Publications by authors named "Jonas Haggstrom"

Article Synopsis
  • Federated networks enhance data privacy by allowing analysis without transferring sensitive data, supporting trustworthy data analysis in healthcare research.
  • The International COVID-19 Data Alliance (ICODA) tested a federated network with partners to analyze data from the International Perinatal Outcome in the Pandemic (iPOP) Study, facing both challenges and benefits in the process.
  • Establishing these networks requires significant investment and planning for technology and governance, which can lead to powerful collaborative research opportunities using health data from various countries.
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During drug development, a key step is the identification of relevant covariates predicting between-subject variations in drug response. The full random effects model (FREM) is one of the full-covariate approaches used to identify relevant covariates in nonlinear mixed effects models. Here we explore the ability of FREM to handle missing (both missing completely at random (MCAR) and missing at random (MAR)) covariate data and compare it to the full fixed-effects model (FFEM) approach, applied either with complete case analysis or mean imputation.

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Growth faltering in children (low length for age or low weight for length) during the first 1,000 days of life (from conception to 2 years of age) influences short-term and long-term health and survival. Interventions such as nutritional supplementation during pregnancy and the postnatal period could help prevent growth faltering, but programmatic action has been insufficient to eliminate the high burden of stunting and wasting in low- and middle-income countries. Identification of age windows and population subgroups on which to focus will benefit future preventive efforts.

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Sustainable Development Goal 2.2-to end malnutrition by 2030-includes the elimination of child wasting, defined as a weight-for-length z-score that is more than two standard deviations below the median of the World Health Organization standards for child growth. Prevailing methods to measure wasting rely on cross-sectional surveys that cannot measure onset, recovery and persistence-key features that inform preventive interventions and estimates of disease burden.

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Globally, 149 million children under 5 years of age are estimated to be stunted (length more than 2 standard deviations below international growth standards). Stunting, a form of linear growth faltering, increases the risk of illness, impaired cognitive development and mortality. Global stunting estimates rely on cross-sectional surveys, which cannot provide direct information about the timing of onset or persistence of growth faltering-a key consideration for defining critical windows to deliver preventive interventions.

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Article Synopsis
  • Preterm birth (PTB) is a major cause of infant mortality globally, and studies show mixed results regarding its rates during COVID-19 lockdowns, with changes ranging from -90% to +30%.
  • Analysis of data from 52 million births in 26 countries indicates modest reductions in PTB rates during the first three months of lockdown, but no significant changes in the fourth month.
  • High-income countries showed an increase in stillbirth risk during the first month of lockdown, with Brazil experiencing increased stillbirth rates throughout the entire lockdown period, highlighting the need for further investigation into these trends.
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Routine health care and research have been profoundly influenced by digital-health technologies. These technologies range from primary data collection in electronic health records (EHRs) and administrative claims to web-based artificial-intelligence-driven analyses. There has been increased use of such health technologies during the COVID-19 pandemic, driven in part by the availability of these data.

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Objectives: The role of Klebsiella pneumoniae (KP) in lower respiratory tract infection (LRTI) is not well studied. We longitudinally investigated KP colonization and its association with LRTI in a South African birth cohort.

Methods: We conducted a case-control study of infants who developed LRTI and age-matched controls, followed twice weekly through infancy.

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The global demand for coronavirus disease 2019 (COVID-19) vaccines currently far outweighs the available global supply and manufacturing capacity. As a result, securing doses of vaccines for low- and middle-income countries has been challenging, particularly for African countries. Clinical trial investigation for COVID-19 vaccines has been rare in Africa, with the only randomized clinical trials (RCTs) for COVID-19 vaccines having been conducted in South Africa.

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This paper aims to provide a perspective on data sharing practices in the context of the COVID-19 pandemic. The scientific community has made several important inroads in the fight against COVID-19, and there are over 2500 clinical trials registered globally. Within the context of the rapidly changing pandemic, we are seeing a large number of trials conducted without results being made available.

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Background: The correlates of prenatal and postnatal growth on Intelligence Quotient (IQ) in childhood in term-born children living in high-income countries are not well known.

Objectives: We examined how birth size and growth in infancy and childhood were associated with IQ at age 5 y in term-born children using path analysis.

Methods: The study sample comprised 1719 children from the Danish National Birth Cohort who participated in a substudy in which psychologists assessed IQ using the Wechsler Primary and Preschool Scales of Intelligence-Revised.

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Adaptive designs and platform designs are among two common clinical trial innovations that are increasingly being used to manage medical intervention portfolios and attain faster regulatory approvals. Planning of adaptive and platform trials necessitate simulations to understand how a set of adaptation rules will likely affect the properties of the trial. Clinical trial simulations, however, remain a black box to many clinical trials researchers who are not statisticians.

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This article reviews important considerations for researchers who are designing adaptive clinical trials. These differ from conventional clinical trials because they allow and even enforce continual modifications to key components of trial design while data are being collected. This innovative approach has the potential to reduce resource use, decrease time to trial completion, limit allocation of participants to inferior interventions, and improve the likelihood that trial results will be scientifically or clinically relevant.

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HAE1, a high-affinity anti-IgE monoclonal antibody, is discussed here as a case study in the use of quantitative pharmacology in the development of a second-generation molecule. In vitro, preclinical, and clinical data from the first-generation molecule, omalizumab, were heavily leveraged in the HAE1 program. A preliminary mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model for HAE1 was developed using an existing model for omalizumab, together with in vitro binding data for HAE1 and omalizumab.

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Objectives: To explore whether the predictive power of mid-life ECG abnormalities and conventional cardiovascular risk factors for future stroke change over a 30-year follow-up period, and whether a repeated examination improves their predictive power.

Design And Setting: Longitudinal population-based study.

Participants: 2,322 men aged 50 years, with a follow-up period of 30 years.

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