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Background Course of Alcohol Dependence Syndrome (ADS) is studded with multiple relapses. Personality factors are implicated as one of the influencing factors in the course of this disorder. Keeping in view of scarcity of Indian data available, the study was planned with the aim to find Personality traits more commonly associated with ADS patients, and identify specific traits, associated with relapses of ADS. Method With sample size of 100 consecutive cases and 100 controls, socio-demographic data was collected. Alcohol Use Disorder Identification Test (AUDIT) and Severity of Alcohol Use Disorder Test (SAD-Q) were administered to each of these patient. Personality dimensions were assessed with NEO-five factor inventory (NEO-FFI) (Costa and McCrae), for both groups and further compared for differences in the dimensions in each of its subscale. Results The NEO scores, showed statistically significant difference with Cases having higher scores in Neuroticism and control group in Openness and Conscientiousness. Neuroticism linked to higher scores of AUDIT and SADQ and also associated with relapses. Other traits also showed statistically significant association which are discussed. Conclusion As new factors are being explored for effective management, routine personality profiling is easily accomplished and can give delightful insight into focused and designed management plan.

Summary Introduction Vocal cord vibration after transoral CO2 LASER-guided thyroarytenoid (TA) myoneurectomy in adductor spasmodic dysphonia (AdSD) patients is unclear to date. The precise vibratory patterns in AdSD patients are difficult to evaluate with routine videolaryngostroboscopy. High-speed videolaryngoscopy (HSV) is an ideal choice to evaluate such patients. This study was performed to compare pre- and postoperative, after 6 months, vocal fold vibratory onset delay (VFVOD) and closed phase glottal cycle (CPGC) in AdSD patients following transoral CO2 LASER-guided TA myoneurectomy using the HSV. Materials and methods Retrospective study, conducted from January, 2016 to January, 2019, of the AdSD patients who underwent transoral CO2 LASER-guided TA myoneurectomy using the HSV. Patient data were acquired from the hospital database to evaluate VFVOD and CPGC from HSV recordings of the patients. VFVOD was calculated as sum of prephonatory delay (PPD) and steady-state delay (SSD). The PPD and SSD were evaluated and compared separately for each patient. The MedCal Version 19.2.6 was used for data analysis. Paired sample t test was performed to compute the significance of the difference between the mean of the dataset. A P value less than 0.05 was considered significant. Results A total of nine patients were included in the study, out of which three were females and six were males. The average age was 45.5 ± 6.9 years. The mean of postoperative PPD (166.8 ± 22.1), SSD (76.5 ± 8.6), and CPGC (62.6 ± 4.8) were significantly less than mean of preoperative PPD (222.6 ± 22.1), SSD (97.7 ± 9.5), and CPGC (71.6 ± 5 %), with P values of 0.0007, 0.0001, and 0.0001, respectively. Conclusions There was a significant decrease in VFVOD and CPGC posttransoral CO2 LASER-guided TA myoneurectomy in AdSD patients after 6 months follow-up. This study also establishes efficiency of the HSV to measure the vocal cord vibration in the patients with AdSD. The primary limitations of the study were the small sample size and its retrospective nature. Future prospective studies with increased sample size can further substantiate the findings of the work performed here.

Introduction and objectives Most of the studies evaluating the effect of cross links on spinal stability are performed in vitro on porcine or human spine segments and there is limited data regarding clinical benefits of cross link augmentation in traumatic injuries. In this study we aimed to evaluate the effects of cross-links insertion between rods on the fusion rates and post-surgical patients’ satisfaction among patients with traumatic thoracolumbar fractures who underwent posterior spinal fixation with pedicle screws. Materials and methods This study was conducted as a randomized clinical trial on 60 patients suffering from traumatic thoracolumbar vertebrae fractures. Patients were randomized into three groups: A (without any cross-link), B (One cross-link insertion) and C (two cross-links insertion). Six months after surgery outcomes were evaluated: fusion rates (plain X-ray and CT scan), Back pain (Visual Analog Scale) and patient satisfaction (fair, good, excellent). Results In group A 13 (65%) patients had structured bone fusion, but in 7 (35%) patients bone fusion was not observed. In both groups B and C, 19 patients (95%) had bone fusion, but only in 1 patient (5%) fusion failed (p = 0.009). In group A, fair satisfaction has the highest rate (8 patients (40%)) compared to the other groups. The highest reported severity of back pain was observed in group A while the lowest reported intensity of back pain was related to group B (p = 0.001). Conclusions Adding cross link to posterior spinal fixations of patients with traumatic thoracolumbar fractures can be associated with better final fusion results and patients’ satisfaction. However it is necessary to design studies with greater sample sizes to confirm this theory. Trial registration number: IRCT20120527009878N3.

Objective There is an unmet need for therapies that target the underlying pathophysiology of osteoarthritis (OA). However, defining appropriate measures for clinical trials of such therapies is challenging. Our objective is to propose concept clinical endpoints that directly capture clinical benefit in this setting and evaluate the feasibility of their use. Methods This analysis used the multi-center, longitudinal, observational Osteoarthritis Initiative (OAI) database. OAI participants primarily had knee OA, with follow-up of up to nine years and assessments of joints, surgical interventions, performance outcomes, and patient-reported outcomes (PROs). We examined this dataset to identify existing outcome measures of direct clinical benefit. We evaluated the feasibility of conducting trials using these candidate endpoints by estimating incidence rates and resulting required sample sizes and study durations in time-to-event analyses. Results We identified candidate endpoints based on total knee replacement (TKR) and composite endpoints defined by TKR and conservative thresholds of PROs of pain and function. Using time to TKR as an endpoint, a study with an average follow-up time of three years requires approximately 3,000 to 18,000 subjects depending on effect size. Alternatively, a composite endpoint such as 'time to TKR or severe pain or severely impaired functioning', the required sample sizes ranged from approximately 2,000 to 11,000 for a three-year study. Conclusion The proposed concept endpoints can reliably and feasibly evaluate effectiveness of therapies for this unmet need. In particular, the composite endpoint approach can substantially reduce sample sizes (up to approximately 40%) compared to the use of TKR alone.

Background: This study aimed at understanding the trend in extracellular fluid (ECF) change and estimating the efficacy of the early complex decongestive therapy (CDT) program in terms of prevalence of lower limb lymphedema, as well as at identifying the quality of life (QoL) associated with response to CDT after gynecological cancer therapy. Methods and Results: Thirty-one patients undergoing gynecological cancer treatment were enrolled and randomly assigned to the CDT and control groups. In the CDT group, CDT was started within 2 weeks after surgery for 30 minutes a day, for 2 weeks (5 days per week). The patients' QoL was assessed through the European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire; version 3. Inbody S10® (Biospace, Seoul, South Korea) was used to calculate the ECF. The assessment was performed at pre- and post-surgery and at 3, 6, and 12 months after surgery. Statistically significant differences, in favor of the CDT group, were encountered at the 3-month follow-up visit, especially with respect to the QoL score. Regarding the prevalence of lymphedema, no significant difference was observed between groups. The mean value of the impedance ratio was low in the CDT group during the entire 12 month follow-up. Conclusions: The results of the present study show that early CDT had a positive effect on the prevalence of lymphedema and body composition. Long-term follow-up studies with a larger sample size are needed to warrant the time-group effect of early rehabilitation.

Accurate diagnosis of a disease is essential in healthcare. Prediction models, based on classical regression techniques, are widely used in clinical practice. Machine Learning (ML) techniques might be preferred in case of a large amount of data per patient and relatively limited numbers of subjects. However, this increases the risk of overfitting, and external validation is imperative. However, in the field of ML, new and more efficient techniques are developed rapidly, and if recruiting patients for a validation study is time consuming, the ML technique used to develop the first model might have been surpassed by more efficient ML techniques, rendering this original model no longer relevant. We demonstrate a stepwise design for simultaneous development and validation of prediction models based on ML techniques. The design enables - in one study - evaluation of the stability and robustness of a prediction model over increasing sample size as well as assessment of the stability of sensitivity/specificity at a chosen cut-off. This will shorten the time to introduction of a new test in health care. We finally describe how to use regular clinical parameters in conjunction with ML based predictions, to further enhance differentiation between subjects with and without a disease.

PURPOSE To compare Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) with traditional ("legacy") patient-reported outcome measures (PROMs) in regard to correlations, ease of use, and quality criteria for upper (UE) and lower extremity (LE) orthopaedic conditions. METHODS A systematic search of the PubMed/MEDLINE database was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify published articles that referenced the various PROMIS PF measures. Two authors independently reviewed selected studies. The search returned 857 studies, 85 of which were selected for independent review by 2 authors. Of these, 54 were selected for inclusion. Mixed linear models were performed to assess for differences between legacy PROMs and PROMIS measures. RESULTS The combined sample size of all included studies yielded 6,074 UE and 9,366 LE patients. Overall, PROMIS PF measures demonstrated strong correlations with legacy PROMs among UE (weighted Pearson correlation, 0.624, standard error [SE] = 0.042; weighted Spearman correlation, 0.566, SE = 0.042) and LE patients (weighted Pearson correlation, 0.645, SE = 0.062; weighted Spearman correlation, 0.631, SE = 0.041). PROMIS PF questionnaires completed by UE patients had fewer questions than legacy PROMs (5.9 vs 17.7, P = .0093) and were completed in less time (90.5 vs 223.8 seconds, P = .084). PROMIS PF questionnaires completed by LE patients had fewer questions than legacy PROMs (4.81 vs 15.33, P < .001) and were completed in less time (63.6 vs 203.2 seconds, P = .0063). The differences for the reliability measures were not significant. CONCLUSIONS PROMIS PF scores correlate strongly with commonly used legacy PROMs in orthopaedics, particularly in UE and LE patients. PROMIS PF forms can be administered efficiently and to a broad patient population while remaining highly reliable. Therefore, they can be justified for standardized use among orthopaedic patients with UE and LE conditions, improving the ability to aggregate and compare outcomes in orthopaedic research. LEVEL OF EVIDENCE Level IV, systematic review of Level I-IV evidence.

Experimental tests of interventions need to have sufficient sample size to constitute a robust test of the intervention's effectiveness with reasonable precision and power. To estimate the required sample size adequately, researchers are required to specify an effect size. But what effect size should be used to plan the required sample size? Various inroads into selecting the a priori effect size have been suggested in the literature-including using conventions, prior research, and theoretical or practical importance. In this paper, we first discuss problems with some of the proposed methods of selecting the effect size for study planning. We then lay out a method for intervention researchers that provides a way out of many of these problems. The proposed method requires setting a meaningful change definition, it is specifically suited for applied researchers interested in planning tests of intervention effectiveness. We provide a hands-on walk through of the method and provide easy-to-use R functions to implement it.

ObjectivesPrevious studies on the association between psychosocial work factors and blood pressure mainly focused on specific occupations or populations and had limited sample sizes. We, therefore, investigated the associations between psychosocial work factors and blood pressure in a large general working population in the Netherlands.MethodsWe included 63 800 employees from the Netherlands, aged 18–65 years, with blood pressure measurements and a reliable job code at baseline. Psychosocial work factors (job strain, effort–reward imbalance (ERI) and emotional demands) in the current job were estimated with three recently developed psychosocial job exposure matrices. To examine the associations, regression analyses adjusted for covariates (age, sex, body mass index, education, monthly income, pack-years, smoking, alcohol consumption and antihypertensive medication (not included for hypertension)) were performed.ResultsHigher job strain was associated with higher systolic blood pressure (SBP) (B (regression coefficients) (95% CI) 2.14 (1.23 to 3.06)) and diastolic blood pressure (DBP) (B (95% CI) 1.26 (0.65 to 1.86)) and with higher odds of hypertension (OR (95% CI) 1.43 (1.17 to 1.74)). Higher ERI was associated with higher DBP (B (95% CI) 4.37 (3.05 to 5.68)), but not with SBP or hypertension. Higher emotional demands were associated with lower SBP (B (95% CI) −0.90 (−1.14 to −0.66)) and lower odds of hypertension ((OR) (95% CI) 0.91 (0.87 to 0.96)).ConclusionsIn the general working population, employees in jobs with high job strain and ERI have higher blood pressure compared with employees with low job strain and ERI. Emotional demands at work are inversely associated with blood pressure.

Objectives Recent advancements in high-resolution imaging have improved the diagnostic assessment of magnetic resonance imaging (MRI) for intralabyrinthine schwannoma (ILS). This systematic review aimed to evaluate the diagnostic performance of MRI for patients with ILS. Methods Ovid-MEDLINE and EMBASE databases were searched for related studies on the diagnostic performance of MRI for patients with ILS published up to February 10, 2020. The primary endpoint was the diagnostic performance of MRI for ILS. The quality of the enrolled studies was assessed using tailored questionnaires and the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. Results Overall, 6 retrospective studies that included 122 patients with ILS from a parent population of 364 were included. The sample size, parent population and its composition, reference standard, detailed parameters of MRI, and even the diagnostic methods varied between the studies. The studies had moderate quality. The sensitivity of combination of T2WI and CE-T1WI was over 90%. Relative sensitivity of T2WI comparative to CE-T1WI ranged from 62% to 100%, and the specificity were 100%. Conclusions MRI has acceptable diagnostic performance for ILS. There is a need for well-organized research to reduce the factors causing heterogeneity.

Left–right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last 4 years, the ENIGMA‐Laterality Working Group has published six studies of gray matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population‐level mapping of average asymmetry was achieved, including an intriguing fronto‐occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA's multi‐dataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for gray matter asymmetry based on large, international, samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders: autism spectrum disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; pediatric obsessive–compulsive disorder was associated with altered subcortical asymmetry; major depressive disorder was not significantly associated with changes of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders., Left–right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Over the last four years, the ENIGMA‐Laterality Working Group has published six studies of grey matter morphological asymmetry in health and disease, based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. Here we review the findings from these six studies.

Aim: To investigate if acupuncture reduces nausea and vomiting in terminally ill patients. Design: A comparative effectiveness research design was used to generate evidence-based knowledge close to practice for the use of clinicians. The sample size was calculated to 136 patients randomised into an intervention and a control group, respectively. Nausea and vomiting were measured using the EORTC QLQ-c15-PAL (European Organisation for Research and Treatment of Cancer, Quality of Life Questionnaire, core 15, Palliation). Location: The trial was conducted among terminally ill patients admitted to three in-bed hospices in Demark. Participants: Terminally ill patients suffering from nausea and/or vomiting; 95% of patients had cancer. Intervention: The intervention group received acupuncture in addition to usual care for three days. We used the acupuncture spots: Pericardium-6, Stomach-36, Liver-3 and Yin Tang. The control group received usual care only. Results: In total, 136 patients were randomised, 24 patients withdrew resulting in a total sample of 112 patients: 52 patients in the intervention group and 60 patients in the control group. In the intervention group, 75% of the patients experienced a reduction of their nausea score after the intervention compared to 55% in the control group. The statistical difference was p = 0.028. In the intervention group, 52% of the patients did not experience nausea at all after the intervention compared to 30% in the control group. In the intervention group, 31% of the patients were still vomiting after the intervention compared to 34% in the control group; no statistically significant difference was found. Conclusion: Acupuncture reduced the experience of nausea among terminally ill patients but did not reduce vomiting. Thus, acupuncture is recommended to reduce nausea among terminally ill patients.

OBJECTIVE: To describe the characteristics of Covid-19 randomized clinical trials (RCTs) and examine the association between trial characteristics and the likelihood of finding a significant effect. STUDY DESIGN: We conducted a systematic review to identify RCTs (up to October 21, 2020) evaluating drugs or blood products to treat or prevent Covid-19. We extracted trial characteristics (number of centers, funding sources, and sample size) and assessed risk of bias (RoB) using the Cochrane RoB 2.0 tool. We performed logistic regressions to evaluate the association between RoB due to randomization, single vs. multicentre, funding source, and sample size, and finding a statistically significant effect. RESULTS: We included 91 RCTs (n = 46,802); 40 (44%) were single-center, 23 (25.3%) enrolled

Background and objective There is evidence of short- and long-term impairment of physical performance in patients with COVID-19 infection, but a verification of measures of physical impairment in this condition is lacking. We reviewed the measures used to assess physical performance in these patients. Secondary targets were measures of exercise or daily life activities induced symptoms. Methods Medline, CINAHL, and Pedro databases were searched from January 2020 to February 2021 for articles in the English language. Two investigators independently conducted the database search, screened all titles and/or abstracts based on the inclusion criteria and independently scored the studies. The quality of the studies was evaluated by two reviewers according to the NIH quality assessment tool for observational cohort and cross-sectional studies. Discrepancies were resolved through consensus. Results Out of 156 potentially relevant articles, 31 observational studies (8 cross-sectional), 1 randomized controlled trial, and 1 protocol were included. The quality of most of 31 evaluable studies was judged as low (11 studies) or fair (14 studies). Sample sizes of each study ranged from 14 to 20,889 patients. Among the 28 reported measures, Barthel Index (42.4% of studies), Six-Minute Walking Distance Test (36.4%), Short Physical Performance Battery (21.2%) and 1-Minute Sit-to-Stand (12.1%) were the most used. Fifteen% and 36% of studies reported exercise induced desaturation and dyspnoea when performing the assessments, respectively. Other exercise induced symptoms were fatigue and pain. Studies reported wide ranges of impairment in physical performance as compared to “reference” values (range of mean or median reported values vs “reference values”: 11-77 vs 100 points for Barthel Index; 11-22 vs 22–37 repetitions/min for 1m-STS; 0.5-7.9 vs 11.4 ±1.3 points for SPPB; and 45-223 vs 380-782 meters for 6MWT respectively). Conclusion This review found that a wide variety of functional status tests have been used, making comparisons difficult between studies. These measures show impairment in physical performance in COVID-19 patients. However, the quality of most of the studies was judged as low or fair.

Clinical trials require participation of numerous patients, enormous research resources and substantial public funding. Time-consuming trials lead to delayed implementation of beneficial interventions and to reduced benefit to patients. This manuscript discusses two methods for the allocation of research resources and reviews a framework for prioritisation and design of clinical trials. The traditional error-driven approach of clinical trial design controls for type I and II errors. However, controlling for those statistical errors has limited relevance to policy makers. Therefore, this error-driven approach can be inefficient, waste research resources and lead to research with limited impact on daily practice. The novel value-driven approach assesses the currently available evidence and focuses on designing clinical trials that directly inform policy and treatment decisions. Estimating the net value of collecting further information, prior to undertaking a trial, informs a decision maker whether a clinical or health policy decision can be made with current information or if collection of extra evidence is justified. Additionally, estimating the net value of new information guides study design, data collection choices, and sample size estimation. The value-driven approach ensures the efficient use of research resources, reduces unnecessary burden to trial participants, and accelerates implementation of beneficial healthcare interventions.

Introduction Magnitudes of change in endothelial function research can be articulated using effect size statistics. Effect sizes are commonly used in reference to Cohen’s seminal guidelines of small (d = 0.2), medium (d = 0.5), and large (d = 0.8). Quantitative analyses of effect size distributions across various research disciplines have revealed values differing from Cohen’s original recommendations. Here we examine effect size distributions in human endothelial function research, and the magnitude of small, medium, and large effects for macro and microvascular endothelial function. Methods Effect sizes reported as standardized mean differences were extracted from meta research available for endothelial function. A frequency distribution was constructed to sort effect sizes. The 25th, 50th, and 75th percentiles were used to derive small, medium, and large effects. Group sample sizes and publication year from primary studies were also extracted to observe any potential trends, related to these factors, in effect size reporting in endothelial function research. Results Seven hundred fifty-two effect sizes were extracted from eligible meta-analyses. We determined small (d = 0.28), medium (d = 0.69), and large (d = 1.21) effects for endothelial function that corresponded to the 25th, 50th, and 75th percentile of the data distribution. Conclusion Our data indicate that direct application of Cohen’s guidelines would underestimate the magnitude of effects in human endothelial function research. This investigation facilitates future a priori power analyses, provides a practical guiding benchmark for the contextualization of an effect when no other information is available, and further encourages the reporting of effect sizes in endothelial function research.

As a reaction to the pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), a multitude of clinical trials for the treatment of SARS‐CoV‐2 or the resulting corona disease 2019 (COVID‐19) are globally at various stages from planning to completion. Although some attempts were made to standardize study designs, this was hindered by the ferocity of the pandemic and the need to set up clinical trials quickly. We take the view that a successful treatment of COVID‐19 patients (i) increases the probability of a recovery or improvement within a certain time interval, say 28 days; (ii) aims to expedite favorable events within this time frame; and (iii) does not increase mortality over this time period. On this background, we discuss the choice of endpoint and its analysis. Furthermore, we consider consequences of this choice for other design aspects including sample size and power and provide some guidance on the application of adaptive designs in this particular context.

As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes, such as clinical phenotypes. Current statistical approaches typically map cells to clusters and then assess differences in cluster abundance. Here we present co-varying neighborhood analysis (CNA), an unbiased method to identify associated cell populations with greater flexibility than cluster-based approaches. CNA characterizes dominant axes of variation across samples by identifying groups of small regions in transcriptional space-termed neighborhoods-that co-vary in abundance across samples, suggesting shared function or regulation. CNA performs statistical testing for associations between any sample-level attribute and the abundances of these co-varying neighborhood groups. Simulations show that CNA enables more sensitive and accurate identification of disease-associated cell states than a cluster-based approach. When applied to published datasets, CNA captures a Notch activation signature in rheumatoid arthritis, identifies monocyte populations expanded in sepsis and identifies a novel T cell population associated with progression to active tuberculosis.

Microscopic examination of stained peripheral blood smears is, nowadays, an indispensable tool in the evaluation of patients with hematological and non-hematological diseases. While a rapid automated quantification of the regular blood cells is available, recognition and counting of immature white blood cells (WBC) still relies mostly on the microscopic examination of blood smears by an experienced observer. Recently, there are efforts to improve the prediction by various machine learning approaches. An open dataset collection including the recently digitalized single-cell images for 200 patients, from peripheral blood smears at 100 × magnification, was used. We studied different morphological, fractal, and textural descriptors for WBC classification, with an aim to indicate the most reliable parameters for the recognition of certain cell types. Structural properties of both the mature and non-mature leukocytes obtained from (i) acute myeloid leukemia patients, or (ii) non-malignant controls, were studied in depth, with a sample size of about 25 WBC per group. We quantified structural and textural differences and, based on the statistical ranges of parameters for different WBC types, selected eight features for classification: Cell area, Nucleus-to-cell ratio, Nucleus solidity, Fractal dimension, Correlation, Contrast, Homogeneity, and Energy. Classification Precision of up to 100% (80% on average) was achieved.

Background Prior studies showed the association between inadequate health literacy (HL) and poor medication-related skills, while none of the published studies have reviewed and compared the existing instruments used to measure medication-related HL. This systematic review comprehensively summarizes the existing instruments that assess medication-related HL. Objectives To identify appropriate HL instruments related to medication use as screening tools for enhancing patients’ ability to use medications correctly. Methods This review retrieved medication-related HL instruments that were published between 2000 and 2019 from three databases (i.e., PubMed, Scopus, EMBASE) and by hand-searching. The PRISMA procedure was followed as well as the SURGE guideline to assess the quality of studies. Psychometric properties, HL dimensions, and types of medication information gleaned from the items in three types of HL instruments (i.e., general, disease-specific, medication-specific) were compared to identify appropriate medication-related HL instruments. Result Forty-eight instruments were identified from 44 studies, whereas 70.8% instruments were either disease- or medication-specific HL instruments. Most instruments with different sample sizes showed certain an extent of reliability and validity. The distributions of HL dimensions and types of medication information among the relevant items were varied across different types of instruments. The five instruments (named as the 16SQ, AKQ-CQ, DHLKI, AKT, and ChMLM) were identified as the most appropriate instruments for three types of medication-related HL, respectively. These appropriate instruments consistently covered items related to HL dimensions of literacy and comprehension and medication-related information regarding dosing, treatment indication, and side effects/precautions. Conclusion Of 48 identified instruments mainly derived from disease- or medication-specific studies, the five most appropriate medication-related HL instruments were identified to support clinicians in facilitating patients' correct medication use. Further confirmation to explore the usefulness among these instruments are needed.

Background The universal Surgical Risk Preoperative Assessment System (SURPAS) prediction models for postoperative adverse outcomes have good accuracy for estimating risk in broad surgical populations and for surgical specialties. The accuracy in individual operations has not yet been assessed. The objective of this study was to evaluate the Surgical Risk Preoperative Assessment System in predicting adverse outcomes for selected individual operations. Methods The SURPAS models were applied to the top 2 most frequent common procedural terminology codes in 9 surgical specialties and 5 additional common general surgical operations in the 2009 to 2018 database of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). Goodness of fit statistics were estimated, including c-indices for discrimination, Hosmer-Lemeshow graphs and P values for calibration, overall observed versus expected event rates, and Brier scores. Results The total sample size was 2,020,172, which represented 29% of the 6.9 million operations in the ACS NSQIP database. Average c-indices across 12 outcomes were acceptable (≥0.70) for 13 (56.5%) of the 23 operations. Overall observed-to-expected rates were similar for mortality and overall morbidity across the 23 operations. Hosmer-Lemeshow graphs over quintiles of risk comparing observed-to-expected rates of mortality and overall morbidity were similar for 52% and 70% of operations, respectively. Model performance was better in less complex operations and those done in patients with lower preoperative risk. Conclusion SURPAS displayed accuracy in estimating postoperative adverse events for some of the 23 operations studied, but not all. In the procedures where SURPAS was not accurate, developing disease or operation-specific risk models might be appropriate.

Background As the burden of treatment-resistant schizophrenia (TRS) on patients and society is high it is important to identify predictors of response to medications in TRS. The aim was to analyse whether baseline patient and study characteristics predict treatment response in TRS in drug trials. Methods A comprehensive search strategy completed in PubMed, Cochrane and Web of Science helped identify relevant studies. The studies had to meet the following criteria: English language clinical trial of pharmacological treatment of TRS, clear definition of TRS and response, percentage of response reported, at least one baseline characteristic presented, and total sample size of at least 15. Meta-regression techniques served to explore whether baseline characteristics predict response to medication in TRS. Results 77 articles were included in the systematic review. The overall sample included 7546 patients, of which 41% achieved response. Higher positive symptom score at baseline predicted higher response percentage. None of the other baseline patient or study characteristics achieved statistical significance at predicting response. When analysed in groups divided by antipsychotic drugs, studies of clozapine and other atypical antipsychotics produced the highest response rate. Conclusions This meta-analytic review identified surprisingly few baseline characteristics that predicted treatment response. However, higher positive symptoms and the use of atypical antipsychotics – particularly clozapine –was associated with the greatest likelihood of response. The difficulty involved in the prediction of medication response in TRS necessitates careful monitoring and personalised medication management. There is a need for more investigations of the predictors of treatment response in TRS.

COVID-19 pandemic challenges have accelerated the reliance on digital health fuelling the expanded incorporation of mobile apps into healthcare services, particularly for the management of long-term conditions such as chronic diseases (CDs). However, the impact of health apps on outcomes for CD remains unclear, potentially owing to both the poor adoption of formal development standards in the design process and the methodological quality of studies. A systematic search of randomised trials was performed on Medline, ScienceDirect, the Cochrane Library and Scopus to provide a comprehensive outlook and review the impact of health apps on CD. We identified 69 studies on diabetes (n = 29), cardiovascular diseases (n = 13), chronic respiratory diseases (n = 13), cancer (n = 10) or their combinations (n = 4). The apps rarely adopted developmental factors in the design stage, with only around one-third of studies reporting user or healthcare professional engagement. Apps differed significantly in content, with a median of eight behaviour change techniques adopted, most frequently pertaining to the ‘Feedback and monitoring’ (91%) and ‘Shaping knowledge’ (72%) categories. As for the study methodologies, all studies adopted a traditional randomised control trial (RCT) design, with relatively short follow-ups and limited sample sizes. Findings were not significant for the majority of studies across all CD, with most RCTs revealing a high risk of bias. To support the adoption of apps for CD management, this review reinforces the need for more robust development and appropriate study characteristics to sustain evidence generation and elucidate whether study results reflect the true benefits of apps or a biased estimate due to unsuitable designs.

Objective To identify and summarize the behavior change techniques (BCTs) included in behavior change interventions for promoting physical activity in persons with multiple sclerosis (MS). Data Sources PubMed, PsycINFO, Cumulative Index to Nursing and Allied Health Complete, Scopus, and Embase were initially searched in November 2019, and data extraction began in June 2020. Study Selection The inclusion criteria for studies were: adults older than 18 years with diagnosed MS, English language, clinical trial designs (ie, pre-post or randomized controlled trials), group or individual interventions, and home or community-based settings wherein physical activity was defined as a primary or secondary outcome. Exclusion criteria for studies included protocol manuscripts pending results, case studies, studies focused on populations with multiple chronic diseases, and interventions targeting multiple behaviors. Two researchers completed screening for study selection, and a third researcher served as a referee. Of the initially identified 8681 studies, 54 studies met selection criteria. Data Extraction Data extraction was completed by 3 researchers. Each article was coded by 2 of the 3 researchers, and a fourth researcher resolved discrepancies. Data extracted from each paper included study title, authors, country, year, sample size, study design, intervention details, physical activity outcomes, and BCTs. Data Synthesis Thirty-eight unique behavior change interventions were identified, and 53 of the 93 possible BCTs were included across the studies. The mean number of BCTs per study was 15, and studies and effect sizes across studies ranged from 0.04-1.49. Conclusions This review provides a comprehensive overview of BCTs as the active ingredients in behavior change interventions targeting physical activity in MS. Results from this study provide a compendium for future intervention development for increasing physical activity and improving overall health in MS.

Problem Recent identification of the early-onset obese-asthma phenotype has spurred exploration of ways to promote effective, long-term management behaviors for children with this comorbid presentation. Few studies have examined the needs of children with both asthma and obesity and little is known about optimal management options for this unique population. Therefore, the authors aimed to review, critique, and synthesize existing published research on health-management programs designed for children with comorbid asthma and obesity in order to describe the state of the science and recommend next steps in creating pediatric management programs. Eligibility criteria Articles selected for a full-text review were pediatric-focused, included children with both asthma and obesity diagnoses, and discussed the implementation and evaluation of a management program or the evaluation of a management behavior. Sample Fifteen articles were selected for review based on the inclusion criteria. Results Studies that included current evidence-based elements had better results than those that did not include such elements. Conclusions Based on this review, it is recommended that researchers use theory based, multicomponent, multimodal, family-focused, behaviorally-based interventions that address systems-level influences, social determinates of health, and children's developmental needs over time. Additionally, there is a need for studies with sample sizes adequate for power analyses that include the youngest children with asthma and obesity. Implications The need for effective programs for pediatric obese-asthma phenotype management creates the opportunity for nursing-led research and interventions to foster long-term health promotion for affected children and families.

Summary Background With increasing age physical performance decreases. However, especially in orienteering, with the risk of running too fast in relation to map reading skills and thus of not being able to process important map information correctly a lower running speed can be an advantage. Further, with increasing age and the often-greater experience, the susceptibility to errors should decrease yielding to the aim of the study to analyze the relationship between average speed and age in senior orienteering. Material & methods All national Competitions of Middle and Long Distance as well as the Swiss Championships in the Middle and Long Distance as well as in night orienteering were analyzed for the season 2018 and 2019 for all senior categories. Average running speed was calculated per category with the concept of performance km, whereby in 2018 ten competitions and in 2019 nine competitions yielding to a total sample size of 855 female and 950 male orienteers analyzed. Furthermore, polynomial analyses of second degree between average running speed and age were conducted with calculation of coefficient of determination and in addition multilinear regression analysis between average course time and age respectively distance absolved. Results Average age of peak performance was identified with 50.0 ± 2.3 years for men and 47.3 ± 3.1 for women in 2018 respectively 51.1 ± 3.1 years for men and 47.0 ± 3.0 for women in 2019. Furthermore, high coefficients of determination were identified with average values of 0.916 ± 0.061 in men and 0.910 ± 0.051 in women 2018 respectively 0.891 ± 0.102 in men and 0.913 ± 0.079 in women in 2019. Discussion The relatively high ages are probably due to the fact that Classic beginner mistakes such as running too fast compared to map reading skills become less common, which is reflected in an absolutely lower error rate and correspondingly leads to a less severe decrease in age-related performance.

Background Non–guideline-directed care (NGDC) is seen in ∼30% of testicular cancer patients and has been identified as a significant predictor of relapse. However, the potential impact of mismanagement on patient quality of life (QoL) is yet to be established. Objective To explore the impact of NGDC on long-term QoL in testicular cancer survivors (TCSs). Design, setting, and participants A retrospective review of TCSs, who completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) in person or via mail ≥6 mo after completion of treatment, was conducted. Outcome measurements and statistical analysis The validated questionnaire evaluates global health status (GHS); cognitive, social, physical, emotional, and role functioning; financial burden; and treatment-specific side effects. Results and limitations A total of 120 men with a median age of 31.5 (interquartile range: 24–42) yr completed the questionnaire. Thirty-four (28%) men received NGDC: overtreatment (44%), improper imaging (32%), and undertreatment (29%). Men with NGDC presented with a more advanced clinical stage (≥IIA: 64% vs 32%, p = 0.007) and were less likely to undergo surveillance (19% vs 37%, p = 0.016). Patients receiving guideline-directed care reported higher GHS (84.1 vs 77.5, p = 0.015), higher physical function scores (98.5 vs 91.2, p = 0.013), and fewer financial difficulties (5.8 vs 18.6, p = 0.006) than those receiving NGDC. Multivariable linear regression showed a significant association between NGDC and poorer GHS (p = 0.002). Limitations of the study include its retrospective nature, modest sample size due to a 21% response rate, and quality-of-life assessment at a single time point rather than serially over time. Conclusions In addition to treatment delay, avoidable morbidity, and higher rates of relapse, NGDC leads to inferior global QoL, worse physical functioning, and more financial stress. Patient summary We have previously shown how mismanagement of testicular cancer results in a higher rate of disease relapse. In this study, we emphasize how the lack of adherence to standard treatment guidelines can lead to worse quality of life outcomes and financial stress in testicular cancer survivors.

Objective: Is the level of shared decision-making (SDM) higher after introduction of a SDM package (including encounter decision aids on treatment options for heavy menstrual bleeding and training for clinicians) than before?. Methods: This before-after study, performed in OB-GYN practice, compared consultations before and after introduction of a SDM package. The target sample size was 25 patients per group. Women seeking treatment for heavy menstrual bleeding were eligible. After their appointments, patients filled out a three-item patient-reported SDM measure. Treatment discussions were audio-recorded and rated for SDM using Observer OPTION 5. Consultation transcripts in the ‘after’ group were checked for adherence to the steps required for intended use of decision aids. Results: 16 gynaecologists participated. 25 patients participated before introduction of the decision aids and 28 after. The proportion of women reporting optimal SDM was higher after introduction (75 %) than before (50 %;p < 0.001). The mean observer-rated level of SDM was also significantly higher after than before (MD = 12.50,95 % CI 5.53–19.47). Conclusion: The level of SDM was higher after the introduction of the package than before. Practice implications: This study was conducted in a real-life setting in three clinics, both large academic and small rural, offering opportunities for implementation in different type of organizations.

Background The prevalence of SARS-CoV-2 infection among health care workers (HCWs) provides information about the spread of COVID-19 within health care facilities, and the risk groups. Objectives We aimed to describe the rate of SARS-CoV-2 seroprevalence and its determinants among HCWs. Data sources We used Web of Science, PubMed, Scopus, MEDLINE, EBSCOhost and Cochrane Library. Study eligibility criteria We included the reports of SARS-CoV-2 seroprevalence with a sample size of minimum 1000 HCWs. Methods The study was registered at the International Prospective Register of Systematic Reviews (PROSPERO, no. CRD42021230456). We used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. The keywords were “COVID-19”, “SARS-CoV-2”, “Coronavirus”, “seroprevalence”, “health care workers” and “risk factors”. Results In total 4329 reports were retrieved, duplications were removed; after filtering according to the title and abstract, 25 studies were selected. Risk of bias was assessed in 25 studies; it was low in 13 studies, medium in four studies, and high in eight studies. In meta-analysis using the random effect model, the weighted average of seroprevalence was calculated as 8% (95% CI 6–10%). The pooled seroprevalence rates of the selected variables that have a rate above the average were male HCWs with 9% (95% CI 7–11%); HCWs from ethnic minorities with 13% (95% CI 9–17%); high exposure 9% (95% CI 6–13%); exposure to the virus outside the health care setting 22% (95% CI 14–32%). Conclusions Our analysis indicates a SARS-CoV-2 seroprevalence rate of 8% among studies that included >1000 HCWs for the year 2020, before vaccinations started. The most common risk factors associated with higher seroprevalence rate were ethnicity, male gender and having a higher number of household contacts. Working as a frontline HCW was inconsistent in its association with higher seroprevalence.

BackgroundWhite matter hyperintensities (WMHs) are a highly prevalent MRI marker of cerebral small vessel disease (SVD), which predict stroke and dementia risk, and are being increasingly used as a surrogate marker in clinical trials. However, the influence of study population selection on WMH progression rate has not been studied and the effect of individual patient factors for WMH growth are not fully understood.MethodsWe performed a systematic review and meta-analysis of the literature on progression of WMHs in longitudinal studies to determine rates of WMH growth, and how these varied according to population characteristics and cardiovascular risk factors. We used these data to calculate necessary sample sizes for clinical trials using WMH as an endpoint.ResultsWMH growth rate was highest in SVD (2.50cc/year), intermediate in unselected stroke patients (1.29cc/year) and lower in patients with non-stroke cardiovascular disease, and with cognitive impairment. Age was significantly associated with progression (correlation coefficient 0.15cc/year, 95% CI 0.02 to 0.28cc/year) as was baseline lesion volume (0.6cc/year, 95% CI 0.13 to 1.06 cc/year). Both hypertension (OR 1.72, 95% CI 1.19 to 2.46) and current smoking (OR 1.48, 95% CI 1.02 to 2.16) were associated with WMH growth. Sample sizes for a clinical trial varied greatly with patient population selection and baseline lesion volume; estimates are provided.ConclusionsWMH progression varies markedly according to the characteristics of the population being studied and this will have a major impact on sample sizes required in a clinical trial. Our sample size estimates provide data for planning clinical trials using WMH as an outcome measure.PROSPERO registration numberCRD42020191781.

Objective To review the effect of the Expanded Food and Nutrition Education Program (EFNEP) in changing nutrition-related outcomes. Methods Relevant research conducted before December 2020 was identified using PubMed, Web of Science, Google Scholar, and the EFNEP Research Database. The methodological quality of each eligible study was assessed. Results Of the 406 studies found, 30 were eligible; 26 studies were on EFNEP, and 4 included both EFNEP and Supplemental Nutrition Assistance Program Nutrition Education (SNAP-Ed). The sample sizes ranged from 35 to 122,961. Outcome measures included consumption of food groups, nutrients, other nutrition-related behaviors, and food security. At least 1 immediate behavior change (P Discussion This review found a consistent, immediate improvement in nutrition behaviors after program participation but poor retention over time. Overall, variation in programming and outcome measures, incomplete reporting, and generally low study quality by modern standards precluded strong conclusions. Implications for Research and Practice This review identified the need for control groups, improved reporting of program protocols, theory-based curriculum, and measurement of long-term outcomes.

Objective The likelihood ratio is a method for assessing evidence regarding two simple statistical hypotheses. Its interpretation is simple – for example, a value of 10 means that the first hypothesis is 10 times as strongly supported by the data as the second. A method is shown for deriving likelihood ratios from published trial reports. Study design The likelihood ratio compares two hypotheses in light of data: that a new treatment is effective, at a specified level (alternate hypothesis: for instance, the hazard ratio equals 0.7), and that it is not (null hypothesis: the hazard ratio equals 1). The result of the trial is summarised by the test statistic z (ie, the estimated treatment effect divided by its standard error). The expected value of z is 0 under the null hypothesis, and A under the alternate hypothesis. The logarithm of the likelihood ratio is given by z·A – A2/2. The values of A and z can be derived from the alternate hypothesis used for sample size computation, and from the observed treatment effect and its standard error or confidence interval. Results Examples are given of trials that yielded strong or moderate evidence in favor of the alternate hypothesis, and of a trial that favored the null hypothesis. The resulting likelihood ratios are applied to initial beliefs about the hypotheses to obtain posterior beliefs. Conclusions The likelihood ratio is a simple and easily understandable method for assessing evidence in data about two competing a priori hypotheses.

Rationale and Objectives Contrast-enhanced ultrasound (CEUS) has increasingly gained acceptance in the postoperative evaluation of kidney-transplantation recipients. Our meta-analysis aims to evaluate the diagnostic accuracy of CEUS in identifying post-transplantation complications. Materials and Methods PubMed, Scopus, Ovid Medline, and Cochrane databases were searched from their inception until February 28, 2020, for diagnostic test accuracy studies comparing CEUS to a reference standard for monitoring complications after kidney transplantation. A meta-analysis was conducted to calculate the pooled sensitivity, specificity, accuracy, and diagnostic odds ratio using a bivariate random effects model. Sensitivity analysis was performed using R software by stratifying the studies based on study design, sample size, age, and origin of the study to evaluate the influence of these factors on the overall effect. Results Two independent reviewers analyzed 285 publications, out of which 29 were determined directly relevant and 12 (with a total of 542 cases) contained all required data for the meta-analysis. The overall sensitivity of included studies was estimated to be 0.86 (95% confidential interval (CI); 0.78-–0.92). Similarly, the overall specificity was estimated to be 0.90 (95% CI; 0.82–0.94). Log diagnostic odds ratio was 4.25 (95% CI; 3.43–5.07), and the area under the curve of the pooled receiver operating characteristic was 0.94. Stratified sensitivity analyses showed study design, sample size, age group, and origin of the study had no significant impact on the overall diagnostic value of CEUS. Conclusion Evidence suggests that CEUS is a potentially effective and accurate method to evaluate a variety of complications such as rejection, vascular complications, and malignancies after kidney transplantation.

Background The P value is a statistical tool used to assess the statistical significance of clinical trial outcomes in orthopedic surgery. However, the P value does not evaluate research quality or clinical significance. The Fragility Index (FI) is an alternative statistical method that can be used to assess the quality and significance of clinical research and is defined as the number of patients in a study intervention group necessary to convert an outcome from statistically significant to statistically insignificant or vice versa. The primary purpose of this study was to evaluate the statistical robustness of clinical trials regarding shoulder arthroplasty using the FI. The secondary goal was to identify trial characteristics associated greater statistical fragility. Methods A systematic review of randomized clinical trials in shoulder arthroplasty was performed. The FI was calculated for all dichotomous, categorical study outcomes discussed in the identified studies. Descriptive statistics and the Pearson correlation coefficient were used to evaluate all studies and characterize associations between study variables. Results A total of 13 randomized controlled trials were identified and evaluated; these trials had a median sample size of 47 patients (mean, 54 patients; range, 26-102 patients) and a median of 7 patients (mean, 5.8 patients; range, 0-14 patients) lost to follow-up. The median FI was 6 (mean, 5; range, 1-11), a higher FI than what has been observed in other orthopedic subspecialties. However, the majority of outcomes (74.4%) had an FI that was less than the number of patients lost to follow-up, and most outcomes (89.7%) were statistically insignificant. Conclusion Randomized controlled trials in shoulder arthroplasty have comparable statistical robustness to the literature in other orthopedic surgical subspecialties. We believe that the inclusion of the FI in future comparative studies in the shoulder arthroplasty literature will allow surgeons to better assess the statistical robustness of future research.

BACKGROUND Measurement of mother-to-child HIV transmission through population-based surveys requires large sample sizes because of low HIV prevalence among children. We estimate potential improvements in sampling efficiency resulting from a targeted sample design. SETTING Eight countries in sub-Saharan Africa with completed Population-based HIV Impact Assessment (PHIA) surveys as of 2017. METHODS The PHIA surveys used a geographically stratified 2-stage sample design with households sampled from randomly selected census enumeration areas. Children (0-14 years of age) were eligible for HIV testing within a random subsample of households (usually 50%). Estimates of child HIV prevalence in each country were calculated using jackknife replicate weights. We compared sample sizes and precision achieved using this design with a 2-phase disproportionate sample design applied to strata defined by maternal HIV status and mortality. RESULTS HIV prevalence among children ranged from 0.4% (95% confidence interval: 0.2 to 0.6) in Tanzania to 2.8% (95% confidence interval: 2.2 to 3.4) in Eswatini with achieved relative standard errors between 11% and 21%. The expected precision improved in the targeted design in all countries included in the analysis, with proportionate reductions in mean squared error ranging from 27% in Eswatini to 61% in Tanzania, assuming an equal sample size. CONCLUSIONS Population-based surveys of adult HIV prevalence that also measure child HIV prevalence should consider targeted sampling of children to reduce required sample size, increase precision, and increase the number of positive children tested. The findings from the PHIA surveys can be used as baseline data for informing future sample designs.

Introduction To assess the value of referring to Diffusion-weighted images in evaluation of T2-weighted images of patients clinically suspicious of locoregional rectal cancer recurrence. Methods After ethics committee approval and informed consent were obtained, 37 consecutive patients (male/female of 22/15; mean age 56 ± 13.5 SD) clinically suspicious of recurrent rectal tumor were prospectively included in the study over a two-year period. T2-weighted images of the patients were reviewed and the results were recorded. Right after that, the corresponding DWI images were provided for the radiologist and new ratings were given to the patients after taking into account the DWI findings. Finally, the patients underwent tissue biopsy. Receiver Operating Characteristic (ROC) analysis was performed, and Area Under the Curve (AUC) of the “T2-weighted alone” and “T2-weighted + DWI” methods were calculated and compared. Results “T2-weighted alone” and “T2-weighted + DWI” methods had an AUC of 0.64 (95% CI 0.47 to 0.79) and 0.75 (95% CI 0.58 to 0.88), respectively. The Difference between the two AUCs was 0.11 (P = 0.16). In the subgroup of patients having equivocal ratings in T2-weighted images, DWI images correctly identified 81% (13/16) of patients with true tumor recurrence and 66% (8/12) of patients without recurrence. Conclusion Our results suggest that referring to DWI does not significantly change the overall diagnostic performance of T2-weighted images. However, DWI is of great value in evaluation of the subgroup of patients with equivocal findings in T2-weighted images. Studies with larger sample sizes are needed to confirm these findings. Implications for practice When T2-weighted images are equivocal, DWI images may be helpful in evaluation of patients with suspected locoregional recurrence of rectal tumor.

Objective Clinicians’ overdependence on p-values to determine significance in clinical trials is common yet potentially misleading. The Fragility Index (FI) describes how robust a significant result is by determining the number of events the statistical significance hinges on. However, this concept cannot be applied to nondichotomous variables. We describe a method to calculate a Continuous Fragility Index (CFI) for continuous variables. We further provide a method to estimate CFI when original data is not available. Study Design and Setting An iterative substitution algorithm is described to calculate CFI prospectively from data or retrospectively from summary statistics and its response to variations in the data is reported. We then apply this method to a previously published review as a proof-of-concept. Results The CFI increases linearly with sample size, logarithmically with mean difference, and decreases exponentially with standard deviation. Forty-eight studies were included of which 30 had significant non-dichotomous outcomes. CFI and FI were uncorrelated and mean CFI was significantly higher than FI (9 vs. 2, P Conclusion Our algorithm extends fragility to continuous outcomes, expanding the applications of the fragility concept. The fragility of outcomes within a single study may vary based on variable type and should be evaluated independently.

Background Current thyroid hormone replacement therapy (THRT) is built on weight-based standard calculation of dose. A novel Poisson regression model, which accounts for seven clinical variables, was recently proposed to improve accuracy of THRT. We aimed to compare the accuracy of estimated THRT dose to reach euthyroid and the difference in predicted dose between the Poisson (scheme A) and the weight-based standard (scheme B) in patients following total thyroidectomy for benign disease. Methods We retrospectively reviewed medical record of patients who underwent total or completion thyroidectomy for benign disease at a single institution between 2011 and 2019. The THRT dose was calculated using both schemes. We compared the difference between calculated THRT and prediction rates for optimal THRT dosing needed to achieve a euthyroid state between dosing schemes. Patients were evaluated for achieving euthyroid state, defined as TSH 0.45-4.5 mIU/L. We also compared dosing error rates (> 25 mcg over- and underdosing) between schemes. Prediction rates were compared by BMI tertiles to account for the effect of BMI extremes in achieving euthyroid state. The difference in predicted dose between schemes was calculated in both the total sample size and patients that met euthyroid. A measure of agreement, Kappa, was used to estimate agreement between dosing schemes. Results A total of 406 patients underwent total thyroidectomy for benign disease, with 184 having sufficient follow up data confirming euthyroid state. Of the 184 patients, 85.9% (n = 158) were women, 81% (n = 149) were Hispanic, and 56.5% (n = 104) were obese with a median BMI of 30.8 kg/m2. Scheme A resulted in a higher, but not statistically significant, accuracy rate (A: 60.3%, n = 111 versus B: 53.8%, n = 99; P = 0.21). Overdosing errors were lower with Scheme A (A:17.9% versus B: 32.1%; P = 0.0025) and less extreme > 25 µg (A: 17.9% versus B: 26.1%; P = 0.08). A trend in improved accuracy in patients with a BMI > 35 kg/m2 was noted (A: 46.9% versus B: 34.4%; P = 0.20). Scheme A also resulted in less overdosing errors in obese patients compared to Scheme B (A: 19.2% versus 45.2%; P = 0.0006). The average difference in predicted dose between schemes was an entire dose difference, mean of 16.0 µg and 15.8 µg for the total and euthyroid samples respectively. Furthermore, for the majority of patients the predicted dose did not match between the two dosing schemes for total and euthyroid samples, 76% (n = 311) and 76% (n = 141) respectively. In patients that achieved euthyroid, agreement between dosing schemes was low to moderate (Kappa = 0.360). Conclusions Lower rates of overdosing were found for scheme A, particularly with obese patients. No statistically significant differences in predicted THRT dose was observed between schemes. The difference in predicted dose between schemes was on average 15 ug, correlating with an entire dose. The consideration of clinical variables other than weight (scheme A) when determining optimal THRT dosing may be of importance to prevent overdoses, with particular clinical relevance in patients with higher BMIs.

Background: With medical information widely available, patients often have preconceived ideas regarding diagnostic procedures and management strategies. Objectives: To investigate whether expectations, such as beliefs about the source of symptoms and knowledge about diagnostic tests, influence pain perception during a clinical diagnostic test. Design: Cross-sectional study. Methods: Pain was induced by intramuscular hypertonic saline infusion in the thenar muscles. In line with sample size calculations, fifteen participants were included. All participants received identical background information regarding basic median nerve biomechanics and basic concepts of differential diagnosis via mechanical loading of painful structures. Based on different explanations about the origin of their induced pain, half of the participants believed (correctly) they had ‘muscle pain’ and half believed (incorrectly) they had ‘nerve pain’. Pain intensity and size of the painful area were evaluated in five different positions of the median nerve neurodynamic test (ULNT1 MEDIAN). Data were analysed with two-way analyses of variance. Results: /findings: Changes in pain in the ULNT1 MEDIAN positions were different between the ‘muscle pain’ and ‘nerve pain’ group (p < 0.001). In line with their expectations, the ‘muscle pain’ group demonstrated no changes in pain throughout the test (p > 0.38). In contrast, pain intensity (p ≤ 0.003) and size of the painful area (p ≤ 0.03) increased and decreased in the ‘nerve pain’ group consistent with their expectations and the level of mechanical nerve loading. Conclusion: Pain perception during a clinical diagnostic test may be substantially influenced by pain anticipation. Moreover, pain was more aligned with beliefs and expectations than with the actual pathobiological process.

Microbiomes not only exist across many different body sites in human beings but also interact dynamically with the host and environment. The unique feature and complexity of 16S ribosomal RNA gene sequence data, especially the sparsity of the data, present challenges to statistical analysis and interpretation. Proper normalization is critical in ensuring the validity of downstream analysis. Modeling the inflated zeros is an active area of research, and it has been extended from differential abundance analysis to a variety of other types of analyses. One specific method may not work well under all conditions, where sample size, effect size, data distribution, and degree of zero inflation vary greatly.

STUDY QUESTION What are the differences in ease of use between two different embryo transfer (ET) techniques: the preload direct approach and the afterload approach. SUMMARY ANSWER The afterload technique seems to reduce the rate of difficult ETs. WHAT IS KNOWN ALREADY Numerous published trials now document that the ET procedure has an impact on pregnancy and delivery rates after IVF. Difficult transfers should be avoided, as they reduce implantation and pregnancy rates. Preload direct ETs with soft catheters under ultrasound guidance is currently considered the best procedure. However, when using soft catheters, it is not known which technique is preferable or which one should be implemented to reduce the operator factor. STUDY DESIGN, SIZE, DURATION This prospective randomised unblinded controlled clinical trial, included 352 ultrasound-guided ETs assigned to either direct ET or afterload ET, between September 2017 and March 2019. The sample size was calculated based on the historical rate of difficult ETs encountered between 2014 and 2015 with a direct ET procedure. PARTICIPANTS/MATERIALS, SETTING, METHODS The inclusion criteria were women 18–38 years old, with BMI between 18 and 28, receiving a single-thawed blastocyst transfer. The exclusion criteria were use of testicular sperm and preimplantation genetic testing (PGT) cycles. The primary outcome was the rate of difficult or suboptimal transfers defined as: advancement of the outer sheath (specific for the direct transfer), multiple attempts, use of force, required manipulation, use of a stylet or tenaculum, dilatation, or use of a different catheter. The secondary outcome was clinical pregnancy rate. MAIN RESULTS AND THE ROLE OF CHANCE A total of 352 frozen ETs were randomised, with 176 patients in each group. The two arms were homogeneous for female and male age, female BMI, duration of infertility, secondary infertility, previous deliveries or miscarriages, myomas, previous surgery to the uterine cavity, cycle day at ovulation trigger, freeze all cycles, first transfers, indication for treatment, endometrial preparation protocol and duration, endometrial thickness, and blastocyst grade at vitrification. Across the entire population, 85 (24.1%) ETs were defined as difficult. The rate of difficult transfers was significantly higher in the direct ET group than in the afterload group: 68 (38.6%) versus 17 (9.7%), respectively (OR 0.17, 95% CI 0.09–0.30, P LIMITATIONS, REASONS FOR CAUTION There were 18 experienced operators who participated in the trial. Conclusions about the pregnancy rate should not be generalised, since the sample analysis was not performed on this outcome and, although clinically relevant, the difference was not significantly different. WIDER IMPLICATIONS OF THE FINDINGS The rate of difficult transfers was significantly higher in the direct ET group compared with the afterload ET group, although a wide variation was observed among operators. Further studies regarding the association between transfer technique and ART outcomes are required. STUDY FUNDING/COMPETING INTEREST(S) No specific funding was sought and there are no competing interests. TRIAL REGISTRATION NUMBER NCT03161119. TRIAL REGISTRATION DATE 5 April 2017. DATE OF FIRST PATIENT'S ENROLMENT 26 September 2017.

BackgroundThis study was conducted to systematically review the existing literature examining the prevalence of anxiety among hospital staff and identifying the contributing factors to address the complications of this disorder and develop effective programmes for reducing the complications of this mental health problem.MethodsWe searched the electronic databases including PubMed, EMBASE, Scopus, Web of Science and Google Scholar from January 2020 to February 2021. To perform meta-analysis, the random effects model was used. To assess the statistical heterogeneity of the included studies, the I2index was used, and 95% CI was estimated. Data analysis was performed by R software.ResultsIn the final analysis, 46 articles with the total sample size of 61 551 hospital staff members were included. Accordingly, anxiety prevalence among healthcare workers (HCWs) was 26.1% (95% CI 19% to 34.6%). The prevalence rates of anxiety in health technicians and medical students were 39% (95% CI 13% to 73%) and 36% (95% CI 15% to 65%), respectively, indicating a much higher prevalence than other hospital staff members. Furthermore, a positive significant relationship between prevalence of anxiety among HCWs and their age was approved (pConclusionThe findings show a moderately high prevalence rate of anxiety in hospital staff. Due to the high prevalence of this mental health problem in health technicians, medical students and frontline health workers, it is highly suggested that healthcare institutions offer mental health programmes for these working groups in order to appropriately manage anxiety during the COVID-19 pandemic.

Summary Multiregional clinical trials (MRCTs) provide the benefit of more rapidly introducing drugs to the global market; however, small regional sample sizes can lead to poor estimation quality of region-specific effects when using current statistical methods. With the publication of the International Conference for Harmonisation E17 guideline in 2017, the MRCT design is recognized as a viable strategy that can be accepted by regional regulatory authorities, necessitating new statistical methods that improve the quality of region-specific inference. In this article, we develop a novel methodology for estimating region-specific and global treatment effects for MRCTs using Bayesian model averaging. This approach can be used for trials that compare two treatment groups with respect to a continuous outcome, and it allows for the incorporation of patient characteristics through the inclusion of covariates. We propose an approach that uses posterior model probabilities to quantify evidence in favor of consistency of treatment effects across all regions, and this metric can be used by regulatory authorities for drug approval. We show through simulations that the proposed modeling approach results in lower MSE than a fixed-effects linear regression model and better control of type I error rates than a Bayesian hierarchical model.

Background The purpose of the meta-analysis is to evaluate the accuracy of extracellular vesicles (EV) miRNAs in the diagnosis of Non-small cell lung cancer (NSCLC). Methods All eligible studies were searched electronically online database. STATA15.0, Meta-disc14.0 and Review Manager 5.2 software were used to perform all statistical analysis. Results The analysis included 16 articles searched electronically online database and a total of 70 studies. Pooled sensitivity (SE) and specificity (SP), positive predictive value (PPV) and negative predictive value (NPV) were 0.77 (95% CI: 0.72-0.80), 0.83(95% CI: 0.78-0.86), 0.88 (95% CI: 0.86-0.90) and 0.63 (95% CI: 0.58-0.68), respectively. The overall diagnostic odds ratio (DOR) were 16(95% CI: 11-21) and the area under the curve (AUC) was 0.86 (95% CI: 0.83-0.89). Threshold analysis showed there was no threshold effect (P=0.11). Meta-regression suggested specimen, publication year and sample size might be the major source of heterogeneity. Subgroup analysis hinted that combined test had better diagnostic accuracy for NSCLC than alone. Conclusion Circulating EV miRNAs are significantly associated with NSCLC diagnosis, especially metastatic NSCLC, followed by early NSCLC, whose AUC values were 0.90 and 0.88, respectively. 3 of EV miRNAs might act as biomarkers for metastatic NSCLC diagnosis, and 10 for early stage of NSCLC. EV miR-21, miR-210, and miR-1290 might be associated with PK13/AKT related pathway and be the valuable diagnostic biomarkers for NSCLC. Besides, multitudinous EV miRNAs combined to diagnose NSCLC show a higher diagnostic value than alone.

Objectives: Understanding the efficacy of indicated homoeopathic medicine as an adjuvant to standard treatment in improving the subjective and objective parameters in patients with mild to moderate confirmed cases of COVID-19. Materials and Methods: Study design: A prospective randomized control trial conducted at Deenanath Mangeshkar Hospital, Erandwane, Pune, wherein Group A received standard treatment along with indicated homoeopathic medicine (experimental group) and Group B received the standard treatment and placebo (control group). Sample size: Fifty confirmed COVID positive, randomly selected patients in Groups A and B. Results: The indicated homoeopathic medicine as an adjuvant reduced subjective distress in a statistically significant proportion. It also reduced oxygen requirement, shortened hospital stay, promoted early recovery, and reduced worsening of the patients and shifting into the intensive care unit (ICU). By day 4 of treatment, subjective symptoms in 56% of patients in the experimental group were completely resolved, compared to 15% in the control group. The oxygen requirement on day 4 reduced by 46.2% in the experimental group, remaining unchanged in the control group. None of the patients in the experimental group needed shifting to the ICU compared to 16.7% in the control group. The average hospital stay was 6 days in the experimental group, compared to 9 days in the control group. Conclusion: Homoeopathic medicines played a significant role in helping to relieve the subjective and objective parameters of COVID-19.

Randomised assignment of individuals to treatment and controls groups is often considered the gold standard to draw valid conclusions about the efficacy of an intervention. In practice, randomisation can lead to accidental differences due to chance. Researchers have offered alternatives to reduce such differences, but these methods are not used frequently due to the requirement of advanced statistical methods. Here, we recommend a simple assignment procedure based on variance minimisation (VM), which assigns incoming participants automatically to the condition that minimises differences between groups in relevant measures. As an example of its application in the research context, we simulated an intervention study whereby a researcher used the VM procedure on a covariate to assign participants to a control and intervention group rather than controlling for the covariate at the analysis stage. Among other features of the simulated study, such as effect size and sample size, we manipulated the correlation between the matching covariate and the outcome variable and the presence of imbalance between groups in the covariate. Our results highlighted the advantages of VM over prevalent random assignment procedure in terms of reducing the Type I error rate and providing accurate estimates of the effect of the group on the outcome variable. The VM procedure is valuable in situations whereby the intervention to an individual begins before the recruitment of the entire sample size is completed. We provide an Excel spreadsheet, as well as scripts in R, MATLAB, and Python to ease and foster the implementation of the VM procedure. Supplementary Information The online version contains supplementary material available at 10.3758/s13423-021-01970-5.

By combining data across multiple studies, researchers increase sample size, statistical power, and precision for pooled analyses of biomarker–disease associations. However, researchers must adjust for between-study variability in biomarker measurements. Previous research often treats the biomarker measurements from a reference laboratory as a gold standard, even though those measurements are certainly not equal to their true values. This paper addresses measurement error and bias arising from both the reference and study-specific laboratories. We develop two calibration methods, the exact calibration method and approximate calibration method, for pooling biomarker data drawn from nested or matched case–control studies, where the calibration subset is obtained by randomly selecting controls from each contributing study. Simulation studies are conducted to evaluate the empirical performance of the proposed methods. We apply the proposed methods to a pooling project of nested case–control studies to evaluate the association between circulating 25-hydroxyvitamin D (25(OH)D) and colorectal cancer risk.

Objective The aim of this study was to compare the prevalence of dental caries among groups of 6–12-year-old children with and without Type 1 diabetes mellitus (T1DM) in Riyadh, Saudi Arabia, taking into account oral health behaviour, diet, and salivary parameters. Methods The study was designed as a comparable study of dental caries experience between T1DM and non-diabetic groups of children. The total sample size of 209 participants consisted of 69 diabetic and 140 non-diabetic children. Oral hygiene, diet and socio-economic status were collected using a pre-tested questionnaire. Caries was recorded in terms of decayed and filled permanent and primary teeth (DFT/dft). Salivary microbial counts and pH levels were recorded using Caries Risk Test (CRT) kit. Student's t-test, the chi-squared test, linear regression and one-way analysis of variance were performed P-value of 0.05 considered significant. Results The mean dft scores for the diabetic and non-diabetic groups were 3.32 ± 0.78 and 3.28 ± 0.71 (mean ± SD), respectively (p = 0.458). The mean DFT scores for the diabetic and non-diabetic groups were 1.62 ± 0.65 and 1.96 ± 0.65, respectively (p = 0.681). Diabetic children visited dentists more often than non-diabetic children did (p = 0.04), and had lower consumption of both sweets (p = 0.003) and flavoured milk (p = 0.002) than the non-diabetic group. Furthermore, analysis showed that the diabetic children had medium oral pH levels (pH = 4.5–5.5), whereas the non-diabetic children tended to have high (pH ≥ 6.0) oral pH; this difference was statistically significant (p = 0.01). In addition, the diabetic group had higher Lactobacillus levels than the non-diabetic group (p = 0.04). Conclusion The difference in caries prevalence between the diabetic and non-diabetic children was not statistically significant. The CRT analysis revealed a higher frequency of “critical” pH values (pH = 4.5–5.5) and higher Lactobacillus counts in diabetic children than in non-diabetic children, which indicated a higher caries risk in the former group.

Heterozygosity is a metric of genetic variability frequently used to inform the management of threatened taxa. Estimating observed and expected heterozygosities from genome-wide sequence data has become increasingly common, and these estimates are often derived directly from genotypes at single nucleotide polymorphism (SNP) markers. While many SNP markers can provide precise estimates of genetic processes, the results of ‘downstream’ analysis with these markers may depend heavily on ‘upstream’ filtering decisions. Here we explore the downstream consequences of sample size, rare allele filtering, missing data thresholds and known population structure on estimates of observed and expected heterozygosity using two reduced-representation sequencing datasets, one from the mosquito Aedes aegypti (ddRADseq) and the other from a threatened grasshopper, Keyacris scurra (DArTseq). We show that estimates based on polymorphic markers only (i.e. SNP heterozygosity) are always biased by global sample size (N), with smaller N producing larger estimates. By contrast, results are unbiased by sample size when calculations consider monomorphic as well as polymorphic sequence information (i.e. genome-wide or autosomal heterozygosity). SNP heterozygosity is also biased when differentiated populations are analysed together while autosomal heterozygosity remains unbiased. We also show that when nucleotide sites with missing genotypes are included, observed and expected heterozygosity estimates diverge in proportion to the amount of missing data permitted at each site. We make three recommendations for estimating genome-wide heterozygosity: (a) autosomal heterozygosity should be reported instead of (or in addition to) SNP heterozygosity; (b) sites with any missing data should be omitted and (c) populations should be analysed in independent runs. This should facilitate comparisons within and across studies and between observed and expected measures of heterozygosity.