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Coming theses from other universities

  • Exploring Perceptions of Route Environments in Relation to Walking Author: Dan Andersson Link: http://urn.kb.se/resolve?urn=urn:nbn:se:gih:diva-8074 Publication date: 2024-01-31 14:39

    Background: Every walk takes place in a route environment, which can play an important role in deterring or facilitating walking. The focus of this thesis is on the perceptions of environmental variables, and how they relate to appraisals of route environments as hindering – stimulating for walking and unsafe – safe for reasons of traffic, in two metropolitan environments. Another focus is to expand the state of knowledge concerning the criterion-related validity of the Active Commuting Route Environment Scale (ACRES).

    Methods: Commuting pedestrians in Greater Stockholm, Sweden, were recruited via advertisements. From the inner urban area there were 294 participants (77% women), aged 49.5 years, and from the suburban areas there were 233 participants (82% women), aged 50.0 years. 77 individuals walked in both areas. The participants evaluated their commuting route environments using the ACRES. Correlation, multiple regression, and mediation analyses were used to explore the relationships between the variables. Comparisons of environmental ratings between groups and settings were performed with t-tests. Studies 1 and 2 focused on the inner urban area and studies 3 and 4 on the suburban areas. Studies 1 and 3 focused exclusively on the relations between the four motorized traffic variables (vehicle speed, vehicle flow, noise, and exhaust fumes), and their relations to the outcome variables (hinders – stimulates walking and unsafe – safe traffic). Studies 2 and 4 utilised proxies from studies 1 and 3 and combined them with other environmental variables to further the understanding of route environmental variables in relation to walking.

    Results: In both areas, aesthetics and greenery were positively related to stimulating walking, whereas noise, a proxy for motorized traffic, was negatively related. Aesthetics was also positively related to unsafe – safe traffic in the inner urban area, whereas greenery had the corresponding role in suburbia. Another important finding was that greenery also influenced aesthetics positively in both areas. Thus, greenery had both a direct and an indirect positive effect. On the other hand, noise influenced aesthetics negatively in the inner urban area, whereas vehicle flow had the corresponding role in suburbia. A number of variables conjointly influenced the outcome unsafe – safe traffic negatively in both areas (speeds of motor vehicles, noise, conflicts, congestion: pedestrians, red lights, and course of the route). The route environment profiles differed distinctly between the two areas.

    Conclusions: Several route environmental variables appear to be particularly influential in relation to pedestrian commuting, e.g., aesthetics, greenery, and noise. An important finding is that both positive and negative interactions, between certain predictor variables, were disclosed. The contrasting route environment profiles in the different settings strengthen the criterion-related validity of the ACRES. The findings expands the state of knowledge concerning the relations between the environment and walking. If implemented, these findings can influence public health positively.

  • The epidemiology of risk factors and short- and long-term outcome in the Swedish intensive care cohort Author: Björn Ahlström Link: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-519461 Publication date: 2024-01-31 12:00

    The sepsis syndrome is present in ¼ to ⅓ of patients in intensive care units (ICUs) worldwide. The short-term prognosis is grim, with a 30-day mortality of 30–35%; however, the long- term outcomes are now being explored, as multi-professional follow-up after ICU care is increasingly being implemented. In 2020 the first and second waves of another severe infection, the Coronavirus disease 2019 (Covid-19) hit Sweden. The number of ICU beds were scaled up by several hundred percent while we simultaneously tried to understand the disease. Reports on risk factors for adverse outcomes in Covid-19 started to appear, but we needed to know more. Thus, we initiated this project aiming at assessing sepsis as an independent risk factor for later morbidity and mortality. Subsequently, with the onset of the pandemic, our focus shifted to identifying risk factors for adverse outcomes in Covid-19 and describing the functional recovery after severe Covid-19. We used the Swedish Intensive Care Registry and several governmental registries to this end.

    In Cox regression, we compared one-year ICU sepsis survivors without previous dementia with ICU patients without sepsis, finding no increased risk of dementia during follow- up. In a similar cohort, we assessed the impact of sepsis on long-term mortality and causes of death in a series of Cox and multinomial models. We found a surprisingly small overall association between sepsis and mortality and a persistently increased risk of infectious causes of death in sepsis patients. We compared the prevalence of several common comorbidities and medications as risk factors for ICU admission and mortality in ICU patients with Covid-19 with that of age- and sex-matched population controls and in patients discharged alive with those that were deceased at discharge. We found associations between several comorbidities and medications with these adverse outcomes. To better understand the meaning of these comorbidities as risk factors for short-term mortality, we compared them in logistic regression models on patients with Covid-19, sepsis and acute respiratory distress syndrome (ARDS). We found very similar impacts from the comorbidities; however, greater age was more associated with mortality in Covid-19 than in either sepsis or ARDS. Finally, we investigated the long-term functional recovery in ICU patients with Covid-19 compared to hospital-admitted patients with Covid-19 and population controls matched to the ICU group. The ICU patients had a markedly impeded recovery that was not explained by demographics or comorbidities in statistical models.

  • Garnishing the smorgasbord of pharmacometric methods Author: Henrik Bjugård Nyberg Link: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-518178 Publication date: 2024-01-25 11:56

    The smorgasbord of methods that we use within the field of pharmacometrics has developed steadily over several decades and is now a well-laid-out buffet. This thesis adds some garnish to the table in the form of small improvements to the handling of certain problems.

    The first problem tackled by the thesis was the challenge of saddle points and local non-identifiability when estimating pharmacometric model parameters. Substituting the common method of randomly perturbing the initial parameter estimates with one saddle-reset step enhances the accuracy of maximum likelihood estimates by overcoming saddle points parameter values, a common issue in nonlinear mixed-effects models. This algorithm, as implemented in the NONMEM software, was applied to various identifiable and nonidentifiable pharmacometric models, showing improved performance over traditional methods.

    Part of the thesis was dedicated to the development of a paediatric pharmacokinetic model for ethionamide, a drug used in treating multidrug-resistant tuberculosis. The resulting model was then used to simulate drug exposure under different dosing regimens, a new dosing regimen for children was proposed. The developed model, and therefore the proposed paediatric dosing regimen, considers factors like maturation of pharmacokinetic pathways and, administration by nasogastric tube, and concurrent rifampicin treatment. The regimen, with some modifications, was adopted in the 2022 update to the World Health Organization operational handbook on tuberculosis.

    Finally, the thesis explored novel model-integrated evidence (MIE) approaches for bioequivalence (BE) determination. Such methods could offer more robust alternatives to standard BE approached using non-compartmental analysis (NCA). Model-based methods have been shown to be advantageous in sparse data situations, such as is found in studies of ophthalmic formulations, but have suffered from inflated type I error rates. MIE BE approaches using a single model or using model averaging were presented and shown to control type I error at the nominal level while demonstrating increased power in bioequivalence determination.

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