Opioid distribution trends in California post recreational marijuana legalization The opioid epidemic has risen to an all-time high. Harm reduction and prevention policies have not alleviated this crisis. Recent investigations have highlighted the efficacy and safety of marijuana-based products for pain management. Providing alternative pain treatment options may help mitigate the opioid epidemic. The distribution of codeine, fentanyl, hydrocodone, morphine, and oxycodone per 100K people and by 3-digit zip codes and overdose rates from 2014 to 2018 in California, which legalized recreational marijuana in 2016, were compared to Texas, where marijuana is functionally prohibited. Drug weights were obtained from the Automation of Reports and Consolidated Orders System and converted to oral morphine milligram equivalents. Overdose data was retrieved from the Centers for Disease Controls WONDER database. California (-43.7%) and Texas (-27.3%) showed significant reductions in cumulative opioid distribution from 2014 to 2018. Opioid distribution per 100K people decreased -38.9% in California relative to -26.4% in Texas. Opioid and heroin overdoses increased between 1999 and 2019 by +11.6% in California but +272.7% in Texas. This evidence supports marijuana legalization as a mitigating factor to the opioid epidemic. Continued studies on safer pain management alternatives and policies will help identify measures that help combat the opioid epidemic.
Health inequities in SARS-CoV-2 infection, seroprevalence, and COVID-19 vaccination: Results from the East Bay COVID-19 study Comprehensive data on transmission mitigation behaviors and both SARS-CoV-2 infection and serostatus are needed from large, community-based cohorts to identify COVID-19 risk factors and the impact of public health measures. From July 2020-March 2021, approximately 5,500 adults from the East Bay Area, California were followed over three data collection rounds to investigate the association between geographic and demographic characteristics and transmission mitigation behavior with SARS-CoV-2 prevalence. We estimated the populated-adjusted prevalence of antibodies from SARS-CoV-2 infection and COVID-19 vaccination, and self-reported COVID-19 test positivity. Population-adjusted SARS-CoV-2 seroprevalence was low, increasing from 1.03% (95% CI: 0.50-1.96) in Round 1 (July-September 2020), to 1.37% (95% CI: 0.75-2.39) in Round 2 (October-December 2020), to 2.18% (95% CI: 1.48-3.17) in Round 3 (February-March 2021). Population-adjusted seroprevalence of COVID-19 vaccination was 21.64% (95% CI: 19.20-24.34) in Round 3, with Whites having 4.35% (95% CI: 0.35-8.32) higher COVID-19 vaccine seroprevalence than non-Whites. No evidence for an association between transmission mitigation behavior and seroprevalence was observed. Despite >99% of participants reporting wearing masks, non-Whites, lower-income, and lower-educated individuals had the highest SARS-CoV-2 seroprevalence and lowest vaccination seroprevalence. Results demonstrate that more effective policies are needed to address these disparities and inequities.
Melodic Intonation Therapy for aphasia: A multi-level meta-analysis of randomised-controlled-trial and individual-participant data AO_SCPLOWBSTRACTC_SCPLOWMelodic Intonation Therapy (MIT) is a prominent rehabilitation programme for individuals with post-stroke aphasia. The present meta-analysis investigated the efficacy of MIT while considering outcome measure quality, experimental design, influence of spontaneous recovery, MIT protocol, and level of generalisation.

An extensive literature search identified 606 studies in major databases and trials registers; of those, 22 studies, overall 129 participants, met all eligibility criteria. Multi-level mixed- and random-effects models served to separately meta-analyse RCT and non-RCT data.

RCT evidence on validated measures revealed a small-to-moderate standardised effect in non-communicative language expression for MIT, with substantial uncertainty. Unvalidated measures attenuated MITs effect size compared to validated tests. MITs effect size was 5.7 times larger for non-RCT data compared to RCT data. Effect size in non-RCT data decreased with number of months post-stroke, suggesting confound through spontaneous recovery. Variation from the original MIT protocol did not systematically alter benefit from treatment. Progress on validated tests arose mainly from gains in repetition tasks rather than other domains of verbal expression such as everyday communication ability.

The current results confirm the promising role of MIT in improving trained/untrained performance with unvalidated measures, alongside validated repetition tasks; whilst highlighting possible limitations in promoting everyday communication ability. Infrequent intranasal oxytocin followed by positive social interaction improves symptoms in autistic children: a pilot randomized clinical trial There are currently no approved drug interventions for social behavior dysfunction in autism spectrum disorder (ASD). Previous trials investigating effects of daily intranasal oxytocin treatment have reported inconsistent results and have not combined it with positive social interaction. However, In two preclinical studies we established that treatment every-other-day rather than daily is more efficacious in maintaining neural and behavioral effects by reducing receptor desensitization. We aimed to establish whether a 6-week intranasal oxytocin compared with placebo treatment, followed by a period of positive social interaction, would produce reliable symptom improvements in children with ASD. A pilot double-blind, randomized, crossover design trial was completed including 41 children with ASD aged 3-8 years. Primary outcomes were the Autism Diagnostic Observation Schedule-2 (ADOS-2) and social responsivity scale-2 (SRS-2). Secondary measures included cognitive, autism and caregiver-related questionnaires and social attention assessed using eye-tracking. Significant improvements were found for oxytocin relative to placebo in primary outcome measures (total ADOS-2 and SRS-2 scores, ps < 0.001) and in behavioral adaptability and repetitive behavior secondary measures. Altered SRS-2 scores were associated with increased saliva oxytocin concentrations. Additionally, oxytocin significantly increased time spent viewing dynamic social compared to geometric stimuli and the eyes of angry, happy and neutral expression faces. There were no adverse side-effects of oxytocin treatment. Overall, results demonstrate that a 6-week intranasal oxytocin treatment administered every other day and followed by positive social interactions can improve clinical, eye-tracking and questionnaire-based assessments of symptoms in young autistic children. Colorectal Cancer Disparities Across the Continuum of Cancer Care: A Systematic Review and Meta-Analysis ImportanceDespite increases in screening among vulnerable populations, colorectal cancer disparities persist.

ObjectiveTo direct future efforts towards high impact opportunities in addressing these disparities, we performed a systematic review and meta-analysis of the colorectal cancer disparities literature with a focus on the utilization of Surgery, the primary treatment for colorectal cancer.

Data SourcesTwo electronic databases (PubMed and SCOPUS) were searched for prospective and retrospective studies reporting on colorectal cancer disparities between 2011 and March 29, 2021.

Study SelectionStudies for the systematic review were selected if: (1) reported on disparities within colorectal, colon, or rectal cancer (2) articles were published in the English language (3) articles used only United States-sourced data.

Studies for the meta-analysis were selected if: (1) reported on at least one of three utilization of surgery outcomes: receipt of colorectal, colon, or rectal surgery, refusal of surgery, or receipt of laparoscopic versus open surgery (2) Outcomes were reported as Odds ratio according to multivariate analysis.

Data Extraction and SynthesisQuality appraisal and data extraction were performed independently by 2 reviewers using the Newcastle-Ottawa Scale for quality assessment. For the meta-analysis, pooled multivariate odds ratios for the three outcomes regarding utilization of surgery were separately calculated according to fixed or random-effects models. Reporting followed the Preferred Reporting Items for Systematic Review and Meta-analyses guidelines.

Main Outcomes and MeasuresSystematic Review: The volume of publications attributed to the following sectors of the colorectal cancer care continuum: (1) Prevention, Screening, or Diagnosis (2) Treatment (3) Survivorship (4) End-of-life Care. Meta-analysis: Receipt of Colorectal, Colon, or Rectal Surgery and Black Race, Refusal of Surgery and Black Race, or Receipt of Laparoscopic versus Open Surgery and Black Race.

ResultsThe systematic review included 1,199 relevant publications. Among them, 60% were focused on Prevention, Screening, or Diagnosis, followed by Survivorship (20%), Treatment (15%), and End-of-Life Care (1%). Within the studies reporting on treatment disparities, 46% were focused on Race/Ethnicity, followed by Socioeconomic Status (28%), Age (17%), Gender (6%), Disabilities/Comorbidities (3%), and LGBTQI+ (0%). A total of 16 studies, including 1,110,674 patients, were applied to three separate meta-analyses regarding utilization of Surgery. Patients of black race were less likely to receive colorectal, or colon, or rectal surgery (OR 0.75, 95% CI 0.67-0.83), less likely to receive laparoscopic versus open colorectal cancer surgery (OR 0.91, 95% CI 0.88-0.94), and twice as likely to refuse colon surgery (OR 2.41, 95% CI 1.91-3.06).

Conclusions and RelevanceThe majority of research, to date, related to colorectal cancer disparities is focused on prevention, screening, or diagnosis and a minimal amount is dedicated to treatment. Additionally, all of the limited publications related to colorectal cancer surgery, as a treatment modality, are observational in nature. The application of this knowledge of past efforts and current continuing adverse outcomes is required in order to shift the focus of the research community towards treatment. In particular, research addressing surgical disparities is necessary, as surgery remains the primary treatment for colorectal cancer. Deceased donor kidney degradomics indicates cytoskeletal proteolytic alterations impacting post-transplant function. BackgroundIn brain death, cerebral injury contributes to systemic biological dysregulation, causing significant cellular stress in donor kidneys that adversely impacts the quality of grafts. Here, we hypothesized that DBD kidneys may undergo proteolytic processes that renders grafts susceptible to post-transplant dysfunction.

Material & MethodsUsing mass spectrometry and immunoblotting analyses, we profiled degradation patterns of cytoskeletal proteins in deceased (n=55) and living (n=10) donor kidneys.

ResultsWe found that in DBD kidneys, key podocyte cytoskeletal proteins had been proteolytically cleaved. Generated degradation profiles were not associated to donor related demographic and clinical factors but were associated to suboptimal post-transplant function. Strikingly, -actinin -4 and Talin-1 degradation profiles were not observed in circulatory-death or living-donor kidneys. As Talin-1 is a specific proteolytic target of Calpain-1, we investigated a potential trigger of Calpain activation and Talin-1 degradation using ex-vivo precision-cut human kidney slices and in-vitro immortalised human podocytes. Notably, we found that Transforming-Growth Factor-{beta} (TGF-{beta}) activated Calpain-1 and proteolytically cleaved Talin-1 to generate distinct peptide fragments. These peptide fragments were of similar size and matched the degradation patterns observed in DBD kidneys. Talin-1 degradation was prevented in vitro by Calpain-1 inhibition.

ConclusionsHere, we provide initial evidence that DBD kidneys are susceptible to cytoskeletal protein degradation that impacts posttransplant kidney function. Subsequent studies should aim to further investigate the link between brain death and activation of proteolytic pathways exploring new therapeutic opportunities. Serum Vitamin D levels are associated with increased COVID-19 severity and mortality independent of whole-body and visceral adiposity INTRODUCTIONCoronavirus disease (COVID-19) is a global pandemic. Vitamin D deficiency has been associated with susceptibility to infectious disease. In this study, the association between COVID-19 outcomes and vitamin D levels in patients attending a COVID-19 reference center in Mexico City are examined.

METHODSConsecutive patients with confirmed COVID-19 were evaluated. All patients underwent clinical evaluation and follow-up, laboratory measurements and a thoracic computerized tomography, including the measurement of epicardial fat thickness. Low vitamin D was defined as levels <20ng/mL (<50nmol/L) and deficient Vitamin D as a level [&le;]12ng/mL (<30nmol/L)

RESULTSOf the 551 patients included, low vitamin D levels were present in 45.6% and deficient levels in 10.9%. Deficient Vitamin D levels were associated with mortality (HR 2.11, 95%CI 1.24-3.58, p=0.006) but not with critical COVID-19, adjusted for age, sex, body-mass index and epicardial fat. Using model-based causal mediation analyses the increased risk of COVID-19 mortality conferred by low vitamin D levels was partly mediated by its effect on D-dimer and cardiac ultrasensitive troponins. Notably, increased risk of COVID-19 mortality conferred by low vitamin D levels was independent of BMI and epicardial fat.

CONCLUSIONVitamin D deficiency ([&le;]12ng/mL or <30nmol/L), is independently associated with COVID-19 mortality after adjustment for visceral fat (epicardial fat thickness). Low vitamin D may contribute to a pro-inflammatory and pro-thrombotic state, increasing the risk for adverse COVID-19 outcomes. Cell-free DNA ultra-low-pass whole genome sequencing to distinguish malignant peripheral nerve sheath tumor (MPNST) from its benign precursor lesion: a cross-sectional study BackgroundThe leading cause of mortality for patients with the Neurofibromatosis type 1 (NF1) cancer predisposition syndrome is development of Malignant Peripheral Nerve Sheath Tumor (MPNST), an aggressive soft tissue sarcoma. In the setting of NF1, this cancer type frequently arises from within its common and benign precursor, plexiform neurofibroma (PN). Transformation from PN to MPNST is challenging to diagnose due to difficulties in distinguishing cross-sectional imaging results and intralesional heterogeneity resulting in biopsy sampling errors.

Methods and FindingsThis multi-institutional study from the National Cancer Institute and Washington University in St. Louis used fragment size analysis and ultra-low-pass whole genome sequencing (ULP-WGS) of plasma cell-free DNA (cfDNA) to distinguish between MPNST and PN in patients with NF1. Following in-silico enrichment for short cfDNA fragments and copy number analysis to estimate the fraction of plasma cfDNA originating from tumor (tumor fraction), we developed a noninvasive classifier which differentiates MPNST from PN with 86% pre-treatment accuracy (91% specificity, 75% sensitivity), and 89% accuracy on serial analysis (91% specificity, 83% sensitivity). Healthy controls without NF1 (subjects = 16, plasma samples = 16), PN (subjects = 23, plasma samples = 23), and MPNST (subjects = 14, plasma samples = 46) cohorts showed significant differences in tumor fraction in plasma (P = 0.001 as well as cfDNA fragment length (P < 0.001) with MPNST samples harboring shorter fragments and being enriched for tumor-derived cfDNA relative to PN and healthy controls. Mutational analysis demonstrated focal NF1 copy number loss in PN and MPNST patient plasma but not in healthy controls. Greater genomic instability including alterations associated with malignant transformation (focal copy number gains in chromosome arms 1q, 7p, 8q, 9q, and 17q; focal copy number losses in SUZ12, SMARCA2, CDKN2A/B, and chromosome arms 6p and 9p) was more prominently observed in MPNST plasma. Furthermore, the sum of longest tumor diameters (SLD) visualized by cross-sectional imaging correlated significantly with paired tumor fractions in plasma from MPNST patients (r = 0.39, P = 0.024). On serial analysis, tumor fraction levels in plasma dynamically correlated with treatment response to therapy and minimal residual disease (MRD) detection before relapse. Study limitations include a modest MPNST sample size despite accrual from two major referral centers for this rare malignancy, and lack of uniform treatment and imaging protocols representing a real-world cohort.

ConclusionsTumor fraction levels derived from cfDNA fragment size and copy number alteration analysis of plasma cfDNA using ULP-WGS significantly correlated with MPNST tumor burden, accurately distinguished MPNST from its benign PN precursor, and dynamically correlated with treatment response. In the future, our findings could form the basis for improved early cancer detection and monitoring in high-risk cancer-predisposed populations.

Author summaryO_ST_ABSWhy was this study done?C_ST_ABS[tpltrtarr] Neurofibromatosis 1 (NF1) is the most common inherited cancer predisposition syndrome.
[tpltrtarr]The leading cause of mortality in NF1 is malignant peripheral nerve sheath tumor (MPNST), an aggressive soft tissue sarcoma that arises from a benign plexiform neurofibroma (PN) precursor lesion.
[tpltrtarr]Transformation from PN to MPNST is challenging to detect by imaging (due to difficulty in distinguishing PN from MPNST radiologically) or by biopsy (due to intralesional heterogeneity), which often delays the diagnosis of MPNST and results in a worsened prognosis.


What did the researchers do and find?[tpltrtarr] We conducted a multi-institutional study involving two large NF1 referral centers, the National Cancer Institute and Washington University in St. Louis, involving 73 patients from whom plasma cell-free DNA (cfDNA) was analyzed using ultra-low-pass whole genome sequencing (ULP-WGS).
We found that cfDNA from patients with MPNST harbors a shorter fragmentation profile compared to patients with PN or healthy donors. Using sequencing reads from this fragmentation profile, we quantified genome-wide copy number alterations (CNAs) in cfDNA and used CNAs to estimate the fraction of plasma cfDNA originating from tumor.
[tpltrtarr]Tumor fraction in plasma cfDNA distinguished pre-treatment MPSNT from PN with 86% accuracy. Plasma cfDNA from MPNST and PN patients harbored focal copy number loss of NF1, not found in healthy donors. Strikingly, MPNST patient cfDNA also had significantly greater tumor genomic instability compared to PN, with copy number alterations in key genomic loci previously observed in MPNST tissue (i.e., gain of chromosome arm 8q and loss of 9p), which enabled sensitive and specific liquid biopsy discrimination of MPNST from PN.
[tpltrtarr]Plasma-derived tumor fraction correlated with tumor size from imaging in MPNST patients, and serial cfDNA analysis demonstrated the potential for noninvasive detection of minimal residual disease, treatment response assessment, and the potential for even greater assay sensitivity.


What do these findings mean?[tpltrtarr] Our findings suggest that cfDNA fragment analysis followed by ULP-WGS has the potential to be developed as a biomarker for treatment response, and as a screening assay for early detection of MPNST.
[tpltrtarr]This study provides, to our knowledge, the first evidence for the ability of liquid biopsy to distinguish between benign and malignant tumors in a heritable cancer predisposition syndrome. Pulsed electromagnetic fields may be effective for the management of primary osteoporosis: a systematic review and meta-analysis ObjectiveTo investigate the effectiveness of pulsed electromagnetic fields (PEMFs) for the management of primary osteoporosis in older adults.

DesignSystematic review and meta-analysis.

Data SourcesMEDLINE, EMBASE, Web of Science, CENTRAL and CCTR, Physiotherapy Evidence Database, CNKI, VIP, Wan Fang, ClinicalTrials.gov and Current controlled trials from the inception dates to April 30, 2021.

Eligibility criteria for study selectionRandomised controlled trials or quasi-randomised trials examining the effects of PEMFs compared to placebo or sham or other agents for the management of primary osteoporosis (including those with previous fractures).

Data extraction and synthesisTwo independent reviewers extracted data. Primary outcomes were bone mass and number of incident fractures. Secondary outcomes were functional assessments, quality of life, and adverse events. Risk of bias was assessed with the Cochrane Collaborations tool and certainty of evidence with the grading of recommendations assessment, development and evaluation (GRADE) framework. A random effects model was used to calculate mean differences and 95% confidence intervals.

ResultsEight trials including 396 participants met the inclusion criteria. Low certainty evidence showed that PEMFs was non-inferior to conventional pharmacological agents in preventing the decline of Bone Mineral Density (BMD) at the lumbar (MD 0.01; CI -0.04 to 0.06) and femur neck (MD 0.01; CI -0.02 to 0.04), and improving balance function measured by Berg Balance Scale (BBS) (MD 0.01; CI -0.09 to 0.11) and Timed Up and Go test (MD -0.04; CI -0.80 to 0.72), directly after intervention. The similar effects were observed in BMD and BBS at 12- and 24-weeks follow-up from baseline with moderate certainty evidence. Very low certainty evidence showed that PEMFs (versus exercise) had small but significant effect on BMD at the femur neck (MD 0.10; CI 0.01 to 0.20), and no effect on BMD at the lumbar (MD 0.15; CI -0.04 to 0.35).

ConclusionPEMFs had positive effects non-inferior to first-line treatment on BMD and balance function in older adults with primary osteoporosis, but with low to very low certainty evidence and short-term follow-ups. There is a need for high-quality randomised controlled trials evaluating PEMFs for the management of primary osteoporosis.

RegistrationPROSPERO CRD42018099518. Covid-19 lockdown: Ethnic differences in childrens self-reported physical activity and the importance of leaving the home environment. A longitudinal and cross-sectional study from the Born in Bradford birth cohort study. BackgroundIn England, the onset of COVID-19 and a rapidly increasing infection rate resulted in a lockdown (March-June 2020) which placed strict restrictions on movement of the public, including children. Using data collected from children living in a multi-ethnic city with high levels of deprivation, this study aimed to: (1) report childrens self-reported physical activity (PA) during the first COVID-19 UK lockdown and identify associated factors; (2) examine changes of childrens self-reported PA prior to and during the first UK lockdown.

MethodsThis study is part of the Born in Bradford (BiB) COVID-19 Research Study. PA (amended Youth Activity Profile), sleep, sedentary behaviours, daily frequency/time/destination/activity when leaving the home, were self-reported by 949 children (9-13 years). A sub-sample (n=634) also self-reported PA (Physical Activity Questionnaire for Children) pre-pandemic (2017-February 2020). Univariate analysis assessed differences in PA between sex and ethnicity groups; multivariable logistic regression identified factors associated with childrens PA. Differences in childrens levels of being sufficiently active were examined using the McNemar test examined change in PA prior to and during the lockdown, and multivariable logistic regression to identify factors explaining change.

ResultsDuring the pandemic, White British (WB) children were more sufficiently active (34.1%) compared to Pakistani Heritage children (PH) (22.8%) or  Other ethnicity children (O) (22.8%). WB children reported leaving the home more frequently and for longer periods than PH and O children. Modifiable variables related to being sufficiently active were frequency, duration, type of activity, and destination away from the home environment. There was a large reduction in children being sufficiently active during the first COVID-19 lockdown (28.9%) compared to pre-pandemic (69.4%).

ConclusionsPromoting safe extended periods of PA everyday outdoors is important for all children, in particular for children from ethnic minority groups. Childrens PA during the first COVID-19 UK lockdown has drastically reduced from before. Policy and decision makers, and practitioners should consider the findings in order to begin to understand the impact and consequences that COVID-19 has had upon childrens PA which is a key and vital behaviour for health and development. Machine Learning Approaches for Binary Classification to Discover Liver Diseases using Clinical Data For a medical diagnosis, health professionals use different kinds of pathological ways to make a decision for medical reports in terms of patients medical condition. In the modern era, because of the advantage of computers and technologies, one can collect data and visualize many hidden outcomes from them. Statistical machine learning algorithms based on specific problems can assist one to make decisions. Machine learning data driven algorithms can be used to validate existing methods and help researchers to suggest potential new decisions. In this paper, Multiple Imputation by Chained Equations was applied to deal with missing data, and Principal Component Analysis to reduce the dimensionality. To reveal significant findings, data visualizations were implemented. We presented and compared many binary classifier machine learning algorithms (Artificial Neural Network, Random Forest, Support Vector Machine) which were used to classify blood donors and non-blood donors with hepatitis, fibrosis and cirrhosis diseases. From the data published in UCI-MLR, all mentioned techniques were applied to find one better method to classify blood donors and non-blood donors (hepatitis, fibrosis, and cirrhosis) that can help health professionals in a laboratory to make better decisions. Our proposed ML-method showed a better accuracy score (e.g. 98.23% for SVM). Thus, it improved the quality of classification. Short Practical Regimen of Acupuncture for Melasma: A Prospective Cohort Study in a Tertiary Hospital in Thailand BackgroundMelasma is a common skin pigmentation disorder. Acupuncture shows benefits for patients with melasma, although no standardized method or optimal number of sessions have been determined.

ObjectiveTo comparatively assess clinical outcomes of melasma between five vs ten standard acupuncture sessions.

MethodsWe performed a prospective observational cohort study in all melasma patients at the Acupuncture Clinic, King Chulalongkorn Memorial Hospital, Bangkok, Thailand. All patients were treated with standard acupuncture procedure twice a week and were evaluated after the fifth and the tenth sessions of acupuncture, with a follow-up one week after the last session. Participants were divided into two treatment groups: Groups A and B received five and ten acupuncture sessions respectively. Melasma outcomes were assessed by using the Melanin Index (MI), Melasma Area and Severity Index (MASI), patient-reported improvement scores and acupuncture-related adverse events.

ResultsOf 113 participants, 67 received five sessions of acupuncture treatment while 39 received ten sessions. 7 participants did not finish treatment. After five sessions of acupuncture in Group A, the mean MI decreased by 28.7 (95%CI -38.5 to -18.8), whereas the median MASI decreased by 3.4 (-6.9, -1.2) points. After ten sessions of acupuncture in Group B, the mean MI decreased by 31.3 (95%CI -45.0 to -17.6), whereas the median MASI decreased by 5.4 (-9.9, - 3.0) points. The first five sessions of acupuncture had a higher effect on the change in magnitude than the last five sessions, although there was no statistically significant difference. However, ten-session of acupuncture, had not reached the peak benefit on melasma yet. Further studies should be done with a higher number of sessions to determine the optimal rounds of treatment. Twenty-nine participants reported minor side effects, mostly consisting of persistent pain and small hematoma. Group B had RR of having adverse events 1.8 times (95% CI 1.0-3.4) compared to group A.

ConclusionAcupuncture has a potential dose-response effect on clinical and patient-reported melasma outcomes with minor side effects. Evaluating a first fully automated interview grounded in Multiple Mini Interview (MMI) methodology: results from a feasibility study ObjectivesGlobal, Covid-driven restrictions around face-to-face interviews for healthcare student selection have forced admissions staff to rapidly adopt adapted online systems before supporting evidence is available. We have developed, what we believe is, the first fully automated interview grounded in Multiple Mini-Interview (MMI) methodology. This study aimed to explore test re-test reliability, acceptability and usability of the system.

Design, setting and participantsmixed-methods feasibility study in Physician Associate (PA) programmes from two UK and one US university during 2019 - 2020.

Primary, secondary outcomesFeasibility measures (test retest reliability acceptability and usability) were assessed using intra-class correlation (ICC), descriptive statistics, thematic and content analysis.

MethodsVolunteers took (T1), then repeated (T2), the automated MMI, with a seven-day interval (+/- 2) then completed an evaluation questionnaire. Admissions staff participated in focus group discussions.

ResultsSixty-two students and seven admission staff participated; 34 students and four staff from UK and 28 students and three staff from US universities.

Good-excellent test-retest reliability was observed with T1 and T2 ICC between 0.62-0.81 (p<0.001) when assessed by individual total scores (range 80.6-119), station total scores 0.6-0.91, p<0.005, individual site (all ICC[&ge;] 0.76 p<0.001) and mean test retest across sites 0.82 p<0.001 (95% CI 0.7-0.9).

Admissions staff reported potential to reduce resource costs and bias through a more objective screening tool for pre-selection or to replace some MMI stations in a  hybrid model. Maintaining human interaction through  touch points was considered essential.

Users positively evaluated the system, stating it was intuitive with an accessible interface. Concepts chosen for dynamic probing needed to be appropriately tailored.

ConclusionThese preliminary findings suggest that the system is reliable, generating consistent scores for candidates and is acceptable to end-users provided human touchpoints are maintained. Thus, there is evidence for the potential of such an automated system to augment healthcare student selection processes. Deep learning for caries detection using optical coherence tomography Early detection of dental caries has been one of the most predominant topics studied over the last few decades. Conventional examination through visual-tactile inspection and radiography can be inaccurate and destructive to the tooth structure. The development of optical coherence tomography (OCT) has given dentistry an alternative diagnostic technique, which has been proven by numerous studies, that it has better sensitivity, specificity, and non-invasive characteristics. The growing popularity of artificial intelligence (AI) also contributes to a more efficient and effective way of image-based detection and decision-making. However, previous studies, which have attempted to employ AI for caries assessment, did not incorporate high-quality ground truth data. Therefore, this study aims to bypass this issue and highlights the importance of high-quality data. A two-phase study was carried out to explore different methods for caries detection. Initially, the comparison of caries detection based on OCT and apical radiography by 5 experienced clinicians was conducted. Then, five convolutional neural networks (CNNs), including AlexNet, VGG-16, ResNet-152, Xception, and ResNext-101, in the scope of AI were employed to detect caries and compared with the findings of the 5 clinicians. The data was preprocessed and labeled with the ground truth corresponding to microcomputed tomography (micro-CT) with rigorous definition. The weighted Kappa statistics suggested that OCT ({varkappa}= .699, SD = .090) showed a higher accuracy rate than radiography ({varkappa}= .407, SD = .049), and CNNs ({varkappa}= .860, SD = .049) were rated higher than clinicians ({varkappa}= .679, SD = .113), both at a .05 significance level. The best result was carried out by ResNet-152, which demonstrated a high accuracy rate of 95.21% and a sensitivity of 98.85%. These findings illustrate the importance of ground truth data for AI training and the potential of deep CNN algorithms combined with OCT for diagnosing dental caries. The effect of stimulus duration on preferences for gain adjustments when listening to speech ObjectivesIn the personalisation of hearing aid fittings, gain is often adjusted to suit patient preferences using live speech. When using brief sentences as stimuli, the minimum gain adjustments necessary to elicit consistent preferences ( preference thresholds) were previously found to be much greater than typical adjustments in current practice. The current study examined the role of duration on preference thresholds.

DesignParticipants heard 2, 4 and 6-s segments of a continuous monologue presented successively in pairs. The first segment of each pair was presented at each individuals real-ear or prescribed gain. The second segment was presented with a {+/-}0-12 dB gain adjustment in one of three frequency bands. Participants judged whether the second was "better", "worse" or "no different" from the first.

Study SampleTwenty-nine adults, all with hearing-aid experience.

ResultsThe minimum gain adjustments needed to elicit "better" or "worse" judgments decreased with increasing duration for most adjustments. Inter-participant agreement and intra-participant reliability increased with increasing duration up to 4 s, then remained stable.

ConclusionsProviding longer stimuli improves the likelihood of patients providing reliable judgments of hearing-aid gain adjustments, but the effect is limited, and alternative fitting methods may be more viable for effective hearing-aid personalisation. Population Pharmacokinetic Analysis of Dexmedetomidine in Children using Real World Data from Electronic Health Records and Remnant Specimens AimOur objectives were to perform a population pharmacokinetic analysis of dexmedetomidine in children using remnant specimens and data from electronic health records (EHRs) and explore the impact of patients characteristics and pharmacogenetics on dexmedetomidine clearance.

MethodsDexmedetomidine dosing and patient data were gathered from EHRs and combined with opportunistically sampled remnant specimens. Population pharmacokinetic models were developed using nonlinear mixed-effects modeling. The first stage developed a model without genotype variables; the second stage added pharmacogenetic effects.

ResultsOur final study population included 354 post-cardiac surgery patients age 0 to 22 years (median 16 months). The final two-compartment model included allometric weight scaling and age maturation. Population parameter estimates and 95% confidence intervals were 27.3 L/hr (24.0 - 31.1 L/hr) for total clearance (CL), 161 L (139 - 187 L) for central compartment volume of distribution (V1), 26.0 L/hr (22.5 - 30.0 L/hr) for intercompartmental clearance (Q), and 7903 L (5617 - 11119 L) for peripheral compartment volume of distribution (V2). The estimate for postmenstrual age when 50% of adult clearance is achieved was 42.0 weeks (41.5 - 42.5 weeks) and the Hill coefficient estimate was 7.04 (6.99 - 7.08). Genotype was not statistically or clinically significant.

ConclusionOur study demonstrates the use of real-world EHR data and remnant specimens to perform a population PK analysis and investigate covariate effects in a large pediatric population. Weight and age were important predictors of clearance. We did not find evidence for pharmacogenetic effects of UGT1A4 or UGT2B10 genotype or CYP2A6 risk score.

What is already known about this subject{circ} Previous dexmedetomidine pharmacokinetic (PK) studies in pediatric populations have limited sample size.
{circ}Smaller studies present a challenge for identifying covariates that may impact individual PK profiles.


What this study adds{circ} We performed a dexmedetomidine population PK study with a large pediatric cohort using data obtained from electronic health records and remnant plasma specimens to enable increased sample size.
{circ}xsDifferences in PK due to UGT1A4 or UGT2B10 variants or CYP2A6 risk score are not clinically impactful for this population. The ANTsX ecosystem for quantitative biological and medical imaging The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis. A Cross-Sectional Examination of Conflict-of-Interest Disclosures of Physician-Authors Publishing in High-Impact US Medical Journals ObjectiveTo assess the accuracy of self-reported financial conflict-of-interest (COI) disclosures in the New England Journal of Medicine (NEJM) and Journal of the American Medical Association (JAMA) within the requisite disclosure period prior to article submission.

DesignCross-sectional investigation.

Data SourcesOriginal clinical-trial research articles published in NEJM (n = 206) or JAMA (n = 188) from January 1 to December 31, 2017; self-reported COI disclosure forms submitted to NEJM or JAMA with the authors published articles; Open Payments website (from database inception; latest search: August 2019).

Main outcome measuresFinancial data reported to Open Payments from 2014 to 2016 (time period that included all subjects requisite disclosure windows) were compared to self-reported disclosure forms submitted to the journals. Payments were defined as those not associated with a research study or formal research funding. Payment types were categorized as "disclosed," "undisclosed," "indeterminate," or "unrelated."

ResultsThirty-one articles from NEJM and 31 articles from JAMA met inclusion criteria. The physician-authors (n = 118) received a combined total of $7.48 million. Of the 106 authors (89.8%) who received payments, 86 (81.1%) received undisclosed payments. The top 23 most highly compensated received $6.32 million, of which $3.00 million (47.6%) was undisclosed. Disclosure rates were the equivalent between the top 23 and the entire sample.

ConclusionsHigh payment amounts, as well as high proportions of undisclosed financial compensation, regardless of amount received, comprised potential COIs for two influential US medical journals. Further research is needed to explain why such high proportions of general payments were undisclosed and whether journals that rely on self-reported COI disclosure need to reconsider their policies. Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs BackgroundPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Cancer patients have mainly accessed these services, but there is growing consensus about the importance of promoting access for patients with non-malignant disease. Bad survival prognosis and patients frailty are usual dimensions to decide PC inclusion.

ObjectivesThe main aim of this work is to design and evaluate three quantitative models based on machine learning approaches to predict frailty and mortality on older patients in the context of supporting PC decision making: one-year mortality, survival regression and one-year frailty classification.

MethodsThe dataset used in this study is composed of 39,310 hospital admissions for 19,753 older patients (age >= 65) from January 1st, 2011 to December 30th, 2018. All prediction models were based on Gradient Boosting Machines. From the initial pool of variables at hospital admission, 20 were selected by a recursive feature elimination algorithm based on the random forests GINI importance criterion. Besides, we run an independent grid search to find the best hyperparameters in each model. The evaluation was performed by 10-fold cross-validation and area under the receiver operating characteristic curve and mean absolute error were reported. The Cox proportional-hazards model was used to compare our proposed approach with classical survival methods.

ResultsThe one-year mortality model achieved an AUC ROC of 0.87 {+/-} 0.01; the mortality regression model achieved an MAE of 329.97 {+/-} 5.24 days. The one-year frailty classification reported an AUC ROC of 0.9 {+/-} 0.01. The Spearmans correlation between the admission frailty index and the survival time was -0.1, while the point-biserial correlation between one-year frailty index and survival time was -0.16.

ConclusionsOne-year mortality model performance is at a state-of-the-art level. Frailty Index used in this study behaves coherently with other works in the literature. One-year frailty classifier demonstrated that frailty status within the year could be predicted accurately. To our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty as two weakly correlated and complementary PC needs assessment criteria. Predictive models are available online at http://demoiapc.upv.es. Croup during the COVID-19 Omicron Variant Surge Croup is a common upper respiratory disease usually associated with parainfluenza virus, resulting in stridor, hoarse voice, barky cough, and variable respiratory distress. Here we examine the data at our center confirming a sharp increase in cases of croup associated with the Omicron variant. Data was retrospectively extracted from patient charts among those seen in the Emergency Department at Seattle Childrens Hospital. Inclusion criteria were patients who were assigned a diagnosis containing "croup" during either 5/30/2021-11/30/2021, a time period correlating with predominance of the COVID-19 Delta variant (B.1.617.2), or the initial phase of the Omicron variant surge (12/1/2021-1/15/2022). Contemporaneous publicly available local data on the proportion of SARS-CoV-2 samples in surrounding King County, Washington, with spike gene target failure on TaqPath PCR assays was used as a proxy for the proportion of infections caused by the Omicron variant. A total of 401 patients were diagnosed with croup during the Delta surge and 107 patients were diagnosed with croup during the Omicron surge. Patients who presented during the Omicron surge were more likely to test positive for COVID-19 (48.2% vs 2.8%, p < 0.0001). Children with a clinical diagnosis of croup during the Omicron surge were more likely to be prescribed racemic epinephrine as part of their care (21.5% vs 13.0%, p = 0.032). There were no differences in presenting age, rate of admission, rate of return to the ED within 72 hours, or admission among those who returned within 72 hours. During the Omicron surge, the incidence of croup nearly doubled compared to the rate in prior months, while at the same time the number of cases of parainfluenza virus identified decreased. Consistent with prior case reports, we have identified a sharp rise in cases of croup seen in our pediatric ED in parallel with the replacement of the SARS-CoV-2 Delta variant by Omicron as the dominant variant in our community. Airway management, procedural data, and mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19) In India, the second wave of coronavirus disease (COVID -19) was associated with a distinct surge in cases of invasive fungal infection with mucormycosis. This disease was seen typically in the sinonasal form in COVID-19 patients. Uncontrolled diabetes, steroid use in COVID-19 treatment, etc. were some of the postulated risk factors for the association of COVID 19 and Mucormycosis. The management plan of these cases included surgical debridement, systemic antifungal therapy, sugar control, and management of antifungal related systemic adverse effects. In this retrospective case record review, we aimed to evaluate the airway management plan, demographics, and overall outcomes in patients undergoing surgical resection for COVID-19 associated mucormycosis. Forty-one (71.9 %) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) had a diagnosis of rhino-orbital mucormycosis, and 2 patients (3.5%) were diagnosed with palatal mucormycosis. Total 44 (77.19 %) patients had co-morbidities. The most common co-morbidity was Diabetes Mellitus 42 (73.6%), followed by hypertension 21 (36.84%) and Acute kidney injury 14 (28.07%). We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 out of 57 patients. In our study, mortality occurred in 7 (12.28 %) patients. The median mortality time was 60 (range, 27-74) days. The median time to hospital discharge was 53.5 (range,10-85) days. Managing COVID-19 on its own is challenging and additional mucormycosis can lead to increased morbidity and mortality. Despite challenges and risks, timely and meticulous interventions can reduce complications. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

MethodsA literature-based substance use risk algorithm identified 696 ABCD Study(R) participants for hair sample collections between baseline and 2-year follow-up (spanning ages 9-13) for laboratory analysis. Chi-square and t-tests assessed differences between participants demographics, positive and negative hair tests, risk algorithm scores, and self-reported substance use.

ResultsHair testing confirmed that 17% of at-risk 9-13 year-olds had evidence of past 3-month use of one (n=99), two (n=17), three (n=3), or four (n=2) drug classes. After considering prescribed medication use, 11% had a positive test incongruent with self- or parent-report. No participant with a positive result self-reported substance use consistent with their toxicology results. Participants with positive tests under-reported use (p<.001), reported less sipping of alcohol (p<.001), and scored higher on the risk algorithm (p<.001) than those with negative hair toxicology.

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. Emergence and Evolution of Big Data Science in HIV Research: Bibliometric Analysis of Federally Sponsored Studies 2000-2019 BackgroundThe rapid growth of inherently complex and heterogeneous data in HIV/AIDS research underscores the importance of Big Data Science. Recently, there have been increasing uptakes of Big Data techniques in basic, clinical, and public health fields of HIV/AIDS research. However, no studies have systematically elaborated on the evolving applications of Big Data in HIV/AIDS research. We sought to explore the emergence and evolution of Big Data Science in HIV/AIDS-related publications that were funded by the US federal agencies.

MethodsWe identified HIV/AIDS and Big Data related publications that were funded by seven federal agencies from 2000 to 2019 by integrating data from National Institutes of Health (NIH) ExPORTER, MEDLINE, and MeSH. Building on bibliometrics and Natural Language Processing (NLP) methods, we constructed co-occurrence networks using bibliographic metadata (e.g., countries, institutes, MeSH terms, and keywords) of the retrieved publications. We then detected clusters among the networks as well as the temporal dynamics of clusters, followed by expert evaluation and clinical implications.

ResultsWe harnessed nearly 600 thousand publications related to HIV/AIDS, of which 19,528 publications relating to Big Data were included in bibliometric analysis. Results showed that (1) the number of Big Data publications has been increasing since 2000, (2) US institutes have been in close collaborations with China, Canada, and Germany, (3) some institutes (e.g., University of California system, MD Anderson Cancer Center, and Harvard Medical School) are among the most productive institutes and started using Big Data in HIV/AIDS research early, (4) Big Data research was not active in public health disciplines until 2015, (5) research topics such as genomics, HIV comorbidities, population-based studies, Electronic Health Records (EHR), social media, precision medicine, and methodologies such as machine learning, Deep Learning, radiomics, and data mining emerge quickly in recent years.

ConclusionsWe identified a rapid growth in the cross-disciplinary research of HIV/AIDS and Big Data over the past two decades. Our findings demonstrated patterns and trends of prevailing research topics and Big Data applications in HIV/AIDS research and suggested a number of fast-evolving areas of Big Data Science in HIV/AIDS research including secondary analysis of EHR, machine learning, Deep Learning, predictive analysis, and NLP. "What do you mean I can't have a doctor? This is Canada!" - A Qualitative Study of the Myriad Consequences for Unattached Patients Awaiting Primary Care Attachment BackgroundPatient access to primary healthcare (PHC) is the foundation of a strong healthcare system and healthy populations. Attachment to a regular PHC provider, a key to healthcare access, has seen a decline in some jurisdictions. This study explored the consequences of unattachment from a patient perspective, an under-studied phenomenon to date.

MethodsA realist-informed qualitative study was conducted with unattached patients in Nova Scotia, Canada. Semi-structured interviews with nine participants were conducted and transcribed for analysis. The framework method was used to carry out analysis, which was guided by Donabedians model of assessing healthcare access and quality.

ResultsFive key findings were noted in this study: 1) Participants experienced a range of consequences from not having a regular PHC provider. Participants used creative strategies to 2) attempt to gain attachment to a regular PHC provider, and, to 3) address their health needs in the absence of a regular PHC provider. 4) Participants experienced negative feelings about themselves and the healthcare system, and 5) stress related to the consequences and added work of being unattached and lost care.

ConclusionsUnattached patients experienced a burden of care related to lost care and managing their own health and related information, due to the download of medical record management and system navigation to them. These findings may underestimate the consequences for further at-risk populations who would not have been included in our recruitment. This may result in poorer health outcomes, which could be mitigated by interventions at the structural level, such as enhanced centralized waitlists to promote attachment. Such waitlists may benefit from a triage approach to appropriately attach patients based on need.