Browsing by Person "Lone, Nazir"

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Determinants of Health-Related Quality of Life After ICU: Importance of Patient Demographics, Previous Comorbidity, and Severity of Illness.
(2018-04-01) Griffith, David M.; Salisbury, Lisa; Lee, Robert J.; Lone, Nazir; Merriweather, Judith L.; Walsh, Timothy S.
ICU survivors frequently report reduced health-related quality of life, but the relative importance of preillness versus acute illness factors in survivor populations is not well understood. We aimed to explore health-related quality of life trajectories over 12 months following ICU discharge, patterns of improvement, or deterioration over this period, and the relative importance of demographics (age, gender, social deprivation), preexisting health (Functional Comorbidity Index), and acute illness severity (Acute Physiology and Chronic Health Evaluation II score, ventilation days) as determinants of health-related quality of life and relevant patient-reported symptoms during the year following ICU discharge. Nested cohort study within a previously published randomized controlled trial. Two ICUs in Edinburgh, Scotland. Adult ICU survivors (n = 240) who required more than 48 hours of mechanical ventilation. None. We prospectively collected data for age, gender, social deprivation (Scottish index of multiple deprivation), preexisting comorbidity (Functional Comorbidity Index), Acute Physiology and Chronic Health Evaluation II score, and days of mechanical ventilation. Health-related quality of life (Medical Outcomes Study Short Form version 2 Physical Component Score and Mental Component Score) and patient-reported symptoms (appetite, fatigue, pain, joint stiffness, and breathlessness) were measured at 3, 6, and 12 months. Mean Physical Component Score and Mental Component Score were reduced at all time points with minimal change between 3 and 12 months. In multivariable analysis, increasing pre-ICU comorbidity count was strongly associated with lower health-related quality of life (Physical Component Score _ = -1.56 [-2.44 to -0.68]; p = 0.001; Mental Component Score _ = -1.45 [-2.37 to -0.53]; p = 0.002) and more severe self-reported symptoms. In contrast, Acute Physiology and Chronic Health Evaluation II score and mechanical ventilation days were not associated with health-related quality of life. Older age (_ = 0.33 [0.19-0.47]; p < 0.001) and lower social deprivation (_ = 1.38 [0.03-2.74]; p = 0.045) were associated with better Mental Component Score health-related quality of life. Preexisting comorbidity counts, but not severity of ICU illness, are strongly associated with health-related quality of life and physical symptoms in the year following critical illness.
Polypharmacy and emergency readmission to hospital after critical illness: A population-level cohort study
(Elsevier, 2020-10-31) Turnbull, Angus J.; Donaghy, Eddie; Salisbury, Lisa; Ramsay, Pamela; Rattray, Janice; Walsh, Timothy; Lone, Nazir
Polypharmacy is common and closely linked to drug interactions. The impact of polypharmacy has not been previously quantified in survivors of critical illness who have reduced resilience to stressors. Our aim was to identify factors associated with preadmission polypharmacy and ascertain whether polypharmacy is an independent risk factor for emergency readmission to hospital after discharge from a critical illness. A population-wide cohort study consisting of patients admitted to all Scottish general ICUs between January 1, 2011 and December 31, 2013, whom survived their ICU stay. Patients were stratified by presence of preadmission polypharmacy, defined as being prescribed five or more regular medications. The primary outcome was emergency hospital readmission within 1 yr of discharge from index hospital stay. Of 23 844 ICU patients, 29.9% were identified with polypharmacy (n=7138). Factors associated with polypharmacy included female sex, increasing age, and social deprivation. Emergency 1-yr hospital readmission was significantly higher in the polypharmacy cohort (51.8% vs 35.8%, P<0.001). After confounder adjustment, patients with polypharmacy had a 22% higher hazard of emergency 1-yr readmission (adjusted hazard ratio 1.22, 95% confidence interval 1.16-1.28, P<0.001). On a linear scale of polypharmacy each additional prescription conferred a 3% increase in hazard of emergency readmission by 1 yr (adjusted hazard ratio 1.03, 95% confidence interval 1.02-1.03, P<0.001). This national cohort study of ICU survivors demonstrates that preadmission polypharmacy is an independent risk factor for emergency readmission. In an ever-growing era of polypharmacy, this risk factor may represent a substantial burden in the at-risk post-intensive care population.
Predicting risk of unplanned hospital readmission in survivors of critical illness: A population-level cohort study
(2018-04-06) Lone, Nazir; Lee, Robert J.; Salisbury, Lisa; Donaghy, Eddie; Ramsay, Pamela; Rattray, Janice; Walsh, Timothy S.
Background Intensive care unit (ICU) survivors experience high levels of morbidity after hospital discharge and are at high risk of unplanned hospital readmission. Identifying those at highest risk before hospital discharge may allow targeting of novel risk reduction strategies. We aimed to identify risk factors for unplanned 90-day readmission, develop a risk prediction model and assess its performance to screen for ICU survivors at highest readmission risk. Methods Population cohort study linking registry data for patients discharged from general ICUs in Scotland (2005-2013). Independent risk factors for 90-day readmission and discriminant ability (c-index) of groups of variables were identified using multivariable logistic regression. Derivation and validation risk prediction models were constructed using a time-based split. Results Of 55 975 ICU survivors, 24.1% (95%CI 23.7% to 24.4%) had unplanned 90-day readmission. Pre-existing health factors were fair discriminators of readmission (c-index 0.63, 95%-CI 0.63 to 0.64) but better than acute illness factors (0.60) or demographics (0.54). In a subgroup of those with no comorbidity, acute illness factors (0.62) were better discriminators than pre-existing health factors (0.56). Overall model performance and calibration in the validation cohort was fair (0.65, 95%-CI 0.64 to 0.66) but did not perform sufficiently well as a screening tool, demonstrating high false-positive/false-negative rates at clinically relevant thresholds. Conclusions Unplanned 90-day hospital readmission is common. Pre-existing illness indices are better predictors of readmission than acute illness factors. Identifying additional patient-centred drivers of readmission may improve risk prediction models. Improved understanding of risk factors that are amenable to intervention could improve the clinical and cost-effectiveness of post-ICU care and rehabilitation.
PReventing early unplanned hOspital readmission aFter critical ILlnEss (PROFILE): protocol and analysis framework for a mixed methods study
(2016-06-28) Walsh, Timothy S.; Salisbury, Lisa; Donaghy, Eddie; Ramsay, Pamela; Lee, Robert J.; Rattray, Janice; Lone, Nazir
Introduction: Survivors of critical illness experience multidimensional disabilities that reduce quality of life, and 25-30% require unplanned hospital readmission within 3 months following index hospitalisation. We aim to understand factors associated with unplanned readmission; develop a risk model to identify intensive care unit (ICU) survivors at highest readmission risk; understand the modifiable and non-modifiable readmission drivers; and develop a risk assessment tool for identifying patients and areas for early intervention. Methods and analysis: We will use mixed methods with concurrent data collection. Quantitative data will comprise linked healthcare records for adult Scottish residents requiring ICU admission (1 January 2000-31 December 2013) who survived to hospital discharge. The outcome will be unplanned emergency readmission within 90 days of index hospital discharge. Exposures will include pre-ICU demographic data, comorbidities and health status, and critical illness variables representing illness severity. Regression analyses will be used to identify factors associated with increased readmission risk, and to develop and validate a risk prediction model. Qualitative data will comprise recorded/transcribed interviews with up to 60 patients and carers recently experiencing unplanned readmissions in three health board regions. A deductive and inductive thematic analysis will be used to identify factors contributing to readmissions and how they may interact. Through iterative triangulation of quantitative and qualitative data, we will develop a construct/ taxonomy that captures reasons and drivers for unplanned readmission. We will validate and further refine this in focus groups with patients/carers who experienced readmissions in six Scottish health board regions, and in consultation with an independent expert group. A tool will be developed to screen for ICU survivors at risk of readmission and inform anticipatory interventions.
The Burden of Specific Symptoms Reported by Survivors after Critical Illness
(2018-01-15) Griffith, David M.; Salisbury, Lisa; Lee, Robert J.; Lone, Nazir; Merriweather, Judith L.; Walsh, Timothy S.