Publications by authors named "N A Haug"

Single-dose doxycycline after high-risk tick bites can prevent Lyme disease, which disproportionately affects children. We described single-dose doxycycline dispensings in an outpatient cohort in the United States. During 2010-2020, a total of 427 105 patients received ≥1 dispensing(s); most were aged ≥65 years.

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There are no clear guidelines regarding the optimal treatment sequence for advanced pancreatic cancer, as head-to-head phase III randomised trials are missing. We assess real-world effectiveness of three common sequential treatment strategies by emulating a hypothetical randomised trial. This analysis included 1551 patients with advanced pancreatic cancer from the prospective, clinical cohort study Tumour Registry Pancreatic Cancer receiving FOLFIRINOX (n = 613) or gemcitabine/nab-paclitaxel (GEMNAB; n = 938) as palliative first-line treatment.

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Background: Data regarding long-term outcomes of catheter-directed thrombolysis (CDT) post intermediate risk pulmonary embolism (PE), the choice of anticoagulation, and factors affecting mortality are not well studied.

Methods: We conducted a ten-year retrospective observational chart review of patients undergoing CDT for intermediate-risk PE. Patients were followed for a period of 1 to a maximum of 5 years from the PE event.

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Purpose: Many studies on cancer patients investigate the impact of treatment on health-related quality of life (QoL). Typically, QoL is measured longitudinally, at baseline and at predefined timepoints thereafter. The question is whether, at a given timepoint, patients who return their questionnaire (available cases, AC) have a different QoL than those who do not return their questionnaire (non-AC).

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In computational neuroscience, hypotheses are often formulated as bottom-up mechanistic models of the systems in question, consisting of differential equations that can be numerically integrated forward in time. Candidate models can then be validated by comparison against experimental data. The model outputs of neural network models depend on both neuron parameters, connectivity parameters and other model inputs.

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