Dynamics of cortisol levels measured in pregnant women during pregnancy determined at different ANC visits. by Francois Kiemde (5369657)

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Rates of change in each retinal layer thickness, calculated using linear mixed models. by Jung-Tae Kim (8997767)

Linear mixed-effect model determination of factors associated with changes in best-corrected visual acuity. by Jung-Tae Kim (8997767)

Stratification of cortisol and prolactin concentration by gravidity in peripheral blood and umbilical blood at delivery. by Francois Kiemde (5369657)

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Cortisol and prolactin concentration in non-pregnant women. by Francois Kiemde (5369657)

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S1 Data - by Francois Kiemde (5369657)

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Interplay or correlation of cortisol on prolactin during pregnancy. by Francois Kiemde (5369657)

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Cortisol and prolactin concentration in peripheral blood and umbilical cord blood at delivery. by Francois Kiemde (5369657)

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Malaria infection by gestation and gestational age. by Francois Kiemde (5369657)

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Interplay or correlation of prolactin on cortisol during pregnancy. by Francois Kiemde (5369657)

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Characteristic of study population. by Francois Kiemde (5369657)

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Dynamic of prolactin in pregnant women during pregnancy. by Francois Kiemde (5369657)

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Factors associated with the hemoglobin level stratified by age group: Linear regression. by Alejandro Rojas Chaves (20614814)

Linear mixed model results, fixed effects for time points, group, time points x group and univariate effects in the two groups WAD grades 2 and 3. by Anneli Peolsson (7867601)

Multiple linear regression analysis of the RAAS and glucose metabolism indicators before and after treatment in DKD and non-DKD patients. by Ningning Wang (560944)

Linear mixed model results, fixed effects for time points, group, time points x group and univariate effects in the neck-specific exercise with internet support (NSEIT) group and t... by Anneli Peolsson (7867601)

Univariate analyses. by Zachary E. M. Giovannini-Green (22008277)

“…Independent variables in the analyses were: 1) age, 2) sex, 3) geographic region, 4) urban or rural residence, and 5) ED visit before or during COVID-19. Multiple linear regression with Generalized Estimating Equations (GEE) modelling was used to identify factors associated with mean monthly ED visits. …”

Overview of individuals in the study. by Zachary E. M. Giovannini-Green (22008277)

“…Independent variables in the analyses were: 1) age, 2) sex, 3) geographic region, 4) urban or rural residence, and 5) ED visit before or during COVID-19. Multiple linear regression with Generalized Estimating Equations (GEE) modelling was used to identify factors associated with mean monthly ED visits. …”

Multivariate analyses. by Zachary E. M. Giovannini-Green (22008277)

“…Independent variables in the analyses were: 1) age, 2) sex, 3) geographic region, 4) urban or rural residence, and 5) ED visit before or during COVID-19. Multiple linear regression with Generalized Estimating Equations (GEE) modelling was used to identify factors associated with mean monthly ED visits. …”

COVID19 effect on essential services. by Admas Abera (11821659)

“…The difference in the trends of services before and during COVID-19 was compared using linear-by-linear tests and the difference of magnitude across the indicators was compared using Autoregressive Integrated Moving Average (ARIMA) interrupted time series analysis at a 5% significance level.…”