ABSTRACT
Objective: This study examines vaccine confidence in pregnancy in an urban, safety-net health system by 1) determining vaccination rates for influenza (Flu), tetanus toxoid, reduced diphtheria toxoid, and acellular pertussis (Tdap) and COVID-19 and 2) examining demographic characteristics and patient-reported factors related to vaccine confidence in pregnancy. Study Design: We determined the yearly prevalence of vaccination for Tdap and Flu during pregnancy in our health system 8/2018 -1/2022 and the monthly prevalence of COVID-19 vaccination 1/2021 - 1/2022 via retrospective cohort design. We conducted a cross-sectional survey 12/14/21 - 4/12/22 using a convenience sample of pregnant individuals. Perceptions/concerns regarding the Flu and COVID-19 vaccinations were tabulated. We used univariate logistic regression models to determine the association of characteristics on vaccination odds. Result(s): The vaccination rate for Tdap ranged from 76.8% - 80.7%. The vaccination rate for Flu ranged from 64.5% - 72.5%, decreasing significantly in 2020-2021 when compared to the prior season [OR: 0.70 95% CI: (0.63, 0.77)]. COVID-19 vaccination rate increased from 0.9% in January 2021 to 49.4% by January 2022 (Figure 1). A total of 250 individuals completed the survey (57.2% Hispanic, 69.3% with reported annual household income < $50,000). 72.7% agreed that COVID-19 vaccination was important for fetal and maternal health. The primary concerns about vaccination for Flu and Covid-19 included: "safety for me," "safety for my baby," and "side effects for me". Other findings are reported in Table 1. Conclusion(s): Vaccination rates in pregnancy are below recommended levels. Individuals were less likely to receive the Flu vaccine than the Tdap vaccine, especially during the pandemic. COVID-19 vaccination increased steadily. Individuals who were receptive to the COVID-19 vaccine displayed trust in their health clinics and were likely to agree with the importance of vaccination not only for themselves and their pregnancies but also for the health of their community. [Formula presented] [Formula presented] Copyright © 2022
ABSTRACT
Objective: The objectives of this study were to measure the global impact of the pandemic on the volumes for intravenous thrombolysis (IVT), IVT transfers, and stroke hospitalizations over 4 months at the height of the pandemic (March 1 to June 30, 2020) compared with two control 4-month periods. Background: The COVID-19 pandemic led to widespread repercussions on the delivery of health care worldwide. Design/Methods: We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by ICD-10 codes and/or classifications in stroke center databases. Results: There were 91,373 stroke admissions in the 4 months immediately before compared to 80,894 admissions during the pandemic months, representing an 11.5% (95%CI,-11.7 to-11.3, p<0.0001) decline. There were 13,334 IVT therapies in the 4 months preceding compared to 11,570 procedures during the pandemic, representing a 13.2% (95%CI,-13.8 to-12.7, p<0.0001) drop. Interfacility IVT transfers decreased from 1,337 to 1,178, or an 11.9% decrease (95%CI,-13.7 to-10.3, p=0.001). There were greater declines in primary compared to comprehensive stroke centers (CSC) for stroke hospitalizations (-17.3% vs-10.3%, p<0.0001) and IVT (-15.5% vs-12.6%, p=0.0001). Recovery of stroke hospitalization volume (9.5%, 95%CI 9.2-9.8, p<0.0001) was noted over the two later (May, June) versus the two earlier (March, April) months of the pandemic, with greater recovery in hospitals with lower COVID-19 hospitalization volume, high volume stroke center, and CSC. There was a 1.48% stroke rate across 119,967 COVID-19 hospitalizations. SARS-CoV-2 infection was noted in 3.3% (1,722/52,026) of all stroke admissions. Conclusions: The COVID-19 pandemic was associated with a global decline in the volume of stroke hospitalizations, IVT, and interfacility IVT transfers. Primary stroke centers and centers with higher COVID19 inpatient volumes experienced steeper declines. Recovery of stroke hospitalization was noted in the later pandemic months, with greater recovery in hospitals with lower COVID-19 hospitalizations, high volume stroke centers, and CSCs.
ABSTRACT
Rationale: Conducting clinical trials during the pandemic is fraught with challenges like missed visits/ procedures, visits out of window, and subject discontinuation. We seek to show that predictive growth models are adequate descriptors of infant weight (wt), length (ln), and head circumference (hc) under various patterns of missing and visits outside protocol windows. Methods: Data from two ongoing and two historical studies were bootstrapped and used for simulation. Goodness of fit was evaluated by comparing how close the observed values were with those estimated by the Gompertz model using t-tests. The Gompertz is a nonlinear growth function. The model may be fitted using ≥ 3 points – the start, end, and at least a middle point. We assumed 1,2, or 3 missing middle points under different patterns of missing. To quantify clinical relevance, differences in means between predicted vs. observed for 1000 bootstrapped studies were compared to the maximum allowable differences (MAD) between repeat measurements for acceptable precision: 100 g for wt, 0.7 cm for ln, and 0.5 cm for hc, and to the 1-month WHO weight velocity standards. Results: There were no significant differences between observed and fitted data for the simulated or bootstrapped distributions (all p>0.1006). On average, predicted values differed from observed by no more than the MAD or are less than or close to the WHO 1-month weight increments that infants growing at the 1st percentile should achieve. On a study basis, in ≥ 80% of the 1000 studies, the 95% confidence interval for the mean difference (predicted – observed) were bound by ½ SD on either side. Collectively, these show that differences were not clinically relevant. Conclusion: The Gompertz model has good predictive properties for estimating infant growth at the regulatory required timepoints even in the presence of missing values or collection outside visit windows and provide an analysis strategy to mitigate the impact of Covid-19. References: N/A. Disclosure of Interest: Y. Choe Other: YC is an employee of Abbott Nutrition, G. Baggs Other: GB is an employee of Abbott Nutrition, C. Steele Other: CS is an employee of Abbott Nutrition, T. Williams Other: TW is an employee of Abbott Nutrition, A. Mackey Other: AM is an employee of Abbott Nutrition.