ORCID Profile
0000-0003-3012-7507
Current Organisations
NHS Lanarkshire
,
University of Glasgow
,
University Of Strathclyde
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Publisher: American Medical Association (AMA)
Date: 08-02-2022
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 07-2022
Publisher: Elsevier BV
Date: 08-2022
Publisher: Wiley
Date: 21-07-2022
DOI: 10.1111/RESP.14325
Abstract: Asthma and chronic obstructive pulmonary disease (COPD) are two prevalent and complex diseases that require personalized management. Although a strategy based on treatable traits (TTs) has been proposed, the prevalence and relationship of TTs to the diagnostic label and disease severity established by the attending physician in a real‐world setting are unknown. We assessed how the presence/absence of specific TTs relate to the diagnosis and severity of ‘asthma’, ‘COPD’ or ‘asthma + COPD’. The authors selected 30 frequently occurring TTs from the NOVELTY study cohort (NOVEL observational longiTudinal studY NCT02760329), a large ( n = 11,226), global study that systematically collects data in a real‐world setting, both in primary care clinics and specialized centres, for patients with ‘asthma’ ( n = 5932, 52.8%), ‘COPD’ ( n = 3898, 34.7%) or both (‘asthma + COPD’ n = 1396, 12.4%). The results indicate that (1) the prevalence of the 30 TTs evaluated varied widely, with a mean ± SD of 4.6 ± 2.6, 5.4 ± 2.6 and 6.4 ± 2.8 TTs atient in those with ‘asthma’, ‘COPD’ and ‘asthma + COPD’, respectively ( p 0.0001) (2) there were no large global geographical variations, but the prevalence of TTs was different in primary versus specialized clinics (3) several TTs were specific to the diagnosis and severity of disease, but many were not and (4) both the presence and absence of TTs formed a pattern that is recognized by clinicians to establish a diagnosis and grade its severity. These results provide the largest and most granular characterization of TTs in patients with airway diseases in a real‐world setting to date.
Publisher: Elsevier BV
Date: 08-2022
DOI: 10.1016/J.RMED.2022.106863
Abstract: Patients with mild asthma represent a substantial proportion of the population with asthma, yet there are limited data on their true burden of disease. We aimed to describe the clinical and healthcare resource utilisation (HCRU) burden of physician-assessed mild asthma. Patients with mild asthma were included from the NOVEL observational longiTudinal studY (NOVELTY NCT02760329), a global, 3-year, real-world prospective study of patients with asthma and/or chronic obstructive pulmonary disease from community practice (specialised and primary care). Diagnosis and severity were based on physician discretion. Clinical burden included physician-reported exacerbations and patient-reported measures. HCRU included inpatient and outpatient visits. Overall, 2004 patients with mild asthma were included 22.8% experienced ≥1 exacerbation in the previous 12 months, of whom 72.3% experienced ≥1 severe exacerbation. Of 625 exacerbations reported, 48.0% lasted >1 week, 27.7% were preceded by symptomatic worsening lasting >3 days, and 50.1% required oral corticosteroid treatment. Health status was moderately impacted (St George's Respiratory Questionnaire score: 23.5 [standard deviation ± 17.9]). At baseline, 29.7% of patients had asthma symptoms that were not well controlled or very poorly controlled (Asthma Control Test score <20), increasing to 55.6% for those with ≥2 exacerbations in the previous year. In terms of HCRU, at least one unscheduled ambulatory visit for exacerbations was required by 9.5% of patients, including 9.2% requiring ≥1 emergency department visit and 1.1% requiring ≥1 hospital admission. In this global s le representing community practice, a significant proportion of patients with physician-assessed mild asthma had considerable clinical burden and HCRU.
Publisher: Springer Science and Business Media LLC
Date: 28-07-2022
DOI: 10.1186/S12966-022-01333-W
Abstract: The number of in iduals recovering from severe COVID-19 is increasing rapidly. However, little is known about physical behaviours that make up the 24-h cycle within these in iduals. This study aimed to describe physical behaviours following hospital admission for COVID-19 at eight months post-discharge including associations with acute illness severity and ongoing symptoms. One thousand seventy-seven patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and in iduals with type 2 diabetes were comparators. Valid accelerometer data from 253 women and 462 men were included. Women engaged in a mean ± SD of 14.9 ± 14.7 min/day of moderate-to-vigorous physical activity (MVPA), with 12.1 ± 1.7 h/day spent inactive and 7.2 ± 1.1 h/day asleep. The values for men were 21.0 ± 22.3 and 12.6 ± 1.7 h /day and 6.9 ± 1.1 h/day, respectively. Over 60% of women and men did not have any days containing a 30-min bout of MVPA. Variability in sleep timing was approximately 2 h in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer total sleep time, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes. Those recovering from a hospital admission for COVID-19 have low levels of physical activity and disrupted patterns of sleep several months after discharge. Our comparative cohorts indicate that the long-term impact of COVID-19 on physical behaviours is significant.
Publisher: Massachusetts Medical Society
Date: 19-07-2100
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 10-2020
Publisher: European Respiratory Society (ERS)
Date: 26-11-2020
DOI: 10.1183/23120541.00828-2020
Abstract: The Respiratory Symptoms Questionnaire (RSQ) is a novel, four-item patient-reported diagnosis-agnostic tool designed to assess the frequency of respiratory symptoms and their impact on activity, without specifying a particular diagnosis. Our objective was to examine its validity in patients with asthma and/or chronic obstructive pulmonary disease (COPD). Baseline data were randomly s led from patients who completed the RSQ in the NOVELTY study ( ClinicalTrials.gov : NCT02760329 ). The total s le (n=1530) comprised three randomly selected s les (n=510 each) from each physician-assigned diagnostic group (asthma, asthma+COPD and COPD). The internal consistency and structural validity of the RSQ were evaluated using exploratory and confirmatory factor analyses psychometric performance was observed using Classical Test Theory and Item Response Theory analyses. For the total s le, the mean± sd RSQ score was 5.6±4.3 (range 0–16). Irrespective of diagnosis, the internal consistency of items was uniformly adequate (Cronbach's α=0.76–0.80). All items had high factor loadings and structural characteristics of the measure were invariant across groups. Using the total s le, RSQ items informatively covered the θ score range of –2.0 to 2.8, with discrimination coefficients for in idual items being high to very high (1.7–2.6). Strong convergent correlations were observed between the RSQ and the St George's Respiratory Questionnaire (0.77, p .001). The RSQ is a valid, brief, patient-reported tool for assessing respiratory symptoms in patients across the whole spectrum of asthma and/or COPD, rather than using different questionnaires for each diagnosis. It can be used for monitoring respiratory symptoms in clinical practice, clinical trials and real-world studies.
Publisher: Elsevier BV
Date: 05-2021
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 05-2021
Publisher: Elsevier BV
Date: 11-2021
Publisher: American Thoracic Society
Date: 15-03-2023
Publisher: Massachusetts Medical Society
Date: 25-02-2021
Publisher: Wiley
Date: 17-02-2023
DOI: 10.1002/JMRI.28643
Abstract: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton ( 1 H)‐MRI lung segmentation. However, previous deep learning studies have utilized single‐center data and limited acquisition parameters. Develop a generalizable CNN for lung segmentation in 1 H‐MRI, robust to pathology, acquisition protocol, vendor, and center. Retrospective. A total of 809 1 H‐MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6–85) 42% females) and 31 healthy participants (median age (range): 34 (23–76) 34% females) that were split into training (593 scans (74%) 157 participants (55%)), testing (50 scans (6%) 50 participants (17%)) and external validation (164 scans (20%) 82 participants (28%)) sets. 1.5‐T and 3‐T / 3D spoiled‐gradient recalled and ultrashort echo‐time 1 H‐MRI . 2D and 3D CNNs, trained on single‐center, multi‐sequence data, and the conventional spatial fuzzy c‐means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance. Kruskal–Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland–Altman analyses assessed agreement with manually derived lung volumes. A P value of .05 was considered statistically significant. The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880–0.987), Average HD of 1.63 mm (0.65–5.45) and XOR of 0.079 (0.025–0.240) on the testing set and a DSC of 0.973 (0.866–0.987), Average HD of 1.11 mm (0.47–8.13) and XOR of 0.054 (0.026–0.255) on external validation data. The 3D CNN generated accurate 1 H‐MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center. 4. Stage 1.
Publisher: European Respiratory Society (ERS)
Date: 25-02-2021
DOI: 10.1183/13993003.03927-2020
Abstract: Studies of asthma and chronic obstructive pulmonary disease (COPD) typically focus on these diagnoses separately, limiting understanding of disease mechanisms and treatment options. NOVELTY is a global, 3-year, prospective observational study of patients with asthma and/or COPD from real-world clinical practice. We investigated heterogeneity and overlap by diagnosis and severity in this cohort. Patients with physician-assigned asthma, COPD or both (asthma+COPD) were enrolled, and stratified by diagnosis and severity. Baseline characteristics were reported descriptively by physician-assigned diagnosis and/or severity. Factors associated with physician-assessed severity were evaluated using ordinal logistic regression analysis. Of 11 243 patients, 5940 (52.8%) had physician-assigned asthma, 1396 (12.4%) had asthma+COPD and 3907 (34.8%) had COPD almost half were from primary care. Symptoms, health-related quality of life and spirometry showed substantial heterogeneity and overlap between asthma, asthma+COPD and COPD, with 23%, 62% and 64% of patients, respectively, having a ratio of post-bronchodilator forced expiratory volume in 1 s to forced vital capacity below the lower limit of normal. Symptoms and exacerbations increased with greater physician-assessed severity and were higher in asthma+COPD. However, 24.3% with mild asthma and 20.4% with mild COPD had experienced ≥1 exacerbation in the past 12 months. Medication records suggested both under-treatment and over-treatment relative to severity. Blood eosinophil counts varied little across diagnosis and severity groups, but blood neutrophil counts increased with severity across all diagnoses. This analysis demonstrates marked heterogeneity within, and overlap between, physician-assigned diagnosis and severity groups in patients with asthma and/or COPD. Current diagnostic and severity classifications in clinical practice poorly differentiate between clinical phenotypes that may have specific risks and treatment implications.
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 2023
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Manish Patel.