ORCID Profile
0000-0003-2707-2779
Current Organisation
The University of Edinburgh
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Publisher: Oxford University Press (OUP)
Date: 20-06-2012
Abstract: Socio-economic differences are a major determinant of perinatal outcomes. The impact of low socio-economic status on the risk of stillbirth, and the association between socio-economic status and stillbirth by maternal country of origin at a national level in Spain are unknown. We aimed to analyse the effect of maternal socio-economic status on the risk of stillbirth by maternal country of origin in Spain for the years 2007 and 2008. We designed a population-based observational study that included 970,740 live births and 2464 stillbirths from 2007 to 2008. Univariate risk ratios (RRs) of stillbirth were calculated by maternal education, country of origin, age, parity, and gestational age. Adjusted stillbirth RRs were calculated using a generalized linear model with the Poisson family. Then, adjusted attributable risks and aetiological fractions in the population were calculated as measures of impact. Stillbirth rate ranged from 1.0 to 4.7 deaths per 1000 births. The stillbirth risk among mothers having secondary or lower education was double than that of mothers with a tertiary education with an adjusted RR of 2.13 [95% confidence interval (CI): 1.74-2.60]. African mothers, compared with mothers from Spain, showed an adjusted stillbirth RR of 1.75 (95% CI: 1.54-2.00). This study confirms the differences of stillbirth risk by maternal socio-economic status. Regardless of socio-economic status, African mothers had the highest risk of stillbirth. These results point out the necessity to reduce factors related to social and health inequalities in perinatal mortality in Spain, and more specifically, to take into consideration the special vulnerability of African mothers.
Publisher: European Respiratory Society (ERS)
Date: 22-12-2022
DOI: 10.1183/23120541.00274-2022
Abstract: Persistence of respiratory symptoms, particularly breathlessness, after acute coronavirus disease 2019 (COVID-19) infection has emerged as a significant clinical problem. We aimed to characterise and identify risk factors for patients with persistent breathlessness following COVID-19 hospitalisation. PHOSP-COVID is a multicentre prospective cohort study of UK adults hospitalised for COVID-19. Clinical data were collected during hospitalisation and at a follow-up visit. Breathlessness was measured by a numeric rating scale of 0–10. We defined post-COVID-19 breathlessness as an increase in score of ≥1 compared to the pre-COVID-19 level. Multivariable logistic regression was used to identify risk factors and to develop a prediction model for post-COVID-19 breathlessness. We included 1226 participants (37% female, median age 59 years, 22% mechanically ventilated). At a median 5 months after discharge, 50% reported post-COVID-19 breathlessness. Risk factors for post-COVID-19 breathlessness were socioeconomic deprivation (adjusted OR 1.67, 95% CI 1.14–2.44), pre-existing depression/anxiety (adjusted OR 1.58, 95% CI 1.06–2.35), female sex (adjusted OR 1.56, 95% CI 1.21–2.00) and admission duration (adjusted OR 1.01, 95% CI 1.00–1.02). Black ethnicity (adjusted OR 0.56, 95% CI 0.35–0.89) and older age groups (adjusted OR 0.31, 95% CI 0.14–0.66) were less likely to report post-COVID-19 breathlessness. Post-COVID-19 breathlessness was associated with worse performance on the shuttle walk test and forced vital capacity, but not with obstructive airflow limitation. The prediction model had fair discrimination (concordance statistic 0.66, 95% CI 0.63–0.69) and good calibration (calibration slope 1.00, 95% CI 0.80–1.21). Post-COVID-19 breathlessness was commonly reported in this national cohort of patients hospitalised for COVID-19 and is likely to be a multifactorial problem with physical and emotional components.
Publisher: National Institute for Health and Care Research
Date: 12-2022
DOI: 10.3310/EQAB4594
Abstract: A previous National Institute for Health and Care Research study [Harrison DA, Ferrando-Vivas P, Shahin J, Rowan KM. Ensuring comparisons of health-care providers are fair: development and validation of risk prediction models for critically ill patients. Health Serv Deliv Res 2015 3 (41)] identified the need for more research to understand risk factors and consequences of critical care and subsequent outcomes. First, to improve risk models for adult general critical care by developing models for mortality at fixed time points and time-to-event outcomes, end-stage renal disease, type 2 diabetes, health-care utilisation and costs. Second, to improve risk models for cardiothoracic critical care by enhancing risk factor data and developing models for longer-term mortality. Third, to improve risk models for in-hospital cardiac arrest by enhancing risk factor data and developing models for longer-term mortality and critical care utilisation. Risk modelling study linking existing data. NHS adult critical care units and acute hospitals in England. Patients admitted to an adult critical care unit or experiencing an in-hospital cardiac arrest. None. Mortality at hospital discharge, 30 days, 90 days and 1 year following critical care unit admission mortality at 1 year following discharge from acute hospital new diagnosis of end-stage renal disease or type 2 diabetes hospital resource use and costs return of spontaneous circulation sustained for 20 minutes survival to hospital discharge and 1 year and length of stay in critical care following in-hospital cardiac arrest. Case Mix Programme, National Cardiac Arrest Audit, UK Renal Registry, National Diabetes Audit, National Adult Cardiac Surgery Audit, Hospital Episode Statistics and Office for National Statistics. Data were linked for 965,576 critical care admissions between 1 April 2009 and 31 March 2016, and 83,939 in-hospital cardiac arrests between 1 April 2011 and 31 March 2016. For admissions to adult critical care units, models for 30-day mortality had similar predictors and performance to those for hospital mortality and did not reduce heterogeneity. Models for longer-term outcomes reflected increasing importance of chronic over acute predictors. New models for end-stage renal disease and diabetes will allow benchmarking of critical care units against these important outcomes and identification of patients requiring enhanced follow-up. The strongest predictors of health-care costs were prior hospitalisation, prior dependency and chronic conditions. Adding pre- and intra-operative risk factors to models for cardiothoracic critical care gave little improvement in performance. Adding comorbidities to models for in-hospital cardiac arrest provided modest improvements but were of greater importance for longer-term outcomes. Delays in obtaining linked data resulted in the data used being 5 years old at the point of publication: models will already require recalibration. Data linkage provided enhancements to the risk models underpinning national clinical audits in the form of additional predictors and novel outcomes measures. The new models developed in this report may assist in providing objective estimates of potential outcomes to patients and their families. (1) Develop and test care pathways for recovery following critical illness targeted at those with the greatest need (2) explore other relevant data sources for longer-term outcomes (3) widen data linkage for resource use and costs to primary care, outpatient and emergency department data. This study is registered as NCT02454257. This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in full in Health and Social Care Delivery Research Vol. 10, No. 39. See the NIHR Journals Library website for further project information.
Publisher: Springer Science and Business Media LLC
Date: 18-07-2018
Publisher: BMJ
Date: 24-05-2023
Publisher: Cold Spring Harbor Laboratory
Date: 14-12-2022
DOI: 10.1101/2022.12.13.22283391
Abstract: Sleep disturbance is common following hospitalisation both for COVID-19 and other causes. The clinical associations are poorly understood, despite it altering pathophysiology in other scenarios. We, therefore, investigated whether sleep disturbance is associated with dyspnoea along with relevant mediation pathways. Sleep parameters were assessed in a prospective cohort of patients (n=2,468) hospitalised for COVID-19 in the United Kingdom in 39 centres using both subjective and device-based measures. Results were compared to a matched UK biobank cohort and associations were evaluated using multivariable linear regression. 64% (456/714) of participants reported poor sleep quality 56% felt their sleep quality had deteriorated for at least 1-year following hospitalisation. Compared to the matched cohort, both sleep regularity (44.5 vs 59.2, p .001) and sleep efficiency (85.4% vs 88.5%, p .001) were lower whilst sleep period duration was longer (8.25h vs 7.32h, p .001). Overall sleep quality (effect estimate 4.2 (3.0–5.5)), deterioration in sleep quality following hospitalisation (effect estimate 3.2 (2.0–4.5)), and sleep regularity (effect estimate 5.9 (3.7–8.1)) were associated with both dyspnoea and impaired lung function (FEV 1 and FVC). Depending on the sleep metric, anxiety mediated 13–42% of the effect of sleep disturbance on dyspnoea and muscle weakness mediated 29-43% of this effect. Sleep disturbance is associated with dyspnoea, anxiety and muscle weakness following COVID-19 hospitalisation. It could have similar effects for other causes of hospitalisation where sleep disturbance is prevalent. UK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council.
Publisher: Cold Spring Harbor Laboratory
Date: 11-05-2023
DOI: 10.1101/2023.05.08.23289442
Abstract: PHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged. PHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials. Data collected covered a wide range of physical measures, biological s les, and Patient Reported Outcome Measures (PROMs). Participants could join the cohort either in Tier 1 only with remote data collection using hospital records, a PROMs app and postal saliva s le for DNA, or in Tier 2 where they were invited to attend two specific research visits for further data collection and biological research s ling. These research visits occurred at five (range 2-7) months and 12 (range 10-14) months post-discharge. Participants could also participate in specific nested studies (Tier 3) at selected sites. All participants were asked to consent to further follow-up for 25 years via linkage to their electronic healthcare records and to be re-contacted for further research. In total, 7935 participants were recruited from 83 UK sites: 5238 to Tier 1 and 2697 to Tier 2, between August 2020 and March 2022. Cohort data are held in a Trusted Research Environment and s les stored in a central biobank. Data and s les can be accessed upon request and subject to approvals.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Nazir I Lone.