Genentech, Genmab, Immunogenesis, Infinity, Kyowa Kirin, Merck, Mirati, Navier, NCI-CTEP, Novartis, Numab, Pfizer, Pyramid Bio, Revolution Medicine, SeaGen, STCube, Takeda, TCR2, Turning Point Therapeutics, VM Oncology., (© 2024 The Authors.)

The introduction of pre-trained language models in natural language processing (NLP) based on deep learning and the availability of electronic health records (EHRs) presents a great opportunity to transfer the “knowledge” learned from data in the general domain to enable the analysis of unstructured textual data in clinical domains. This study explored the feasibility of applying NLP to a small EHR dataset to investigate the power of transfer learning to facilitate the process of patient screening in psychiatry. A total of 500 patients were randomly selected from a medical center database. Three annotators with clinical experience reviewed the notes to make diagnoses for major/minor depression, bipolar disorder, schizophrenia, and dementia to form a small and highly imbalanced corpus. Several state-of-the-art NLP methods based on deep learning along with pre-trained models based on shallow or deep transfer learning were adapted to develop models to classify the aforementioned diseases. We hypothesized that the models that rely on transferred knowledge would be expected to outperform the models learned from scratch. The experimental results demonstrated that the models with the pre-trained techniques outperformed the models without transferred knowledge by micro-avg. and macro-avg. F-scores of 0.11 and 0.28, respectively. Our results also suggested that the use of the feature dependency strategy to build multi-labeling models instead of problem transformation is superior considering its higher performance and simplicity in the training process.

The introduction of pre-trained language models in natural language processing (NLP) based on deep learning and the availability of electronic health records (EHRs) presents a great opportunity to transfer the "knowledge" learned from data in the general domain to enable the analysis of unstructured textual data in clinical domains. This study explored the feasibility of applying NLP to a small EHR dataset to investigate the power of transfer learning to facilitate the process of patient screening in psychiatry. A total of 500 patients were randomly selected from a medical center database. Three annotators with clinical experience reviewed the notes to make diagnoses for major/minor depression, bipolar disorder, schizophrenia, and dementia to form a small and highly imbalanced corpus. Several state-of-the-art NLP methods based on deep learning along with pre-trained models based on shallow or deep transfer learning were adapted to develop models to classify the aforementioned diseases. We hypothesized that the models that rely on transferred knowledge would be expected to outperform the models learned from scratch. The experimental results demonstrated that the models with the pre-trained techniques outperformed the models without transferred knowledge by micro-avg. and macro-avg. F-scores of 0.11 and 0.28, respectively. Our results also suggested that the use of the feature dependency strategy to build multi-labeling models instead of problem transformation is superior considering its higher performance and simplicity in the training process. [ABSTRACT FROM AUTHOR]

Recruitment and retention are critical in clinical studies but there are limited objective metrics of trial performance. We tested if development of trial performance metrics will allow for objective evaluation of study quality. Performance metrics were developed using data from the observational cohort (OBS) and randomized clinical trial (RCT) arms of the prospective Alcoholic Hepatitis Network. Yield-rate (%YR; eligible/screened), recruitment index (RI; mean recruitment time/patient), completion index (CI; average number of days to complete the follow-up/patient), and protocol adherence index (AI; average number of deviations/subject recruited) were determined. 2250 patients (1168 for OBS; 1082 for RCT) were screened across 8 sites. Recruitment in the RCT (57% target) was similar to that in the OBS (59% target). Of those screened, 743 (63.6%) subjects in the OBS and 147 (13.6%) subjects in the RCT were enrolled in the study. In OBS study, 253 (34.1%) subjects, and in the RCT, 68 (46.3%) subjects, completed the study or reached a censoring event. Across all sites (range), YR for OBS was 63.6% (41.3–98.3%) and for RCT was 13.6% (5.5–92.6%); RI for OBS was 1.66 (8.79–19.85) and for RCT was 4.05 (19.76–36.43); CI for OBS was 4.87 (22.6–118.3) and for RCT was 8.75 (27.27–161.5); and AR for OBS was 0.56 (0.08–1.04) and for RCT was 1.55 (0.39–3.21. Factors related to participants, research design, study team, and research sponsors contributed to lower performance metrics. Objective measures of clinical trial performance allow for strategies to enhance study quality and development of site-specific improvement plans. Trial registration number: ClinicalTrials.gov NCT4072822 NCT 3850899. [Display omitted] • Recruitment, retention and protocol adherence are critical to ensure validity of clinical trials. • There are currently limited objective metrics to evaluate clinical trial performance, especially in multicenter studies. • We developed 4 objective metrics that measure different components of a clinical trial- eligible subjects, those who agree to participate after being eligible, time taken to complete a study visit and protocol adherence rates. • We then tested it in a population of patients with alcohol associated hepatitis who have a high morbidity and mortality. • Objective measures of trial performance allows for identifying challenges including study design, logistics, patient and research team related factors that can be modified to improve study performance. [ABSTRACT FROM AUTHOR]

Abstract Background Acute kidney injury (AKI) is common in patients with multiple myeloma (MM). Whether serum free light chain (sFLC) measurements can distinguish between myeloma and other causes of AKI requires confirmation to guide early treatment. A rapid and portable sFLC test (Seralite®) is newly available and could reduce delays in obtaining sFLC results and accelerate diagnosis in patients with unexplained AKI. This study evaluated the accuracy of Seralite® to identify MM as the cause of AKI. Method sFLCs were retrospectively analysed in patients with AKI stage 3 as per KDIGO criteria (i.e. serum creatinine ≥354 μmol/L or those on dialysis treatment) (n = 99); 45/99 patients had a confirmed MM diagnosis. Results The Seralite® κ:λ FLC ratio accurately diagnosed all MM patients in the presence of AKI: a range of 0.14–2.02 returned 100% sensitivity and specificity for identifying all non-myeloma related AKI patients. The sFLC difference (dFLC) also demonstrated high sensitivity (91%) and specificity (100%): an optimal cut-off of 399 mg/L distinguished between myeloma and non-myeloma AKI patients. We propose a pathway of patient screening and stratification in unexplained AKI for use of Seralite® in clinical practice, with a κ:λ ratio range of 0.14–2.02 and dFLC 400 mg/L as decision points. Conclusions Seralite® accurately differentiates between AKI due to MM and AKI due to other causes in patients considered at risk of myeloma. This rapid test can sensitively screen for MM in patients with AKI and help inform early treatment intervention.

Background: Population ageing will lead to more deaths with an uncertain trajectory. Identifying patients at risk of dying could facilitate more effective care planning. Aim: To determine whether screening for likely death within 12 months is more effective using screening tools or intuition. Design: Randomised controlled trial of screening tools (Surprise Question plus the Supportive and Palliative Care Indicators Tool for Surprise Question positive patients) to predict those at risk of death at 12 months compared with unguided intuition (clinical trials registry: ACTRN12613000266763). Setting/participants: Australian general practice. A total of 30 general practitioners (screening tool = 12, intuition = 18) screened all patients (n = 4365) aged ≥70 years seen at least once in the last 2 years. Results: There were 142 deaths (screening tool = 3.1%, intuition = 3.3%; p = 0.79). General practitioners identified more at risk of dying using Surprise Question (11.8%) than intuition (5.4%; p = 0.01), but no difference with Surprise Question positive then Supportive and Palliative Care Indicators Tool (5.1%; p = 0.87). Surprise Question positive predicted more deaths (53.2%, intuition = 33.7%; p = 0.001), but Surprise Question positive/Supportive and Palliative Care Indicators Tool predictions were similar (5.1%; p = 0.87 vs intuition). There was no difference in proportions correctly predicted to die (Surprise Question = 1.6%, intuition = 1.1%; p = 0.156 and Surprise Question positive/Supportive and Palliative Care Indicators Tool = 1.1%; p = 0.86 vs intuition). Screening tool had higher sensitivity and lower specificity than intuition, but no difference in positive or negative predictive value. Conclusion: Screening tool was better at predicting actual death than intuition, but with a higher false positive rate. Both were similarly effective at screening the whole cohort for death. Screening for possible death is not the best option for initiating end-of-life planning: recognising increased burden of illness might be a better trigger. [ABSTRACT FROM AUTHOR]

Background: Acute kidney injury (AKI) is common in patients with multiple myeloma (MM). Whether serum free light chain (sFLC) measurements can distinguish between myeloma and other causes of AKI requires confirmation to guide early treatment. A rapid and portable sFLC test (Seralite®) is newly available and could reduce delays in obtaining sFLC results and accelerate diagnosis in patients with unexplained AKI. This study evaluated the accuracy of Seralite® to identify MM as the cause of AKI.Method: sFLCs were retrospectively analysed in patients with AKI stage 3 as per KDIGO criteria (i.e. serum creatinine ≥354 μmol/L or those on dialysis treatment) (n = 99); 45/99 patients had a confirmed MM diagnosis.Results: The Seralite® κ:λ FLC ratio accurately diagnosed all MM patients in the presence of AKI: a range of 0.14-2.02 returned 100% sensitivity and specificity for identifying all non-myeloma related AKI patients. The sFLC difference (dFLC) also demonstrated high sensitivity (91%) and specificity (100%): an optimal cut-off of 399 mg/L distinguished between myeloma and non-myeloma AKI patients. We propose a pathway of patient screening and stratification in unexplained AKI for use of Seralite® in clinical practice, with a κ:λ ratio range of 0.14-2.02 and dFLC 400 mg/L as decision points.Conclusions: Seralite® accurately differentiates between AKI due to MM and AKI due to other causes in patients considered at risk of myeloma. This rapid test can sensitively screen for MM in patients with AKI and help inform early treatment intervention. [ABSTRACT FROM AUTHOR]