Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis.

Deep learning algorithms have demonstrated remarkable potential in clinical diagnostics, particularly in the field of medical imaging. In this study, we investigated the application of deep learning models in early detection of fetal kidney anomalies. To provide an enhanced interpretation of those models' predictions, we proposed an adapted two-class representation and developed a multi-class model interpretation approach for problems with more than two labels and variable hierarchical grouping of labels. Additionally, we employed the explainable AI (XAI) visualization tools Grad-CAM and HiResCAM, to gain insights into model predictions and identify reasons for misclassifications. The study dataset consisted of 969 ultrasound images from unique patients; 646 control images and 323 cases of kidney anomalies, including 259 cases of unilateral urinary tract dilation and 64 cases of unilateral multicystic dysplastic kidney. The best performing model achieved a cross-validated area under the ROC curve of 91.28% ± 0.52%, with an overall accuracy of 84.03% ± 0.76%, sensitivity of 77.39% ± 1.99%, and specificity of 87.35% ± 1.28%. Our findings emphasize the potential of deep learning models in predicting kidney anomalies from limited prenatal ultrasound imagery. The proposed adaptations in model representation and interpretation represent a novel solution to multi-class prediction problems.

Public attitudes towards COVID-19 vaccine mandates and vaccine certificates in Canada: a time series study.

INTRODUCTION: Since the beginning of the pandemic, numerous public health measures such as COVID-19 vaccines, vaccine mandates and vaccination certificates have been introduced to mitigate the spread of COVID-19. Public opinion and attitudes towards these measures have fluctuated in response to the dynamic political, social, and cultural landscape of the pandemic. METHODS: We conducted a time-series study consisting of national cross-sectional surveys between November 2021 to March 2022 to evaluate the Canadian public's attitudes towards COVID-19 vaccine mandates and vaccine certificates. RESULTS: When examining public sentiment towards COVID-19 vaccine certificates and proof of vaccination measures, there was a shift in responses over time. The proportion of participants "strongly supporting" these measures decreased from 66.0 to 43.1% between W25(Capacity Limits), -W32 (Mask Mandate Removed), whereas "strongly oppose" was the second most common response and rose from 15.9 to 20.6% during this same time period. Concurrently, when examining participants views surrounding mandates, many participants believed that their province was reopening at "about the right pace", which remained relatively stable over time (33.0-35.4%) between W28 (Emergency Act)-W32 (Mask Mandate Removed). CONCLUSION: Our study's findings on the public's attitudes towards COVID-19 vaccine mandates and vaccine certificates in Canada may aid to guide and streamline the implementation of future similar public health interventions. Future research should include extended follow-up and a more comprehensive examination of trust in government institutions and polarized perspectives on vaccine mandates.

Inherited thrombophilia gene mutations and risk of venous thromboembolism in patients with cancer: A systematic review and meta-analysis.

In the general population, individuals with an inherited thrombophilia have a higher risk of thrombosis, but the effect of inherited thrombophilia on the risk of cancer-associated venous thromboembolism (VTE) remains controversial. Our objective was to determine the risk of VTE in cancer patients with inherited thrombophilia. We conducted a systematic review and meta-analysis of studies reporting on VTE after a cancer diagnosis in adult patients who were tested for inherited thrombophilia. In September 2022, we searched Medline, EMBASE, and Cochrane Central. Two reviewers screened the abstracts/full texts and assessed study quality using the Quality in Prognostic Studies tool. We used Mantel-Haenszel random-effects models to estimate pooled odds ratios (OR) of VTE and 95% confidence intervals (95%CI). We included 37 and 28 studies in the systematic review and meta-analysis, respectively. Most studies focused on specific cancer types and hematologic malignancies were rare. The risk of VTE was significantly higher in cancer patients with non-O (compared with O) blood types (OR: 1.56 [95% CI: 1.28-1.90]), Factor V Leiden, and Prothrombin Factor II G20210A mutations compared with wild types (OR: 2.28 [95% CI: 1.51-3.48] and 2.14 [95% CI: 1.14-4.03], respectively). Additionally, heterozygous and homozygous methylenetetrahydrofolate reductase C677T had ORs of 1.50 (95% CI: 1.00-2.24) and 1.38 (95% CI: 0.87-2.22), respectively. Among those with Plasminogen-Activator Inhibitor-1 4G/5G, Vascular Endothelial Growth Factor (VEGF) A C634G, and VEGF C2578A mutations, there was no significant association with VTE. In conclusion, this meta-analysis provided evidence that non-O blood types, Factor V Leiden, and Prothrombin Factor II G20210A mutations are important genetic risk factors for VTE in cancer patients.

Relationship Between Gestational Weight Gain and Health Service Utilization in Early Childhood: A Retrospective Cohort Study.

OBJECTIVE: Gestational weight gain (GWG) outside recommended ranges can negatively impact both the woman and child. The long-term effects of below-recommended or above-recommended GWG on the child are unclear. METHODS: This retrospective cohort study used a population-based birth registry of 258,005 live births to evaluate the relationship between maternal GWG and paediatric health service use. RESULTS: The results suggest below recommended GWG in underweight women in particular is associated with an increased rate of hospitalizations and specialist visits for the child in the first 24 months. CONCLUSION: Findings indicate that GWG may impact paediatric outcomes in ways that depend on pre-pregnancy body mass index, as derived from maternal height and weight measures.

Serological markers and long COVID-A rapid systematic review.

BACKGROUND: Long COVID is highly heterogeneous, often debilitating, and may last for years after infection. The aetiology of long COVID remains uncertain. Examination of potential serological markers of long COVID, accounting for clinical covariates, may yield emergent pathophysiological insights. METHODS: In adherence to PRISMA guidelines, we carried out a rapid review of the literature. We searched Medline and Embase for primary observational studies that compared IgG response in individuals who experienced COVID-19 symptoms persisting ≥12 weeks post-infection with those who did not. We examined relationships between serological markers and long COVID status and investigated sources of inter-study variability, such as severity of acute illness, long COVID symptoms assessed and target antigen(s). RESULTS: Of 8018 unique records, we identified 29 as being eligible for inclusion in synthesis. Definitions of long COVID varied. In studies that reported anti-nucleocapsid (N) IgG (n = 10 studies; n = 989 participants in aggregate), full or partial anti-Spike IgG (i.e. the whole trimer, S1 or S2 subgroups, or receptor binding domain, n = 19 studies; n = 2606 participants), or neutralizing response (n = 7 studies; n = 1123 participants), we did not find strong evidence to support any difference in serological markers between groups with and without persisting symptoms. However, most studies did not account for severity or level of care required during acute illness, and other potential confounders. CONCLUSIONS: Pooling of studies would enable more robust exploration of clinical and serological predictors among diverse populations. However, substantial inter-study variations hamper comparability. Standardized reporting practices would improve the quality, consistency and comprehension of study findings.

The Transformative Potential of AI in Obstetrics and Gynaecology.

The transformative power of artificial intelligence (AI) is reshaping diverse domains of medicine. Recent progress, catalyzed by computing advancements, has seen commensurate adoption of AI technologies within obstetrics and gynaecology. We explore the use and potential of AI in three focus areas: predictive modelling for pregnancy complications, Deep learning-based image interpretation for precise diagnoses, and large language models enabling intelligent health care assistants. We also provide recommendations for the ethical implementation, governance of AI, and promote research into AI explainability, which are crucial for responsible AI integration and deployment. AI promises a revolutionary era of personalized health care in obstetrics and gynaecology.

A Hospital-Wide Open-Label Cluster Crossover Pragmatic Comparative Effectiveness Randomized Trial Comparing Normal Saline to Ringer's Lactate: Protocol and Statistical Analysis Plan of The FLUID Trial.

BACKGROUND: Normal saline (NS) and Ringer's lactate (RL) are the most common crystalloids given to hospitalized patients. Despite concern about possible harm associated with NS (eg, hyperchloremic metabolic acidosis, impaired kidney function, and death), few large multicenter randomized trials focused on critically ill patients have compared these fluids. Uncertainty exists about the effects of these fluids on clinically important outcomes across all hospitalized patients. OBJECTIVE: The FLUID trial is a pragmatic, multicenter, 2×2 cluster crossover comparative effectiveness randomized trial that aims to evaluate the effectiveness of a hospital-wide policy that stocks either NS or RL as the main crystalloid fluid in 16 hospitals across Ontario, Canada. METHODS: All hospitalized adult and pediatric patients (anticipated sample size 144,000 patients) with an incident admission to the hospital over the course of each study period will be included. Either NS or RL will be preferentially stocked throughout the hospital for 12 weeks before crossing to the alternate fluid for the subsequent 12 weeks. The primary outcome is a composite of death and hospital readmission within 90 days of hospitalization. Secondary outcomes include death, hospital readmission, dialysis, reoperation, postoperative reintubation, length of hospital stay, emergency department visits, and discharge to a facility other than home. All outcomes will be obtained from health administrative data, eliminating the need for individual case reports. The primary analysis will use cluster-level summaries to estimate cluster-average treatment effects. RESULTS: The statistical analysis plan has been prepared "a priori" in advance of receipt of the trial data set from ICES and any analyses. CONCLUSIONS: We describe the protocol and statistical analysis plan for the evaluation of primary and secondary outcomes for the FLUID trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT04512950; https://classic.clinicaltrials.gov/ct2/show/NCT04512950. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51783.

Gestational weight loss and fetal growth in uncomplicated pregnancies among women with obesity: a population-based retrospective cohort study.

OBJECTIVE: The impact of gestational weight loss (GWL) on fetal growth among women with obesity remains unclear. This study aimed to examine the association between weight loss during pregnancy among women with body mass index (BMI) ≥ 30 kg/m2 and the risk of small-for-gestational-age (SGA) and large-for-gestational-age (LGA) neonates. METHODS: We conducted a retrospective, population-based cohort study of women with pre-pregnancy obesity that resulted in a singleton live birth in 2012-2017, using birth registry data in Ontario, Canada. Women with pregnancy complications or health conditions which could cause weight loss were excluded. GWL is defined as negative gestational weight change (≤0 kg). The association between GWL and fetal growth was estimated using generalized estimating equation models and restricted cubic spline regression analysis. Stratified analysis was conducted by obesity class (I:30-34.9 kg/m2, II:35-39.9 kg/m2, and III + : ≥40 kg/m2). RESULTS: Of the 52,153 eligible women who entered pregnancy with a BMI ≥ 30 kg/m2, 5.3% had GWL. Compared to adequate gestational weight gain, GWL was associated with an increased risk of SGA neonates (aRR:1.45, 95% CI: 1.30-1.60) and a decreased risk of LGA neonates (aRR: 0.81, 95% CI:0.73-0.93). Non-linear L-shaped associations were observed between gestational weight change and SGA neonates, with an increased risk of SGA observed with increased GWL. On the contrary, non-linear S-shaped associations were observed between gestational weight change and LGA neonates, with a decreased risk of LGA observed with increased GWL. Similar findings were observed from the stratified analysis by obesity class. CONCLUSION: These findings highlight that GWL in women with obesity may increase the risk of SGA neonates but reduce the risk of LGA neonates. Recommendations of GWL for women with obesity should be interpreted with caution.

Thrombophilia gene mutations predict venous thromboembolism in ambulatory cancer patients receiving chemotherapy.

BACKGROUND: Inherited thrombophilia and cancer both independently increase the risk of venous thromboembolism (VTE). However, whether the increased VTE risk associated with inherited thrombophilia exists in cancer patients is less clear. OBJECTIVES: Our objective was to determine the influence of inherited thrombophilia on VTE and bleeding risk in moderate-to-high-risk ambulatory cancer patients receiving chemotherapy. METHODS: We conducted a post hoc analysis using blood samples from patients enrolled in the AVERT trial to determine if previously recognized thrombophilia gene mutations (prothrombin factor [F] II G20210A, FXI, fibrinogen gamma, serpin family A member 10, FV K858R, FXIII, FV Leiden [FVL], and ABO blood) were associated with VTE or bleeding during the 7-months after starting chemotherapy. Logistic regression was used to compare heterozygous and homozygous mutations (combined) to wild-type. VTE rates, bleeding rates, and risk differences for mutations stratified by prophylactic anticoagulation use were calculated. RESULTS: Of the 447 patients, there were 39 VTE and 39 bleeding events. The odds of VTE were significantly increased with FVL mutation and non-O blood type (odds ratio [OR]: 5.2; 95% CI: 1.9-14.7 and OR: 2.7; 95% CI: 1.2-6.1, respectively). The use of anticoagulation prophylaxis resulted in complete protection in FVL patients, whereas those not receiving anticoagulation had a VTE rate of 119 per 100 patient-years. Lower VTE rates were also observed in non-O blood type patients taking prophylactic anticoagulation. No other thrombophilia genes tested were significantly associated with VTE or bleeding. CONCLUSION: Our results indicate that FVL mutation and ABO blood type may be important VTE predictors in cancer patients starting chemotherapy.

Maternal weight and paediatric health use: mediating role of adverse birth outcomes: a retrospective cohort study.

BACKGROUND: Maternal pre-pregnancy body mass index (BMI) and gestational weight gain (GWG) above or below recommendations have been associated with increased paediatric health service utilization as well as increased risk of adverse birth outcomes, including small for gestational age (SGA) and preterm birth (PTB). SGA and PTB are associated with numerous adverse health outcomes in the child, including delayed growth, motor and cognitive impairment. Previous research has identified birth weight and gestational age on the causal pathway in the association between maternal pre-pregnancy BMI and child hospital admissions, there are no studies to date to quantify this relationship across other areas of health service utilization, nor the impact of gestational weight gain. This study aimed to assess if SGA or PTB partially explain the association between maternal weight and paediatric health service utilization. METHODS: The study population consisted of all women who delivered a singleton, live infant in Ontario between 2012 and 2014, and was assembled from data contained in the provincial birth registry. Health service utilization over the first 24 months following birth was examined by linking data from the registry with other provincial health administrative databases housed at ICES. The mediating roles of PTB and SGA were assessed using the Baron-Kenny method and causal mediation analysis. RESULTS: A total of 204,162 infants were included in the analysis of maternal pre-pregnancy BMI and 171,127 infants were included in the GWG analysis. The small magnitude of association between maternal BMI and paediatric health service utilization impacted our ability to estimate the indirect effect of maternal BMI through adverse birth outcomes (adjusted indirect effect = 0.00). 56.7% of the association between below recommended GWG and increased hospitalizations was attributed to PTB, while 6.8% of the association was attributed to SGA. CONCLUSION: Paediatric hospitalizations may be partially attributable to PTB and SGA in children born to mothers with below-recommended GWG. However, maternal weight also appears to be related to increased paediatric health service utilization independent of PTB and SGA.

The influence of sociodemographic factors on COVID-19 vaccine certificate acceptance: A cross-sectional study.

Vaccine certificates have been implemented worldwide, aiming to promote vaccination rates and to reduce the spread of COVID-19. However, their use during the COVID-19 pandemic was controversial and has been criticized for infringing upon medical autonomy and individual rights. We administered a national online survey exploring social and demographic factors predicting the degree of public approval of vaccine certificates in Canada. We conducted a multivariate linear regression which revealed which factors were predictive of vaccine certificate acceptance in Canada. Self-reported minority status (p < .001), rurality (p < .001), political ideology (p < .001), age (p < .001), having children under 18 in the household (p < .001), education (p = .014), and income status (p = .034) were significant predictors of attitudes toward COVID-19 vaccine certificates. We observed the lowest vaccine-certificate approval among participants who: self-identify as a visible minority; live in rural areas; are politically conservative; are 18-34 years of age; have children under age 18 living in the household; have completed an apprenticeship or trades education; and those with an annual income between $100,000-$159,999. The present findings are valuable for their ability to inform the implementation of vaccine certificates during future pandemic scenarios which may require targeted communication between public health agencies and under-vaccinated populations.

Effect of Donor Sex on Recipient Mortality in Transfusion.

BACKGROUND: Conflicting observational evidence exists regarding the association between the sex of red-cell donors and mortality among transfusion recipients. Evidence to inform transfusion practice and policy is limited. METHODS: In this multicenter, double-blind trial, we randomly assigned patients undergoing red-cell transfusion to receive units of red cells from either male donors or female donors. Patients maintained their trial-group assignment throughout the trial period, including during subsequent inpatient and outpatient encounters. Randomization was conducted in a 60:40 ratio (male donor group to female donor group) to match the historical allocation of red-cell units from the blood supplier. The primary outcome was survival, with the male donor group as the reference group. RESULTS: A total of 8719 patients underwent randomization before undergoing transfusion; 5190 patients were assigned to the male donor group, and 3529 to the female donor group. At baseline, the mean (±SD) age of the enrolled patients was 66.8±16.4 years. The setting of the first transfusion was as an inpatient in 6969 patients (79.9%), of whom 2942 (42.2%) had been admitted under a surgical service. The baseline hemoglobin level before transfusion was 79.5±19.7 g per liter, and patients received a mean of 5.4±10.5 units of red cells in the female donor group and 5.1±8.9 units in the male donor group (difference, 0.3 units; 95% confidence interval [CI], -0.1 to 0.7). Over the duration of the trial, 1141 patients in the female donor group and 1712 patients in the male donor group died. In the primary analysis of overall survival, the adjusted hazard ratio for death was 0.98 (95% CI, 0.91 to 1.06). CONCLUSIONS: This trial showed no significant difference in survival between a transfusion strategy involving red-cell units from female donors and a strategy involving red-cell units from male donors. (Funded by the Canadian Institutes of Health Research; iTADS ClinicalTrials.gov number, NCT03344887.).

Development and external validation of machine learning algorithms for postnatal gestational age estimation using clinical data and metabolomic markers.

BACKGROUND: Accurate estimates of gestational age (GA) at birth are important for preterm birth surveillance but can be challenging to obtain in low income countries. Our objective was to develop machine learning models to accurately estimate GA shortly after birth using clinical and metabolomic data. METHODS: We derived three GA estimation models using ELASTIC NET multivariable linear regression using metabolomic markers from heel-prick blood samples and clinical data from a retrospective cohort of newborns from Ontario, Canada. We conducted internal model validation in an independent cohort of Ontario newborns, and external validation in heel prick and cord blood sample data collected from newborns from prospective birth cohorts in Lusaka, Zambia and Matlab, Bangladesh. Model performance was measured by comparing model-derived estimates of GA to reference estimates from early pregnancy ultrasound. RESULTS: Samples were collected from 311 newborns from Zambia and 1176 from Bangladesh. The best-performing model accurately estimated GA within about 6 days of ultrasound estimates in both cohorts when applied to heel prick data (MAE 0.79 weeks (95% CI 0.69, 0.90) for Zambia; 0.81 weeks (0.75, 0.86) for Bangladesh), and within about 7 days when applied to cord blood data (1.02 weeks (0.90, 1.15) for Zambia; 0.95 weeks (0.90, 0.99) for Bangladesh). CONCLUSIONS: Algorithms developed in Canada provided accurate estimates of GA when applied to external cohorts from Zambia and Bangladesh. Model performance was superior in heel prick data as compared to cord blood data.

FLUID trial: a hospital-wide open-label cluster cross-over pragmatic comparative effectiveness randomised pilot trial comparing normal saline to Ringer's lactate.

OBJECTIVES: Normal saline (NS) and Ringer's lactate (RL) are the most common crystalloids used for fluid therapy. Despite evidence of possible harm associated with NS (eg, hyperchloremic metabolic acidosis, impaired kidney function and death), few large multi-centre randomised trials have evaluated the effect of these fluids on clinically important outcomes. We conducted a pilot trial to explore the feasibility of a large trial powered for clinically important outcomes. DESIGN: FLUID was a pragmatic pilot cluster randomised cross-over trial. SETTING: Four hospitals in the province of Ontario, Canada PARTICIPANTS: All hospitalised adult and paediatric patients with an incident admission to the hospital over the course of each study period. INTERVENTIONS: A hospital wide policy/strategy which stocked either NS or RL throughout the hospital for 12 weeks before crossing over to the alternate fluid for the subsequent 12 weeks. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary feasibility outcome was study fluid protocol adherence. Secondary feasibility outcomes included time to Research Ethics Board (REB) approval and trial initiation. Primary (composite of death or re-admission to hospital in first 90 days of index hospitalisation) and secondary clinical outcomes were analysed descriptively. RESULTS: Among 24 905 included patients, mean age 59.1 (SD 20.5); 13 977 (56.1%) were female and 21 150 (85.0%) had medical or surgical admitting diagnoses. Overall, 96 821 L were administered in the NS arm, and 78 348 L in the RL arm. Study fluid adherence to NS and RL was 93.7% (site range: 91.6%-98.0%) and 79.8% (site range: 72.5%-83.9%), respectively. Time to REB approval ranged from 2 to 48 days and readiness for trial initiation from 51 to 331 days. 5544 (22.3%) patients died or required hospital re-admission in the first 90 days. CONCLUSIONS: The future large trial is feasible. Anticipating and addressing logistical challenges during the planning stages will be imperative. TRIAL REGISTRATION NUMBER: NCT02721485.

Deep ROC Analysis and AUC as Balanced Average Accuracy, for Improved Classifier Selection, Audit and Explanation.

Optimal performance is desired for decision-making in any field with binary classifiers and diagnostic tests, however common performance measures lack depth in information. The area under the receiver operating characteristic curve (AUC) and the area under the precision recall curve are too general because they evaluate all decision thresholds including unrealistic ones. Conversely, accuracy, sensitivity, specificity, positive predictive value and the F1 score are too specific-they are measured at a single threshold that is optimal for some instances, but not others, which is not equitable. In between both approaches, we propose deep ROC analysis to measure performance in multiple groups of predicted risk (like calibration), or groups of true positive rate or false positive rate. In each group, we measure the group AUC (properly), normalized group AUC, and averages of: sensitivity, specificity, positive and negative predictive value, and likelihood ratio positive and negative. The measurements can be compared between groups, to whole measures, to point measures and between models. We also provide a new interpretation of AUC in whole or part, as balanced average accuracy, relevant to individuals instead of pairs. We evaluate models in three case studies using our method and Python toolkit and confirm its utility.

Effects of the COVID-19 pandemic on self-reported 12-month pneumococcal vaccination series completion rates in Canada.

Routine childhood vaccination improves health and prevents morbidity and mortality from vaccine-preventable diseases. There are indications that the COVID-19 pandemic has negatively impacted immunization rates globally, but systematic studies on this are still lacking in Canada. This study aims to add knowledge on the pandemic's effect on children's immunization rates with pneumococcal vaccine using self-reported immunization data from CANImmunize. An interrupted time series analysis was conducted on aggregated monthly enrollment of children on the platform (2016-2021) and their pneumococcal immunization series completion rates (2016-2020). Predicted trends before and after the onset of the COVID19-related restriction (March 1, 2020) were compared by means of an Autoregressive Integrated Moving Average (ARIMA). The highest monthly enrollment was 3,474 new infant records observed in January 2020, and the lowest was 100 records in December 2021. The highest Self-reported pneumococcal immunization series completion rate was 78.89%, observed in February 2017, and the lowest was 6.94% in December 2021. Enrollment decreased by 1177.52 records (95% CI: -1865.47, -489.57), with a continued decrease of 80.84 records each month. Completion rates had an immediate increase of 14.57% (95% CI 4.64, 24.51), followed by a decrease of 3.54% each month. The onset of the COVID-19 related restrictions impacted the enrollment of children in the CANImmunize digital immunization platform and an overall decrease in self-reported pneumococcal immunization series completion rates. Our findings support efforts to increase catch-up immunization campaigns so that children who could not get scheduled immunization during the pandemic are not missed.

Validation of gestational age determination from ultrasound or a metabolic gestational age algorithm using exact date of conception in a cohort of newborns conceived using assisted reproduction technologies.

BACKGROUND: Accurate estimates of gestational age in pregnancy are important for the provision of optimal care. Although current guidelines generally recommend estimating gestational age via first-trimester ultrasound measurement of crown-rump length, error associated with this method can range from 3 to 8 days of gestation. In pregnancies resulting from assisted reproductive technology, estimated due date can be calculated on the basis of the age of the embryo and the date of embryo transfer, arguably providing the most accurate estimates possible. We have developed and extensively validated statistical models to estimate gestational age postnatally using metabolomic markers from blood samples in combination with clinical and demographic data. These models have shown high accuracy compared with first-trimester ultrasound, the recommended method for estimating gestational age in spontaneous pregnancies. We hypothesized that gestational age derived from date and stage of embryo at transfer in newborns conceived using assisted reproduction therapy would provide the most accurate reference standard possible to evaluate and compare the accuracy of both first-trimester ultrasound and metabolomic model-based gestational dating. OBJECTIVE: This study aimed to validate both first-trimester ultrasound dating and postnatal metabolomic gestational age estimation models against gestational age derived from date and stage of embryo at transfer in a cohort of newborns conceived via assisted reproductive technology, both overall and in important subgroups of interest (preterm birth, small for gestational age, and multiple birth). STUDY DESIGN: This was a retrospective cohort study of infants born in Ontario, Canada between 2015 and 2017 and captured in the provincial birth registry. Spontaneous conceptions were randomly partitioned into a model derivation sample (80%) and a test sample (20%) for model validation. A cohort of assisted conceptions resulting from fresh embryo transfers was derived to evaluate the accuracy of both ultrasound and model-based gestational dating. Postnatal gestational age estimation models were developed with multivariable linear regression using elastic-net regularization. Gestational age estimates from dating ultrasound and from postnatal metabolomic models were compared with date of embryo transfer reference gestational age in the independent test cohorts. Accuracy was quantified by calculating mean absolute error and the square root of mean squared error. RESULTS: Our model derivation cohort included 202,300 spontaneous conceptions, and the testing cohorts included 50,735 spontaneous conceptions and 1924 assisted conceptions. In the assisted conception cohort, first-trimester dating ultrasound was accurate to within approximately ±1.5 days compared with date of embryo transfer reference overall (mean absolute error, 0.21 [95% confidence interval, 0.20-0.23]). When compared with gestational age derived from date of embryo transfer, the metabolomic estimation models were accurate to within approximately ±5 days overall (0.79 [0.76-0.81] weeks). When ultrasound was used as the reference in validating the metabolomic model, the mean absolute error was slightly higher overall (0.81 [0.78-0.84] weeks). In general, the accuracy of gestational age estimates derived from ultrasound or metabolomic models was highest in term infants and lower in preterm and small-for-gestational-age newborns. CONCLUSION: Our findings support the accuracy of ultrasound as a gestational age dating tool. They also support the potential utility of metabolic gestational age dating algorithms in settings where ultrasound or other accurate methods of estimating gestational age are not available because of lack of infrastructure or specialized training (eg, low-income countries). However, the accuracy of metabolomic model-based dating was generally lower than that of ultrasound.

A Population-Based Analysis of the Risk of Glomerular Disease Relapse after COVID-19 Vaccination.

BACKGROUND: Although case reports have described relapses of glomerular disease after COVID-19 vaccination, evidence of a true association is lacking. In this population-level analysis, we sought to determine relative and absolute risks of glomerular disease relapse after COVID-19 vaccination. METHODS: In this retrospective population-level cohort study, we used a centralized clinical and pathology registry (2000-2020) to identify 1105 adult patients in British Columbia, Canada, with biopsy-proven glomerular disease that was stable on December 14, 2020 (when COVID-19 vaccines first became available). The primary outcome was disease relapse, on the basis of changes in kidney function, proteinuria, or both. Vaccination was modeled as a 30-day time-varying exposure in extended Cox regression models, stratified on disease type. RESULTS: During 281 days of follow-up, 134 (12.1%) patients experienced a relapse. Although a first vaccine dose was not associated with relapse risk (hazard ratio [HR]=0.67; 95% confidence interval [95% CI], 0.33 to 1.36), exposure to a second or third dose was associated with a two-fold risk of relapse (HR=2.23; 95% CI, 1.06 to 4.71). The pattern of relative risk was similar across glomerular diseases. The absolute increase in 30-day relapse risk associated with a second or third vaccine dose varied from 1%-2% in ANCA-related glomerulonephritis, minimal change disease, membranous nephropathy, or FSGS to 3%-5% in IgA nephropathy or lupus nephritis. Among 24 patients experiencing a vaccine-associated relapse, 4 (17%) had a change in immunosuppression, and none required a biopsy. CONCLUSIONS: In a population-level cohort of patients with glomerular disease, a second or third dose of COVID-19 vaccine was associated with higher relative risk but low absolute increased risk of relapse.

The Canadian Mother-Child Cohort Active Surveillance Initiative (CAMCCO): Comparisons between Quebec, Manitoba, Saskatchewan, and Alberta.

BACKGROUND: Given that pregnant women taking medications are excluded from clinical trials, real-world evidence is essential. We aimed to build a Canadian Mother-Child Cohort Active Surveillance Initiative (CAMCCO) and compare frequency of prematurity, low-birth-weight (LBW), major malformations, multiplicity, and gestational medication use across four provinces. METHODS: CAMCCO is a collaborative research infrastructure that uses real-world data from large provincial health care databases in Canada; developed with standardized methods to similarly construct population-based pregnancy/child cohorts with longitudinal follow-up by linking administrative/hospital/birth databases. CAMCCO also includes a common repository to i) share algorithms and case definitions based on diagnostic and procedural codes for research/training purpose, and ii) download aggregate data relevant to primary care providers, researchers, and decision makers. For this study, data from Quebec (1998-2015), Manitoba (1995-2019), Saskatchewan (1996-2020), and Alberta (2005-2018) are compared (Chi-square tests, p-values), and trends are calculated using Cochran-Armitage trend tests. RESULTS: Almost two-thirds (61%) of women took medications during pregnancy, mostly antibiotics (26%), asthma drugs (8%), and antidepressants (4%). Differences in the prevalence of prematurity (5.9-6.8%), LBW (4.0-5.2%), and multiplicity (1.0-2.5%) were statistically significant between provinces (p<0.001). Frequency of major malformations increased over time in Quebec (7-11%; p<0.001), Saskatchewan (5-11%; p<0.001), and Alberta (from 7-8%; p<0.001), and decreased in Manitoba (5-3%; p<0.001). Cardiovascular and musculoskeletal malformations were the most prevalent. INTERPRETATION: Medications are often used among Canadian pregnancies but adverse pregnancy outcomes vary across provinces. Digitized health data may help researchers and care providers understand the risk-benefit ratios related to gestational medication use, as well as province-specific trends.