Implementing pathogen reduction technology while discontinuing blood donor deferral criteria for sexual risk behaviors: A simulation study.

BACKGROUND: Combining pathogen reduction technology (PRT) with blood screening may alleviate concerns over the risk of transfusion-transmitted infections (TTI) and support changes in blood donor selection to potentially increase blood availability. This study aimed to estimate the residual risk of human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) transfusion-transmission in Canada after implementing PRT, while eliminating deferrals for sexual risk behaviors. STUDY DESIGN AND METHODS: A probabilistic approach that combined Bayesian networks with Monte Carlo simulations was used to estimate the risk of transfusing HIV-, HBV-, or HCV-contaminated blood components. Different scenarios were considered to compare the current residual risk after PRT implementation, with and without donor deferral criteria for sexual risk behaviors. Donor profiles and blood component outcomes were simulated based on a literature review including the prevalence and incidence of HIV, HBV, and HCV in the Canadian blood donor population; the use of current blood screening assays; and HIV, HBV, and HCV blood donor viral loads. RESULTS: In the universal PRT scenario (i.e., with PRT/without deferral criteria), the estimated risks of HIV, HBV, and HCV transmission were significantly lower than those in the currently observed scenario (i.e., without PRT/with deferral criteria). CONCLUSIONS: This risk model suggests that PRT for platelets and plasma (and eventually for RBCs when available) significantly reduces the residual risks of HIV, HBV and HCV transfusion-transmission and could enable the removal of blood donor deferral criteria for sexual risk behaviors.

The response of Canada's clinical health research ecosystem to the COVID-19 pandemic.

BACKGROUND: The response of Canada's research community to the COVID-19 pandemic provides a unique opportunity to examine the country's clinical health research ecosystem. We sought to describe patterns of enrolment across Canadian Institutes of Health Research (CIHR)-funded studies on COVID-19. METHODS: We identified COVID-19 studies funded by the CIHR and that enrolled participants from Canadian acute care hospitals between January 2020 and April 2023. We collected information on study-and site-level variables from study leads, site investigators, and public domain sources. We described and evaluated factors associated with cumulative enrolment. RESULTS: We obtained information for 23 out of 26 (88%) eligible CIHR-funded studies (16 randomized controlled trials [RCTs] and 7 cohort studies). The 23 studies were managed by 12 Canadian and 3 international coordinating centres. Of 419 Canadian hospitals, 97 (23%) enrolled a total of 28 973 participants - 3876 in RCTs across 78 hospitals (median cumulative enrolment per hospital 30, interquartile range [IQR] 10-61), and 25 097 in cohort studies across 62 hospitals (median cumulative enrolment per hospital 158, IQR 6-348). Of 78 hospitals recruiting participants in RCTs, 13 (17%) enrolled 50% of all RCT participants, whereas 6 of 62 hospitals (9.7%) recruited 54% of participants in cohort studies. INTERPRETATION: A minority of Canadian hospitals enrolled the majority of participants in CIHR-funded studies on COVID-19. This analysis sheds light on the Canadian health research ecosystem and provides information for multiple key partners to consider ways to realize the full research potential of Canada's health systems.

Two-phase Bayesian latent class analysis to assess diagnostic test performance in the absence of a gold standard: COVID-19 serological assays as a proof of concept.

BACKGROUND AND OBJECTIVES: In this proof-of-concept study, which included blood donor samples, we aimed to demonstrate how Bayesian latent class models (BLCMs) could be used to estimate SARS-CoV-2 seroprevalence in the absence of a gold standard assay under a two-phase sampling design. MATERIALS AND METHODS: To this end, 6810 plasma samples from blood donors who resided in Québec (Canada) were collected from May to July 2020 and tested for anti-SARS-CoV-2 antibodies using seven serological assays (five commercial and two non-commercial). RESULTS: SARS-CoV-2 seroprevalence was estimated at 0.71% (95% credible interval [CrI] = 0.53%-0.92%). The cPass assay had the lowest sensitivity estimate (88.7%; 95% CrI = 80.6%-94.7%), while the Héma-Québec assay had the highest (98.7%; 95% CrI = 97.0%-99.6%). CONCLUSION: The estimated low seroprevalence (which indicates a relatively limited spread of SARS-CoV-2 in Quebec) might change rapidly-and this tool, developed using blood donors, could enable a rapid update of the prevalence estimate in the absence of a gold standard. Further, the present analysis illustrates how a two-stage BLCM sampling design, along with blood donor samples, can be used to estimate the performance of new diagnostic tests and inform public health decisions regarding a new or emerging disease for which a perfect reference standard does not exist.

The Triple-Tracer strategy against Metastatic PrOstate cancer (3TMPO) study protocol.

OBJECTIVE: To determine the prevalence of intra-patient inter-metastatic heterogeneity based on positron emission tomography (PET)/computed tomography (CT) in patients with metastatic castration-resistant prostate cancer (mCRPC) and to determine the prevalence of neuroendocrine disease in these patients and their eligibility for radioligand therapies (RLTs). PATIENTS AND METHODS: This multicentre observational prospective clinical study will include 100 patients with mCRPC from five Canadian academic centres. Patients with radiological or biochemical progression and harbouring at least three metastases by conventional imaging will be accrued. Intra-patient inter-metastatic heterogeneity will be determined with triple-tracer imaging using fluorine-18 fluorodeoxyglucose (18 F-FDG), gallium-68-(68 Ga)-prostate-specific membrane antigen (PSMA)-617 and 68 Ga-DOTATATE, which are a glucose analogue, a PSMA receptor ligand and a somatostatin receptor ligand, respectively. The 68 Ga-PSMA-617 and 18 F-FDG PET/CT scans will be performed first. If at least one PSMA-negative/FDG-positive lesion is observed, an additional PET/CT scan with 68 Ga-DOTATATE will be performed. The tracer uptake of individual lesions will be assessed for each PET tracer and patients with lesions presenting discordant uptake profiles will be considered as having inter-metastatic heterogeneous disease and may be offered a biopsy. EXPECTED RESULTS: The proposed triple-tracer approach will allow whole-body mCRPC characterisation, investigating the inter-metastatic heterogeneity in order to better understand the phenotypic plasticity of prostate cancer, including the neuroendocrine transdifferentiation that occurs during mCRPC progression. Based on 68 Ga-PSMA-617 or 68 Ga-DOTATATE PET positivity, the potential eligibility of patients for PSMA and DOTATATE-based RLT will be assessed. Non-invasive whole-body determination of mCRPC heterogeneity and transdifferentiation is highly innovative and might establish the basis for new therapeutic strategies. Comparison of molecular imaging findings with biopsies will also link metastasis biology to radiomic features. CONCLUSION: This study will add novel, biologically relevant dimensions to molecular imaging: the non-invasive detection of inter-metastatic heterogeneity and transdifferentiation to neuroendocrine prostate cancer by using a multi-tracer PET/CT strategy to further personalise the care of patients with mCRPC.

Risk of transfusion-related acute lung injury and human immunodeficiency virus associated with donations from trans donors in Quebec, Canada.

BACKGROUND AND OBJECTIVES: Blood operator must establish selection criteria according to the populations at risk of blood-related infections and complications. Therefore, this study aimed to assess the risks of transfusion-related acute lung injury (TRALI) and human immunodeficiency virus (HIV) associated with donations from trans persons. MATERIALS AND METHODS: Donor screening data from Héma-Québec were used. The risks of TRALI and HIV were estimated based on internal data and assumptions derived from the literature. The risk was assessed under four scenarios: a most likely scenario, an optimistic scenario and two pessimistic scenarios. All scenarios assumed no prior screening for trans donors. RESULTS: The trans population comprised 134 donors, including 94 (70.1%) trans men. Of the 134 donors, 58 (43.3%) were deferred from donating a blood-derived product because of an ongoing gender-affirming genital surgery, and the remaining 76 (56.7%) were eligible donors. The risk of having a TRALI-causing donation, given that it comes from a trans man, was estimated at one every 115-999 years for all scenarios. The risk of having an HIV-contaminated donation, given that it comes from a trans woman, was estimated at one every 1881-37,600 years for all scenarios. CONCLUSION: This study suggests that donations from trans persons are associated with a negligible risk of TRALI and HIV.

HIV residual risk in Canada for apheresis source plasma donation without deferral for men who have sex with men.

BACKGROUND AND OBJECTIVES: In Canada, men having sex with men (MSM) are deferred for 3 months from last sexual contact to reduce human immunodeficiency virus (HIV) risk to recipients. The aim of this paper was to model the Canadian residual risk of HIV-positive source plasma incorporating pathogen inactivation (PI) under no MSM deferral scenarios for apheresis plasma donations. MATERIALS AND METHODS: A combined Bayesian network (BN) and Monte Carlo approach were implemented to estimate the HIV residual risk under 3-month deferral compared with no deferral without quarantine scenarios for MSM donors. Models involve the stochastic generation of donation and its infection status based on its corresponding simulated donor profile. Viral load reduction conferred by PI used by source plasma fractionators was simulated. Model parameters were derived from Héma-Québec and Canadian Blood Services data, viral loads in a large sample of HIV-positive US blood donors, CSL Behring documentation and from published data. RESULTS: In the most likely scenario for the 3-month deferral model, there were 2.71 positive donations per 1,000,000 donations (95% confidence interval [CI] 2.63-2.78). For the no-deferral model, there were 3.01 positive donations per 1,000,000 donations (95% CI 2.94-3.09). For both scenarios, the risk of having an infectious pool was 0 in 300,000 pools (95% CI 0-0.0000123) after consideration of PI. CONCLUSION: Based on simulation results, there would be a negligible HIV residual risk associated with the removal of a time-based MSM deferral without quarantine for source plasma incorporating PI.

Bayesian Evaluation of Solana HSV 1+2/VZV Assay Compared to Viral Culture and Commercial PCR Assay for Cutaneous or Mucocutaneous Specimens.

Results from the Solana HSV 1+2/VZV assay for the detection of herpes simplex virus 1 (HSV-1), HSV-2, and varicella-zoster virus (VZV) in cutaneous or mucocutaneous specimens were compared with that of viral culture and a commercial PCR assay (RealStar alpha herpesvirus PCR kit). Three hundred two mucocutaneous specimens, for which HSV-1, HSV-2, or VZV viral culture or PCR detection have been requested, were randomly selected and prospectively processed on the Solana assay and viral culture or the RealStar assay. Discordant results between culture and the Solana assay were further analyzed using the RealStar assay. A Bayesian latent class model was developed to estimate the performance of each method. Viral culture detected 123 positive specimens (85 HSV-1, 36 HSV-2, and 2 VZV), while the Solana assay detected 27 additional positive specimens (4 HSV-1, 11 HSV-2, and 12 VZV), in agreement with the RealStar PCR assay. The estimated sensitivity of the Solana assay according to our model was 92.7% to 98.7%, 87.1% to 97.8%, and 94.9% to 98.8% (95% confidence interval [CI]) for HSV-1 HSV-2, and VZV, respectively, while the estimated sensitivity of viral culture was 85.2% to 95.0%, 73.6% to 89.6%, and 30.9% to 45.8% (95% CI), respectively. A nonsignificant tendency toward increased sensitivity was noted for the Solana assay compared with culture for HSV-1 and HSV-2, and the Solana assay was significantly more sensitive than culture for the detection of VZV. The Solana assay performed comparably to the RealStar assay. Processing time was reduced with the Solana assay compared with viral culture.

Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Health Analytics.

BACKGROUND: Data from multiple organizations are crucial for advancing learning health systems. However, ethical, legal, and social concerns may restrict the use of standard statistical methods that rely on pooling data. Although distributed algorithms offer alternatives, they may not always be suitable for health frameworks. OBJECTIVE: This paper aims to support researchers and data custodians in three ways: (1) providing a concise overview of the literature on statistical inference methods for horizontally partitioned data; (2) describing the methods applicable to generalized linear models (GLM) and assessing their underlying distributional assumptions; (3) adapting existing methods to make them fully usable in health settings. METHODS: A scoping review methodology was employed for the literature mapping, from which methods presenting a methodological framework for GLM analyses with horizontally partitioned data were identified and assessed from the perspective of applicability in health settings. Statistical theory was used to adapt methods and to derive the properties of the resulting estimators. RESULTS: From the review, 41 articles were selected, and six approaches were extracted for conducting standard GLM-based statistical analysis. However, these approaches assumed evenly and identically distributed data across nodes. Consequently, statistical procedures were derived to accommodate uneven node sample sizes and heterogeneous data distributions across nodes. Workflows and detailed algorithms were developed to highlight information-sharing requirements and operational complexity. CONCLUSIONS: This paper contributes to the field of health analytics by providing an overview of the methods that can be used with horizontally partitioned data, by adapting these methods to the context of heterogeneous health data and by clarifying the workflows and quantities exchanged by the methods discussed. Further analysis of the confidentiality preserved by these methods is needed to fully understand the risk associated with the sharing of summary statistics.

GLP-1 response during pregnancy: variations between trimesters and associations with appetite sensations and usual energy intake.

Further research is required to understand hormonal regulation of food intake during pregnancy and its association with energy intake. The objectives are to (i) compare postprandial responses of plasma glucagon-like peptide-1 (GLP-1) between trimesters, (ii) compare postprandial appetite sensations between trimesters, and (iii) examine trimester-specific associations between GLP-1 levels, appetite sensations, and usual energy intake. At each trimester, participants (n = 26) consumed a standard test meal following a 12 h fast. Plasma GLP-1 levels were measured by enzyme-linked immunosorbent assay method at fasting and at 30, 60, 120, and 180 min postprandial. A visual analogue scale assessing appetite sensations was completed at fasting and at 15, 30, 45, 60, 90, 120, 150, and 180 min postprandial. Mean energy intake was assessed using three web-based 24 h dietary recalls at each trimester. Lower postprandial GLP-1 responses were observed in the 2nd (p = 0.004) and 3rd trimesters (p < 0.001) compared to the 1st trimester. Greater postprandial sensations of desire to eat, hunger, and prospective food consumption were noted in the 3rd trimester compared to the 1st trimester (p < 0.04, for all). Fasting GLP-1 was negatively associated with fasting appetite sensations (except fullness) at the 2nd trimester (p < 0.02, for all). Postprandially, significant associations were observed for incremental areas under the curve from 0 to 30 min between GLP-1 and fullness at the 2nd (p = 0.01) and 3rd trimesters (p = 0.03). No associations between fasting or postprandial GLP-1 and usual energy intake were observed. Overall, GLP-1 and appetite sensation responses significantly differ between trimesters, but few associations were observed between GLP-1, appetite sensations, and usual energy intake.

Implementation of Recommendations on the Use of Corticosteroids in Severe COVID-19.

Importance: Research diversity and representativeness are paramount in building trust, generating valid biomedical knowledge, and possibly in implementing clinical guidelines. Objectives: To compare variations over time and across World Health Organization (WHO) geographic regions of corticosteroid use for treatment of severe COVID-19; secondary objectives were to evaluate the association between the timing of publication of the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial (June 2020) and the WHO guidelines for corticosteroids (September 2020) and the temporal trends observed in corticosteroid use by region and to describe the geographic distribution of the recruitment in clinical trials that informed the WHO recommendation. Design, Setting, and Participants: This prospective cohort study of 434 851 patients was conducted between January 31, 2020, and September 2, 2022, in 63 countries worldwide. The data were collected under the auspices of the International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC)-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Analyses were restricted to patients hospitalized for severe COVID-19 (a subset of the ISARIC data set). Exposure: Corticosteroid use as reported to the ISARIC-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Main Outcomes and Measures: Number and percentage of patients hospitalized with severe COVID-19 who received corticosteroids by time period and by WHO geographic region. Results: Among 434 851 patients with confirmed severe or critical COVID-19 for whom receipt of corticosteroids could be ascertained (median [IQR] age, 61.0 [48.0-74.0] years; 53.0% male), 174 307 (40.1%) received corticosteroids during the study period. Of the participants in clinical trials that informed the guideline, 91.6% were recruited from the United Kingdom. In all regions, corticosteroid use for severe COVID-19 increased, but this increase corresponded to the timing of the RECOVERY trial (time-interruption coefficient 1.0 [95% CI, 0.9-1.2]) and WHO guideline (time-interruption coefficient 1.9 [95% CI, 1.7-2.0]) publications only in Europe. At the end of the study period, corticosteroid use for treatment of severe COVID-19 was highest in the Americas (5421 of 6095 [88.9%]; 95% CI, 87.7-90.2) and lowest in Africa (31 588 of 185 191 [17.1%]; 95% CI, 16.8-17.3). Conclusions and Relevance: The results of this cohort study showed that implementation of the guidelines for use of corticosteroids in the treatment of severe COVID-19 varied geographically. Uptake of corticosteroid treatment was lower in regions with limited clinical trial involvement. Improving research diversity and representativeness may facilitate timely knowledge uptake and guideline implementation.

Promoting healthy eating in early pregnancy in individuals at risk of gestational diabetes mellitus: does it improve glucose homeostasis? A study protocol for a randomized control trial.

Background: Healthy eating during pregnancy has favorable effects on glycemic control and is associated with a lower risk of gestational diabetes mellitus (GDM). According to Diabetes Canada, there is a need for an effective and acceptable intervention that could improve glucose homeostasis and support pregnant individuals at risk for GDM. Aims: This unicentric randomized controlled trial (RCT) aims to evaluate the effects of a nutritional intervention initiated early in pregnancy, on glucose homeostasis in 150 pregnant individuals at risk for GDM, compared to usual care. Methods: Population: 150 pregnant individuals ≥18 years old, at ≤14 weeks of pregnancy, and presenting ≥1 risk factor for GDM according to Diabetes Canada guidelines. Intervention: The nutritional intervention initiated in the first trimester is based on the health behavior change theory during pregnancy and on Canada's Food Guide recommendations. It includes (1) four individual counseling sessions with a registered dietitian using motivational interviewing (12, 18, 24, and 30 weeks), with post-interview phone call follow-ups, aiming to develop and achieve S.M.A.R.T. nutritional objectives (specific, measurable, attainable, relevant, and time-bound); (2) 10 informative video clips on healthy eating during pregnancy developed by our team and based on national guidelines, and (3) a virtual support community via a Facebook group. Control: Usual prenatal care. Protocol: This RCT includes three on-site visits (10-14, 24-26, and 34-36 weeks) during which a 2-h oral glucose tolerance test is done and blood samples are taken. At each trimester and 3 months postpartum, participants complete web-based questionnaires, including three validated 24-h dietary recalls to assess their diet quality using the Healthy Eating Food Index 2019. Primary outcome: Difference in the change in fasting blood glucose (from the first to the third trimester) between groups. This study has been approved by the Ethics Committee of the Centre de recherche du CHU de Québec-Université Laval. Discussion: This RCT will determine whether a nutritional intervention initiated early in pregnancy can improve glucose homeostasis in individuals at risk for GDM and inform Canadian stakeholders on improving care trajectories and policies for pregnant individuals at risk for GDM. Clinical trial registration: https://clinicaltrials.gov/study/NCT05299502, NCT05299502.

Squaring Things Up with R2: What It Is and What It Can (and Cannot) Tell You.

The coefficient of correlation (r) and the coefficient of determination (R2 or r2) have long been used in analytical chemistry, bioanalysis and forensic toxicology as figures demonstrating linearity of the calibration data in method validation. We clarify here what these two figures are and why they should not be used for this purpose in the context of model fitting for prediction. R2 evaluates whether the data are better explained by the regression model used than by no model at all (i.e., a flat line of slope = 0 and intercept $\bar y$), and to what degree. Hopefully, in the context of calibration curves, the fact that a linear regression better explains the data than no model at all should not be a point of contention. Upon closer examination, a series of restrictions appear in the interpretation of these coefficients. They cannot indicate whether the dataset at hand is linear or not, because they assume that the regression model used is an adequate model for the data. For the same reason, they cannot disprove the existence of another functional relationship in the data. By definition, they are influenced by the variability of the data. The slope of the calibration curve will also change their value. Finally, when heteroscedastic data are analyzed, the coefficients will be influenced by calibration levels spacing within the dynamic range, unless a weighted version of the equations is used. With these considerations in mind, we suggest to stop using r and R2 as figures of merit to demonstrate linearity of calibration curves in method validations. Of course, this does not preclude their use in other contexts. Alternative paths for evaluation of linearity and calibration model validity are summarily presented.

Trimester-specific gestational weight gain in women with and without previous bariatric surgeries.

OBJECTIVES: The study aimed 1) to compare trimester-specific and total gestational weight gain (GWG) between mothers who had undergone biliopancreatic diversion with duodenal switch (BPD) and two control groups of unoperated women and 2) to examine the associations between GWG, intrauterine fetal growth and neonatal birthweight. METHODS: This retrospective study included data collected in medical records of newborns and mothers from 3 groups: the first control group (PP) included mothers (n = 158) with a pre-pregnancy BMI similar to that of the surgical group (n = 63) and the second one (PS) included mothers (n = 85) with a pre-pregnancy BMI corresponding to that of the surgical group prior to BPD or a BMI > 40 kg/m2. Trimester-specific GWG was obtained using linear interpolation and compared to the recommendations. RESULTS: Women exposed to BPD have an increased prevalence of insufficient weight gain in the second and third trimesters as well as for the whole pregnancy in comparison with women in the PP group. The weekly GWG rate in the third trimester was significantly lower in women exposed to BPD, compared to both control groups. Although the newborns of women with previous BPD were significantly smaller during pregnancy and at birth, no association was found with GWG. CONCLUSION: Women exposed to BPD are at substantial risk of insufficient GWG, however, mechanisms and long-term impacts require further investigation.

DOI estimation through signal arrival time distribution: a theoretical description including proof of concept measurements.

The challenge to reach 10 ps coincidence time resolution (CTR) in time-of-flight positron emission tomography (TOF-PET) is triggering major efforts worldwide, but timing improvements of scintillation detectors will remain elusive without depth-of-interaction (DOI) correction in long crystals. Nonetheless, this momentum opportunely brings up the prospect of a fully time-based DOI estimation since fast timing signals intrinsically carry DOI information, even with a traditional single-ended readout. Consequently, extracting features of the detected signal time distribution could uncover the spatial origin of the interaction and in return, provide enhancement on the timing precision of detectors. We demonstrate the validity of a time-based DOI estimation concept in two steps. First, experimental measurements were carried out with current LSO:Ce:Ca crystals coupled to FBK NUV-HD SiPMs read out by fast high-frequency electronics to provide new evidence of a distinct DOI effect on CTR not observable before with slower electronics. Using this detector, a DOI discrimination using a double-threshold scheme on the analog timing signal together with the signal intensity information was also developed without any complex readout or detector modification. As a second step, we explored by simulation the anticipated performance requirements of future detectors to efficiently estimate the DOI and we proposed four estimators that exploit either more generic or more precise features of the DOI-dependent timestamp distribution. A simple estimator using the time difference between two timestamps provided enhanced CTR. Additional improvements were achieved with estimators using multiple timestamps (e.g. kernel density estimation and neural network) converging to the Cramér-Rao lower bound developed in this work for a time-based DOI estimation. This two-step study provides insights on current and future possibilities in exploiting the timing signal features for DOI estimation aiming at ultra-fast CTR while maintaining detection efficiency for TOF PET.

Development and Validation of a Predictive Model of Pain Modulation Profile to Guide Chronic Pain Treatment: A Study Protocol.

Introduction: Quantitative sensory testing is frequently used in research to assess endogenous pain modulation mechanisms, such as Temporal Summation (TS) and Conditioned Pain Modulation (CPM), reflecting excitatory and inhibitory mechanisms, respectively. Numerous studies found that a dysregulation of these mechanisms is associated with chronic pain conditions. In turn, such a patient's "profile" (increased TS and/or weakened CPM) could be used to recommend different pharmacological treatments. However, the procedure to evaluate these mechanisms is time-consuming and requires expensive equipment that is not available in the clinical setting. In this study, we aim to identify psychological, physiological and socio-demographic markers that could serve as proxies to allow healthcare professionals to identify these pain phenotypes in clinic, and consequently optimize pharmacological treatments. Method: We aim to recruit a healthy participant cohort (n = 360) and a chronic pain patient cohort (n = 108). Independent variables will include psychological questionnaires, pain measurements, physiological measures and sociodemographic characteristics. Dependent variables will include TS and CPM, which will be measured using quantitative sensory testing in a single session. We will evaluate one prediction model and two validation models (for healthy and chronic pain participants) using multiple regression analysis between TS/CPM and our independent variables. The significance thresholds will be set at p = 0.05, respectively. Perspectives: This study will allow us to develop a predictive model to compute the pain modulation profile of individual patients based on their biopsychosocial characteristics. The development of the predictive model is the first step toward the overarching goal of providing clinicians with a set of quick and cheap tests, easily applicable in clinical practice to orient pharmacological treatments.

Healthy for My Baby Research Protocol- a Randomized Controlled Trial Assessing a Preconception Intervention to Improve the Lifestyle of Overweight Women and Their Partners.

Background: Preconception lifestyle interventions appear promising to reduce pregnancy complications, prevent adult cardiometabolic diseases, and prevent childhood obesity. These interventions have almost exclusively been studied in populations of obese infertile women. The development of preconception lifestyle interventions targeting a broader population of overweight and obese women without a history infertility and their partners is needed. Methods: This study is a multicenter open label parallel group randomized controlled trial. Sixty-eight non-infertile women with overweight or obesity in the preconception period and their partners will be recruited from the Sherbrooke and Quebec City regions. The couples will be randomized in a 1:1 ratio to receive the Healthy for my Baby intervention or standard care in the preconception period and pregnancy. Women and their partners will be invited to take part in this lifestyle intervention which includes motivational interviews and daily self-monitoring of lifestyle goals through a mobile phone application. The primary endpoint of this study is the diet quality of women during the preconception period, which will be evaluated using the C-HEI 2007 score at baseline, 2, 4- and 6-months following study enrolment. Women's dietary quality will also be evaluated through the measure of urinary biomarkers of habitual dietary intake at baseline and 2 months in preconception, and 24-26 weeks in pregnancy. Additional indicators of women's lifestyle as well as anthropometric measures will be documented in preconception and pregnancy. For the pregnancy period, the main secondary endpoint is the pattern of gestational weight gain. Pregnancy and neonatal complications will also be evaluated. For partners, diet quality, other lifestyle habits, and anthropometric measures will be documented in the preconception and pregnancy periods. Discussion: This study will evaluate the effectiveness of a low-cost intervention designed to improve diet and other lifestyle characteristics of women in the preconception period who are overweight or obese. If the Healthy for my Baby intervention is efficacious regarding dietary measures, larger trials will be needed to evaluate the impact of this intervention on the rates of pregnancy complications, childhood obesity, and adult cardiometabolic disease. Clinical Trial Registration:clinicaltrials.gov (NCT04242069).

Qualitative threshold method validation and uncertainty evaluation: A theoretical framework and application to a 40 analytes liquid chromatography-tandem mass spectrometry method.

Qualitative methods hold an important place in drug testing, filling central needs in screening and analyses, among others, linked to per se legislation. Nevertheless, the bioanalytical method validation guidelines do not discuss this type of method or describe method validation procedures ill-adapted to qualitative methods. The output of qualitative methods are typically categorical, binary results, such as presence/absence or above cut-off/below cut-off. As the goal of any method validation is to demonstrate fitness for use under production conditions, qualitative validation guidelines should evaluate performance based on discrete, binary results instead of the continuous measurements obtained from the instrument (e.g. area). A tentative validation guideline for threshold qualitative methods was developed by in silico modelling of measurements and derived binary results. This preliminary guideline was applied to a liquid chromatography-tandem mass spectrometry method for 40 analytes, each with a defined threshold concentration. Validation parameters calculated from the analysis of 30 samples spiked above and below the threshold concentration (false negative rate, false positive rate, selectivity rate, sensitivity rate and reliability rate) showed a surprisingly high failure rate. Overall, 13 out of the 40 analytes were not considered validated. A subsequent examination found that this was attributable to an appreciable shift in the standard deviation of the area ratio on a day-to-day basis, a previously undescribed and unaccounted-for behaviour in the qualitative threshold method validation literature. Consequently, the developed guideline was modified and used to validate a qualitative threshold method, based on the binary results for performance evaluation and incorporating measurement uncertainty.

Procedure for the Selection and Validation of a Calibration Model II-Theoretical Basis.

In the first part of this paper (I-Description and application), an automated, stepwise and analyst-independent process for the selection and validation of calibration models was put forward and applied to two model analytes. This second part presents the mathematical reasoning and experimental work underlying the selection of the different components of this procedure. Different replicate analysis designs (intra/inter-day and intra/inter-extraction) were tested and their impact on test results was evaluated. For most methods, the use of intra-day/intra-extraction measurement replicates is recommended due to its decreased variability. This process should be repeated three times during the validation process in order to assess the time stability of the underlying model. Strategies for identification of heteroscedasticity and their potential weaknesses were examined and a unilateral F-test using the lower limit of quantification and upper limit of quantification replicates was chosen. Three different options for model selection were examined and tested: ANOVA lack-of-fit (LOF), partial F-test and significance of the second-order term. Examination of mathematical assumptions for each test and LC-MS-MS experimental results lead to selection of the partial F-test as being the most suitable. The advantages and drawbacks of ANOVA-LOF, examination of the standardized residuals graph and residuals normality testing (Kolmogorov-Smirnov or Cramer-Von Mises) for validation of the calibration model were examined with the last option proving the best in light of its robustness and accuracy. Choosing the correct calibration model improves QC accuracy, and simulations have shown that this automated scheme has a much better performance than a more traditional method of fitting with increasingly complex models until QC accuracies pass below a threshold.

Procedure for the Selection and Validation of a Calibration Model I-Description and Application.

Calibration model selection is required for all quantitative methods in toxicology and more broadly in bioanalysis. This typically involves selecting the equation order (quadratic or linear) and weighting factor correctly modelizing the data. A mis-selection of the calibration model will generate lower quality control (QC) accuracy, with an error up to 154%. Unfortunately, simple tools to perform this selection and tests to validate the resulting model are lacking. We present a stepwise, analyst-independent scheme for selection and validation of calibration models. The success rate of this scheme is on average 40% higher than a traditional "fit and check the QCs accuracy" method of selecting the calibration model. Moreover, the process was completely automated through a script (available in Supplemental Data 3) running in RStudio (free, open-source software). The need for weighting was assessed through an F-test using the variances of the upper limit of quantification and lower limit of quantification replicate measurements. When weighting was required, the choice between 1/x and 1/x2 was determined by calculating which option generated the smallest spread of weighted normalized variances. Finally, model order was selected through a partial F-test. The chosen calibration model was validated through Cramer-von Mises or Kolmogorov-Smirnov normality testing of the standardized residuals. Performance of the different tests was assessed using 50 simulated data sets per possible calibration model (e.g., linear-no weight, quadratic-no weight, linear-1/x, etc.). This first of two papers describes the tests, procedures and outcomes of the developed procedure using real LC-MS-MS results for the quantification of cocaine and naltrexone.

Determination of confidence intervals in non-normal data: application of the bootstrap to cocaine concentration in femoral blood.

Calculating the confidence interval is a common procedure in data analysis and is readily obtained from normally distributed populations with the familiar [Formula: see text] formula. However, when working with non-normally distributed data, determining the confidence interval is not as obvious. For this type of data, there are fewer references in the literature, and they are much less accessible. We describe, in simple language, the percentile and bias-corrected and accelerated variations of the bootstrap method to calculate confidence intervals. This method can be applied to a wide variety of parameters (mean, median, slope of a calibration curve, etc.) and is appropriate for normal and non-normal data sets. As a worked example, the confidence interval around the median concentration of cocaine in femoral blood is calculated using bootstrap techniques. The median of the non-toxic concentrations was 46.7 ng/mL with a 95% confidence interval of 23.9-85.8 ng/mL in the non-normally distributed set of 45 postmortem cases. This method should be used to lead to more statistically sound and accurate confidence intervals for non-normally distributed populations, such as reference values of therapeutic and toxic drug concentration, as well as situations of truncated concentration values near the limit of quantification or cutoff of a method.