The Use of Objective Data to Assess Activity and Participation Prior to and Following Critical Illness

This thesis is composed of five distinct chapters that investigate the feasibility of using smartphone data to define activity and participation in patients who have suffered critical illness. Specifically the thesis investigates the current state of play with regards to outcome measurement following critical illness; explores how others have used objective activity data to monitor survivors of critical illness;, investigates the ownership of smartphones and the data available on these devices amongst Intensive Care Unit (ICU) survivors; demonstrates the accuracy of the step data collected by a smartphone; and explores the use of a dedicated smartphone app to monitor patient activity and participation. The thesis comprises 6 distinct manuscripts. Survival of critical illness frequently leads to the development of Post Intensive Care Syndrome (PICS). PICS is the new or worsening of cognitive, psychological and/or physical function that persists following hospital discharge in patients who have suffered critical illness. While PICS leads to disability its measurement is challenging, often relying on surveys that lack construct validity in survivors of critical illness (Chapter 1.1). Objective measurement of activity following critical illness has been investigated using wearable devices, but not smartphones, that are becoming ubiquitous in modern day life (Chapter 1.2). We investigated smartphone ownership amongst ICU survivors and were able to obtain step and location data from a minority of these phones using manual techniques (Chapter 2.2). These patients were followed up (Chapter 2.3) at 3 and 6 months following ICU discharge. This study demonstrates that the step data collected from smartphones appears to be accurate when compared to a dedicated wearable device. We were able to show that the location data obtained from smartphones could be used to demonstrate elements of physical participation such as time spent at home, distance traveled and the extent of travel in activity spaces (Chapter 2.4). However, the manual extraction of these data was time consuming, relying on the use of obtaining Global Position System (GPS) data from screenshots of patients’ phones. In 2015 Google Maps released a function that allowed the download of a single file that contained an individual’s whole location history. We explored the availability of this data in patients admitted under general medicine (Chapter 3.2). Although the data extraction was more efficient and the analysis could be automated, the data were only available on a minority of devices. Due to the inefficiencies associated with smartphone data extraction, we examined the smartphone user ability in patients receiving renal dialysis (Chapter 4.2). This demonstrated that the majority of smartphone owning patients do have the user ability, or immediate access to assistance to install a smartphone app. The development of a custom-built smartphone app in collaboration with the Software Engineering department of the University of Adelaide allowed the testing of a smartphone app to collect Step and GPS data in patients undergoing Cardiothoracic Surgery. The data generated by the app showed great promise in being able to monitor patient’s recovery remotely and link this back to the same pre-morbid metrics, However, the technical failures of the app provide excellent learning opportunities for future studies.Thesis (Ph.D.) -- University of Adelaide, Adelaide Medical School, 202

Higher twists and αs(MZ)\alpha_s(M_Z) extractions from the NNLO QCD analysis of the CCFR data for xF3xF_3 structure function

A detailed next-to-next-to-leading order (NNLO) QCD analysis is performed for the experimental data of the CCFR collaboration for the $xF_3$ structure function. Theoretical ambiguities of the results of our NNLO fits are estimated by application of the Pad\'e resummation technique and variation of the factorization and renormalization scales. The NNLO and N$^3$LO $\alpha_s(Q^2)$ $\bar{MS}$-matching conditions are used. In the process of the fits we are taking into account of twist-4 $1/Q^2$-terms. We found that the amplitude of the $x$-shape of the twist-4 factor is decreasing in NLO and NNLO, though some remaining twist-4 structure seems to retain in NNLO in the case when statistical uncertainties are taken into account. The question of the stability of these results to the application of the [0/2] Pad\'e resummation technique is considered. Our NNLO results for $\alpha_s(M_Z)$ values, extracted from the CCFR $xF_3$ data, are $\alpha_s(M_Z)=0.118 \pm 0.002 (stat) \pm 0.005 (syst)\pm 0.003 (theory)$ provided the twist-4 contributions are fixed through the infrared renormalon model and $\alpha_s(M_Z)=0.121^{+0.007}_{0.010}(stat)\pm 0.005 (syst) \pm 0.003 (theory)$ provided the twist-4 terms are considered as free parameters.Comment: 33 pages LaTeX, 3 ps figures; minor misprints are eliminated, 2 new referencies are added; accepted for publication in Nucl. Phys.

Inclusive Lambda Production in Two-Photon Collisions at LEP

The reactions e^+e^- -> e^+e^- Lambda X and e^+e^- -> e^+e^- Lambda X are studied using data collected at LEP with the L3 detector at centre-of-mass energies between 189 and 209 GeV. Inclusive differential cross sections are measured as a function of the lambda transverse momentum, p_t, and pseudo-rapidity, eta, in the ranges 0.4 GeV < p_t < 2.5 GeV and |\eta| < 1.2. The data are compared to Monte Carlo predictions. The differential cross section as a function of p_t is well described by an exponential of the form A exp (- p_t / )$

Epidemiological and Immunological Features of Obesity and SARS-CoV-2

Obesity is a key correlate of severe SARS-CoV-2 outcomes while the role of obesity on risk of SARS-CoV-2 infection, symptom phenotype, and immune response remain poorly defined. We examined data from a prospective SARS-CoV-2 cohort study to address these questions. Serostatus, body mass index, demographics, comorbidities, and prior COVID-19 compatible symptoms were assessed at baseline and serostatus and symptoms monthly thereafter. SARS-CoV-2 immunoassays included an IgG ELISA targeting the spike RBD, multiarray Luminex targeting 20 viral antigens, pseudovirus neutralization, and T cell ELISPOT assays. Our results from a large prospective SARS-CoV-2 cohort study indicate symptom phenotype is strongly influenced by obesity among younger but not older age groups; we did not identify evidence to suggest obese individuals are at higher risk of SARS-CoV-2 infection; and remarkably homogenous immune activity across BMI categories suggests immune protection across these groups may be similar

Measurement of the Charm Production Cross Section in gamma gamma Collisions at LEP

Open charm production in gamma-gamma collisions is studied with data collected at e+e- centre-of-mass energies from 189 GeV to 202 GeV corresponding to a total integrated luminosity of 410 pb-1. The charm cross section sigma(gamma gamma ---> c c~ X) is measured for the first time as a function of the two-photon centre-of-mass energy in the interval from 5 GeV to 70 GeV and is compared to NLO QCD calculations

SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort

Identifying the potential for Severe Acute Respiratory Syndrome : Coronavirus 2 (SARS-CoV-2) reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4,411 United States employees in 4 states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an odds ratio for reinfection ranging from 0.14 (95% CI: 0.019 to 0.63) to 0.28 (95% CI: 0.05 to 1.1), implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 72% to 86% reduced odds of a subsequent PCR positive test based on our point estimates. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a 6-month time period. We also highlight 2 major sources of bias and uncertainty to be considered when estimating the relative risk of reinfection, confounders, and the choice of baseline time point and show how to account for both in reinfection analysis

Increasing frailty is associated with higher prevalence and reduced recognition of delirium in older hospitalised inpatients: results of a multi-centre study

Purpose: Delirium is a neuropsychiatric disorder delineated by an acute change in cognition, attention, and consciousness. It is common, particularly in older adults, but poorly recognised. Frailty is the accumulation of deficits conferring an increased risk of adverse outcomes. We set out to determine how severity of frailty, as measured using the CFS, affected delirium rates, and recognition in hospitalised older people in the United Kingdom. Methods: Adults over 65 years were included in an observational multi-centre audit across UK hospitals, two prospective rounds, and one retrospective note review. Clinical Frailty Scale (CFS), delirium status, and 30-day outcomes were recorded. Results: The overall prevalence of delirium was 16.3% (483). Patients with delirium were more frail than patients without delirium (median CFS 6 vs 4). The risk of delirium was greater with increasing frailty [OR 2.9 (1.8–4.6) in CFS 4 vs 1–3; OR 12.4 (6.2–24.5) in CFS 8 vs 1–3]. Higher CFS was associated with reduced recognition of delirium (OR of 0.7 (0.3–1.9) in CFS 4 compared to 0.2 (0.1–0.7) in CFS 8). These risks were both independent of age and dementia. Conclusion: We have demonstrated an incremental increase in risk of delirium with increasing frailty. This has important clinical implications, suggesting that frailty may provide a more nuanced measure of vulnerability to delirium and poor outcomes. However, the most frail patients are least likely to have their delirium diagnosed and there is a significant lack of research into the underlying pathophysiology of both of these common geriatric syndromes