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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.

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]

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]

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

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]

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]

Background: Parkinson’s disease (PD) is a common neurodegenerative condition with a chronic course divided into stages. The treatment of the condition is symptomatic and highly individualized. Due to the lack of clear guidelines, traditional oral and transdermal therapy is often unnecessarily prolonged resulting in lower efficacy of the treatment and patients’ lower quality of life. Literature Review: Assessment of advanced Parkinson’s disease (APD) is mostly subjective and dependent on the clinican’s personal judgement of the patient’s condition. Even though the staging of the PD depends on the patient’s expectations and demands regarding the effects of therapy, the clinician’s judgement is still considered the gold standard of staging. Implementing screening tools for APD in clinical pratice should contribute to more accurate assessment of the symptoms’ severity. Moreover, treatment standardization is challenged by a lack of evidence-based guidelines regarding the device-aided treatment (DAT) in APD. Patients suitable for DAT were often overlooked or the recommendation came too late. Patient care should be optimized by defining the standard of care and maximizing the effect of conventional treatment options, but not unnecessarily prolonging them. Delayed referral for DAT also comes from poor patient and clinican education. Educational courses regarding advanced treatment options for APD are generally unavailable which contributes to the lack of motivation for further education about this issue. Early implemenation of DAT could be greatly beneficial for some patients, not only helping with motor symptoms, but also with non-motor symptoms of PD. Conclusion: Improving patient care should be an imperative, which calls for defining clear evidence-based guidelines for DAT in APD. Patient and clinician education starting from medical students is a logical first step in achieving improvement regarding the issue of delayed referral and poor recognition of patients who are suitable for DAT. Proper timing of introducing different therapy methods is crucial for the treatment’s success. [ABSTRACT FROM AUTHOR]

Abstract: We previously developed a new posttraumatic stress disorder (PTSD) screening instrument—the New York PTSD Risk Score (NYPRS). Since research suggests different PTSD risk factors and outcomes for men and women, in the current study we assessed the suitability of male and female versions of this screening instrument among 3298 adults exposed to traumatic events. Using diagnostic test methods, including receiver operating characteristic (ROC) curve and bootstrap techniques, we examined different prediction domains, including core PTSD symptoms, trauma exposures, sleep disturbances, depression symptoms, and other measures to assess PTSD prediction models for men and women. While the original NYPRS worked well in predicting PTSD, significant interaction was detected by gender, suggesting that separate models are warranted for men and women. Model comparisons suggested that while the overall results appeared robust, prediction results differed by gender. For example, for women, core PTSD symptoms contributed more to the prediction score than for men. For men, depression symptoms, sleep disturbance, and trauma exposure contributed more to the prediction score. Men also had higher cut-off scores for PTSD compared to women. There were other gender-specific differences as well. The NYPRS is a screener that appears to be effective in predicting PTSD status among at-risk populations. However, consistent with other medical research, this instrument appears to require male and female versions to be the most effective. [Copyright &y& Elsevier]

The objective of cosmetic surgery is increased patient self-esteem and confidence. Most patients undergoing a procedure report these results post-operatively. The success of any procedure is measured in patient satisfaction. In order to optimize patient satisfaction, literature suggests careful pre-operative patient preparation including a discussion of the risks, benefits, limitations and expected results for each procedure undertaken. As a general rule, the patients that are motivated to surgery by a desire to align their outward appearance to their body-image tend to be the most satisfied. There are some psychiatric conditions that can prevent a patient from being satisfied without regard aesthetic success. The most common examples are minimal defect/Body Dysmorphic Disorder, the patient in crisis, the multiple revision patient, and loss of identity. This paper will familiarize the audience with these conditions, symptoms and related illnesses. Case examples are described and then explored in terms of the conditions presented. A discussion of the patient's motivation for surgery, goals pertaining to specific attributes, as well as an evaluation of the patient's understanding of the risks, benefits, and limitations of the procedure can help the physician determine if a patient is capable of being satisfied with a cosmetic plastic surgery procedure. Plastic surgeons can screen patients suffering from these conditions relatively easily, as psychiatry is an integral part of medical school education. If a psychiatric referral is required, then the psychiatrist needs to be aware of the nuances of each of these conditions. [ABSTRACT FROM AUTHOR]

Abstract: Objective: The objective was to develop a brief posttraumatic stress disorder (PTSD) screening instrument that is useful in clinical practice, similar to the Framingham Risk Score used in cardiovascular medicine. Methods: We used data collected in New York City after the World Trade Center disaster (WTCD) and other trauma data to develop a new PTSD prediction tool — the New York PTSD Risk Score. We used diagnostic test methods to examine different clinical domains, including PTSD symptoms, trauma exposures, sleep disturbances, suicidal thoughts, depression symptoms, demographic factors and other measures to assess different PTSD prediction models. Results: Using receiver operating curve (ROC) and bootstrap methods, five prediction domains, including core PTSD symptoms, sleep disturbance, access to care status, depression symptoms and trauma history, and five demographic variables, including gender, age, education, race and ethnicity, were identified. For the best prediction model, the area under the ROC curve (AUC) was 0.880 for the Primary Care PTSD Screen alone (specificity=82.2%, sensitivity=93.7%). Adding care status, sleep disturbance, depression and trauma exposure increased the AUC to 0.943 (specificity=85.7%, sensitivity=93.1%), a significant ROC improvement (P<.0001). Adding demographic variables increased the AUC to 0.945, which was not significant (P=.250). To externally validate these models, we applied the WTCD results to 705 pain patients treated at a multispecialty group practice and to 225 trauma patients treated at a Level I Trauma Center. These results validated those from the original WTCD development and validation samples. Conclusion: The New York PTSD Risk Score is a multifactor prediction tool that includes the Primary Care PTSD Screen, depression symptoms, access to care, sleep disturbance, trauma history and demographic variables and appears to be effective in predicting PTSD among patients seen in healthcare settings. This prediction tool is simple to administer and appears to outperform other screening measures. [Copyright &y& Elsevier]

Abstract: Detection of sleep apnea using electrocardiographic (ECG) parameters is noninvasive and inexpensive. Our approach is based on the hypothesis that the patient''s sleep-wake cycle during episodes of sleep apnea modulates heart rate (HR) oscillations. These HR oscillations appear as low-frequency fluctuations of instantaneous HR (IHR) and can be detected using HR variability analysis in the frequency domain. The purpose of this study was to evaluate the efficacy of our ECG-based algorithm for sleep apnea detection and quantification. The algorithm first detects normal QRS complexes and R-R intervals used to derive IHR and to estimate its spectral power in several frequency ranges. A quadratic classifier, trained on the learning set, uses 2 parameters to classify the 1-minute epoch in the middle of each 6-minute window as either apneic or normal. The windows are advanced by 1-minute steps, and the classification process is repeated. As a measure of quantification, the algorithm correctly classified 84.7% of all the 1-minute epochs in the evaluation database; and as a measure of the accuracy of apnea classification, the algorithm correctly classified all 30 test recordings in the evaluation database either as apneic or normal. Our sleep apnea detection algorithm based on analysis of a single-lead ECG provides accurate apnea detection and quantification. Because of its noninvasive and low-cost nature, this algorithm has the potential for numerous applications in sleep medicine. [Copyright &y& Elsevier]

Background: Patient-administered computerized questionnaires represent a novel tool to assist primary care physicians in the delivery of preventive health care.Objective: The aim of this study was to assess patient-reported ease of use with a self-administered tablet computer-based questionnaire in routine clinical care.Design: All patients seen in a university-based primary care practice were asked to provide routine screening information using a touch-screen tablet computer-based questionnaire. Patients reported difficulty using the tablet computer after completion of their first questionnaire.Patients: Ten thousand nine hundred ninety-nine patients completed the questionnaire between January 2004 and January 2006.Measurements: We calculated rates of reporting difficulty (no difficulty, some difficulty, or a lot of difficulty) using the tablet computers based on patient age, sex, race, educational attainment, marital status, and number of comorbid medical conditions. We constructed multivariable ordered logistic models to identify predictors of increased self-reported difficulty using the computer.Results: The majority of patients (84%) reported no difficulty using the tablet computers to complete the questionnaire, with only 3% reporting a lot of difficulty. Significant predictors of reporting more difficulty included increasing age [odds ratio (OR) 1.05, 95% confidence interval (CI) 1.05-1.05)]; Asian race (OR 2.3, 95% CI 1.8-2.9); African American race (OR 1.4, 95% CI 1.2-1.6); less than a high school education (OR 3.0, 95% CI 2.6-3.4); and the presence of comorbid medical conditions (1-2: OR 1.3, 95% CI 1.2-1.5; > or =3: OR 1.7 95% CI 1.5-2.1).Conclusions: The majority of primary care patients reported no difficulty using a self-administered tablet computer-based questionnaire. While computerized questionnaires present opportunities to collect routine screening information from patients, attention must be paid to vulnerable groups. [ABSTRACT FROM AUTHOR]

Abstract: The rapid advancement of high-resolution DNA copy number assessment methods revealed the significant contribution of submicroscopic genetic imbalances to abnormal phenotypes, including mental retardation. In order to detect submicroscopic genetic imbalances, we have screened 20 families with X-linked mental retardation (XLMR) using a chromosome X-specific array-MAPH platform with median resolution of 238kb. Among the 20 families, 18 were experimental, as they were not previously screened with any microarray method, and two were blind controls with known aberrations, as they were previously screened by array-CGH. This study presents the first clinical application of chromosome X-specific array-MAPH methodology. The screening of 20 affected males from 20 unrelated XLMR families resulted in the detection of an unknown deletion, spanning a region of 7–23kb. Family studies and population screening demonstrated that the detected deletion is an unknown rare copy number variant. One of the control samples, carrying approximately 6-Mb duplication was correctly identified, moreover it was found to be interrupted by a previously unknown 19kb region of normal copy number. The second control 50kb deletion was not identified, as this particular region was not covered by array-MAPH probes. This study demonstrates that the chromosome X-specific array-MAPH platform is a valuable tool for screening patients with XLMR, or other X-linked disorders, and emerges the need for introducing new high-resolution screening methods for the detection of genetic imbalances. [Copyright &y& Elsevier]

Awareness under anesthesia, also known as unintentional intraoperative awareness, occurs when a patient unintentionally becomes aware while under general anesthesia. Although unintentional intraoperative awareness occurs rarely, patients who experience this may develop anxiety disorders of varying severity, including posttraumatic stress disorder. Perianesthesia nurses can play an important role in the prevention and management of unintentional intraoperative awareness in patients. [Copyright &y& Elsevier]

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The article explores the study which evaluates patient support services as a primary area in which practices among dental schools in the U.S. can be reviewed. It analyzes the admission services such as screening and emergency dental service as a primary point-of-entry for patients in dental schools. It looks into the delegation of responsibilities where patient management is stressed as a multifaceted challenge for dental schools and four basic concerns were considered.

MRI offers detailed diagnostic images without ionizing radiation; however, there are considerable safety concerns associated with high electromagnetic field strength. With increasing use of high and ultra high (7T) magnetic field strength, adequate patient preparation and screening for ferrous material is increasingly important. We review current safety standards for patient screening and preparation and how they are implemented at our institution. In addition, we describe a novel supplemental screening technique wherein the lights are dimmed in response to detected ferrous metal at the threshold of Zone IV. [ABSTRACT FROM AUTHOR]

Subcutaneous Implantable Cardioverter-Defibrillators (S-ICDs) are used for prevention of sudden cardiac death triggered by ventricular arrhythmias. T Wave Over Sensing (TWOS) is an inherent risk with S-ICDs which can lead to inappropriate shocks. A major predictor of TWOS is a high T:R ratio (the ratio between the amplitudes of the T and R waves). Currently, patients' Electrocardiograms (ECGs) are screened over 10 s to measure the T:R ratio to determine the patients' eligibility for S-ICD implantation. Due to temporal variations in the T:R ratio, 10 s is not a long enough window to reliably determine the normal values of a patient's T:R ratio. In this paper, we develop a convolutional neural network (CNN) based model utilising phase space reconstruction matrices to predict T:R ratios from 10-second ECG segments without explicitly locating the R or T waves, thus avoiding the issue of TWOS. This tool can be used to automatically screen patients over a much longer period and provide an in-depth description of the behavior of the T:R ratio over that period. The tool can also enable much more reliable and descriptive screenings to better assess patients' eligibility for S-ICD implantation. [ABSTRACT FROM AUTHOR]