Immunocompromised individuals are not optimally protected by COVID-19 vaccines and potentially require additional preventive interventions to mitigate the risk of severe COVID-19. We aimed to characterise and describe the risk of severe COVID-19 across immunocompromised groups as the pandemic began to transition to an endemic phase.
To evaluate whether polypharmacy is associated with treatment response and serious adverse events (SAEs) in patients with RA using data from the British Society for Rheumatology Biologics Register (BSRBR-RA).The BSRBR-RA is a prospective observational cohort study of biologic therapy starters and a DMARD comparator arm. A logistic regression model was used to calculate the odds of a EULAR 'good response' after 12 months of biologic therapy by medication count. Cox proportional hazards models were used to identify risk of SAEs. The utility of the models were compared with the Rheumatic Disease Comorbidity Index using Receiver Operator Characteristic and Harrell's C statistic.The analysis included 22 005 patients, of which 83% were initiated on biologics. Each additional medication reduced the odds of a EULAR good response by 8% [odds ratios 0.92 (95% CI 0.91, 0.93) P < 0.001] and 3% in the adjusted model [adjusted odds ratios 0.97 (95% CI 0.95, 0.98) P < 0.001]. The Receiver Operator Characteristic demonstrated significantly greater areas under the curve with the polypharmacy model than the Rheumatic Disease Comorbidity Index. There were 12 547 SAEs reported in 7286 patients. Each additional medication equated to a 13% increased risk of an SAE [hazard ratio 1.13 (95% CI 1.12, 1.13) P < 0.001] and 6% in the adjusted model [adjusted hazard ratio 1.06 (95% CI 1.05, 1.07) P < 0.001]. Predictive values for SAEs were comparable between the polypharmacy and Rheumatic Disease Comorbidity Index model.Polypharmacy is a simple but valuable predictor of clinical outcomes in patients with RA. This study supports medication count as a valid measure for use in epidemiologic analyses.
Of the many factors that influence how the word recognition process unfolds, the influence of similarity has received much attention. In this chapter, we consider how visual and auditory word recognition is influenced by phonological and orthographic similarity defined in terms of neighborhood structure. Orthographic neighbors are words that differ by a letter (e.g., bait and bail), whereas phonological neighbors are words that differ by a phoneme (e.g., bait and date). Throughout the chapter, we situate the effect of neighbors within a theoretical framework consisting of interactive activation and competition. We conclude by evaluating recent research indicating that individual differences play a role in the influence of neighbors on word recognition.
Background: The COVID-19 pandemic continues to escalate. There is urgent need to stratify patients. Understanding risk of deterioration will assist in admission and discharge decisions, and help selection for clinical studies to indicate where risk of therapy-related complications is justified. Methods: An observational cohort of patients acutely admitted to two London hospitals with COVID-19 and positive SARS-CoV-2 swab results was assessed. Demographic details, clinical data, comorbidities, blood parameters and chest radiograph severity scores were collected from electronic health records. Endpoints assessed were critical care admission and death. A risk score was developed to predict outcomes. Findings: Analyses included 1,157 patients. Older age, male sex, comorbidities, respiratory rate, oxygenation, radiographic severity, higher neutrophils, higher CRP and lower albumin at presentation predicted critical care admission and mortality. Non-white ethnicity predicted critical care admission but not death. Social deprivation was not predictive of outcome. A risk score was developed incorporating twelve characteristics: age>40, male, non-white ethnicity, oxygen saturations<93%, radiological severity score>3, neutrophil count>8.0 x109/L, CRP>40 mg/L, albumin<34 g/L, creatinine>100 µmol/L, diabetes mellitus, hypertension and chronic lung disease. Risk scores of 4 or higher corresponded to a 28-day cumulative incidence of critical care admission or death of 40.7% (95% CI: 37.1 to 44.4), versus 12.4% (95% CI: 8.2 to 16.7) for scores less than 4. Interpretation: Our study identified predictors of critical care admission and death in people admitted to hospital with COVID-19. These predictors were incorporated into a risk score that will inform clinical care and stratify patients for clinical trials. Funding Statement: NoneDeclaration of Interests: All authors have completed an ICMJE conflict of interest form and report no conflicts of interest.Ethics Approval Statement: The project operated under London South East Research Ethics Committee (reference 18/LO/2048) approval granted to the King's Electronic Records Research Interface (KERRI); specific work on COVID-19 research was reviewed with expert patient input on a virtual committee with Caldicott Guardian oversight.
Abstract Background Missing clinical outcome data are a common occurrence in longitudinal studies. Data quality in clinical audit is a particular cause for concern. The relationship between departmental levels of missing clinical outcome data and care quality is not known. We hypothesise that completeness of key outcome data in a national audit predicts departmental performance. Methods The National Clinical Audit for Rheumatoid and Early Inflammatory Arthritis (NCAREIA) collected data on care of patients with suspected rheumatoid arthritis (RA) from early 2014 to late 2015. This observational cohort study collected data on patient demographics, departmental variables, service quality measures including time to treatment, and the key RA clinical outcome measure, disease activity at baseline, and 3 months follow-up. A mixed effects model was conducted to identify departments with high/low proportions of missing baseline disease activity data with the results plotted on a caterpillar graph. A mixed effects model was conducted to assess if missing baseline disease activity predicted prompt treatment. Results Six thousand two hundred five patients with complete treatment time data and a diagnosis of RA were recruited from 136 departments. 34.3% had missing disease activity at baseline. Mixed effects modelling identified 13 departments with high levels of missing disease activity, with a cluster observed in the Northwest of England. Missing baseline disease activity was associated with not commencing treatment promptly in an adjusted mix effects model, odds ratio 0.50 (95% CI 0.41 to 0.61, p < 0.0001). Conclusions We have shown that poor engagement in a national audit program correlates with the quality of care provided. Our findings support the use of data completeness as an additional service quality indicator.
Indirect excess morbidity in the COVID-19 pandemic may arise from public health risk-mitigation efforts such as stay-at-home orders and re-purposing of healthcare services.1 Increased mental health disorders and shortfalls in the care of long-term conditions are described.2, 3 We used global self-reported cross-sectional data to characterise the factors associated with worsening psoriasis in the pandemic, focussing on the impact of anxiety and depression. Data from a cross-sectional survey (PsoProtectMe4) were extracted on 15th January 2021. After excluding participants self-reporting COVID-19, the association between mental health and worsening psoriasis was assessed using a fully adjusted logistic regression model including covariates selected a priori as potentially influential on psoriasis severity and anxiety/depression. Participants scoring ≥3 in GAD-2 or PHQ-2 defined a positive mental health screen.5 4043 people with psoriasis from 86 countries were included (Table 1). 1728 (42.7%) reported worsening psoriasis in the pandemic. A total of 3575 (88.4%) returned information on their mental health, with a greater proportion of those reporting worsening psoriasis having a positive mental health screen (814/1621, 50.2%) compared to those without worsening psoriasis (562/1954, 28.8%). A greater proportion of females reported worsening psoriasis (1322/2684, 49.3%) compared with males (406/1354, 30.0%). A fully adjusted regression model for worsening psoriasis estimated an odds ratio (OR) 2.01 (95% CI, 1.72–2.34) for those with a positive screen for anxiety or depression compared to those without a positive screen (Fig. 1). Associations were also observed for female gender (OR, 1.82, 95% CI, 1.56–2.13); obesity (OR, 1.22, 95% CI, 1.09–1.36) and shielding (OR, 1.18, 95% CI, 1.03–1.35). There were inverse associations with systemic therapy use [standard systemic OR 0.69 [95% CI, 0.56–0.86] and targeted therapy OR 0.49 (95% CI, 0.38-0.64)]. Of 1541 (38.1%) participants receiving standard systemic ?or targeted therapies for psoriasis, 284 (18.4%) reported non-adherence during the pandemic (Table 1). The commonest reason was concern regarding complications related to COVID-19 (n = 217). Non-adherence was associated with worsening psoriasis (OR, 2.90, 95% CI, 2.31–3.63). A positive mental health screen was more common in those reporting non-adherence compared to those who were adherent (42.8% vs. 32.4%). These data indicate a burden due to the COVID-19 pandemic in people with psoriasis; worsening psoriasis is common and is associated with poor mental health. We find that in the subset on systemic therapy, non-adherence is associated with worsening disease and is driven by concerns about immunosuppressant-related risks of COVID-19. This is an important observation since current guidelines (informed by reassuring data on drug-related risks of severe COVID-196) recommend continuing immunosuppression in people without COVID-19 to maintain disease control.7 Our findings parallel data from the general population indicating an increased mental health burden during the pandemic, particularly in women.8 People with psoriasis – especially those with severe psoriasis, and women – have a high prevalence of anxiety and depression and may thus be particularly vulnerable to the adverse impact of the pandemic on mental health.9 Whilst men are known to be at greater risk of severe outcomes from COVID-19, our data suggest that women may be more susceptible to indirect excess morbidity – poor mental health and worsening skin disease – than men. The generalisability of results is limited given the self-selecting bias of our study population towards UK white women. Individuals non-adherent to treatment, with low computer literacy or less anxiety, may be disinclined to participate, which may introduce ascertainment bias. Our data underscore the importance of holistic models of care and indicate a need to provide access to psychological support. In those with worsening psoriasis, possible non-adherence should be explored. Evidence-based communication around medication-related COVID-19 risks and behavioural approaches for supporting adherence may help address fears, anxieties and confusion.10 Attention given now to address this may mitigate a long-lasting detrimental impact of the pandemic on health outcomes in people with psoriasis. We are grateful to all the patients who have contributed to PsoProtectMe, the professional and patient organisations who supported or promoted PsoProtectMe and for the input of Prof Lars Iversen, Prof Nick Reynolds, Prof Joel Gelfand, Ms Christine Janus and Ms Melissa Sweeney through their vital contributions. We would also like to acknowledge the following individuals for help with translating the PsoProtectMe survey; Dr Haleema Alfailakawi, Dr Wisam Alwan, Dr Rosa Andres Ejarque, Dr Ines Barbosa, Ms Carmen Bugarin Diz, Ms Katarzyna Grys, Dr Mahira Hamdy El Sayed, Mr Tran Hong Truong, Mr Masanori Okuse, Ms Dagmara Samselska, Ms Isabella Tosi, Ms Ya-Hsin Wang, and the Engine Group UK for their generous creative input and website expertise. Nothing to disclose: Dr Yates, Dr Dand, Prof. Langan, Dr. Norton, Dr. Tsakok, Dr. Yiu, Dr De La Cruz, Dr. Contreras, Ms. Vesty, Ms. Vincent, Mr. Bola Coker, Ms. Meynell, Dr. Lambert, Prof. Brown, Prof. Naldi. Prof. Barker reports grants and personal fees from Abbvie, grants and personal fees from Novartis, grants and personal fees from Lilly, grants and personal fees from J&J, from null, during the conduct of the study. Prof. Griffiths reports grants and personal fees from AbbVie, grants from Amgen, grants from BMS, grants and personal fees from Janssen, grants from LEO, grants and personal fees from Novartis, grants from Pfizer, grants from Almirall, grants and personal fees from Lilly, grants and personal fees from UCB Pharma, outside the submitted work. Prof. Jullien reports personal fees and non-financial support from Abbvie, personal fees and non-financial support from Novartis, personal fees and non-financial support from Janssen-Cilag, personal fees and non-financial support from Lilly, personal fees and non-financial support from Leo-Pharma, personal fees and non-financial support from MEDAC, personal fees and non-financial support from Celgene, personal fees from Amgen, outside the submitted work. Dr. Capon reports consultancy fees from AnaptysBio, grants from Boheringer-Ingelheim, outside the submitted work. Prof. Bachelez reports personal fees from Abbvie, personal fees from Janssen, personal fees from LEO Pharma, personal fees from Novartis, personal fees from UCB, personal fees from Almirall, personal fees from Biocad, personal fees from Boehringer-Ingelheim, personal fees from Kyowa Kirin, personal fees from Pfizer, outside the submitted work. Prof. Gisondi reports personal fees from Abbvie, Amgen, Eli Lilly, Janssen, Novartis, Pierre Fabre, Sandoz, UCB, outside the submitted work. Dr. Galloway reports personal fees from Abbvie, personal fees from Sanofi, personal fees from Novartis, personal fees from Pfizer, grants from Eli Lilly, personal fees from Janssen, personal fees from UCB, outside the submitted work. Prof. Weinmann has presented talks for Abbvie, Abbott, Bayer, Chiesi, Boehringer Ingelheim, Roche and Merck. Dr. Mason reports personal fees from LEO Pharma and Novartis, outside the submitted work. Ms. Moorhead reports personal fees from Abbvie, personal fees from Celgene, personal fees from Janssen, personal fees from LEO Pharma, personal fees from Novartis, personal fees from UCB, outside the submitted work. Dr. Puig reports grants and personal fees from AbbVie, grants and personal fees from Almirall, grants and personal fees from Amgen, grants and personal fees from Boehringer Ingelheim, personal fees from Bristol Myers Squibb, personal fees from Fresenius-Kabi, grants and personal fees from Janssen, grants and personal fees from Lilly, personal fees from Mylan, grants and personal fees from Novartis, personal fees from Pfizer, personal fees from Sandoz, personal fees from Sanofi, personal fees from Samsung-Bioepis, grants and personal fees from UCB, outside the submitted work. Dr. Mahil reports departmental income from Abbvie, Celgene, Eli Lilly, Janssen-Cilag, Novartis, Sanofi, UCB, outside the submitted work. Dr. Di Meglio reports grants and personal fees from UCB, personal fees from Novartis, personal fees from Janssen, outside the submitted work. Prof. Warren reports grants and personal fees from Abbvie, grants and personal fees from Celgene, grants and personal fees from Eli Lilly, grants and personal fees from Novartis, personal fees from Sanofi, grants and personal fees from UCB|, grants and personal fees from Almirall, grants and personal fees from Amgen, grants and personal fees from Janssen, grants and personal fees from Leo, grants and personal fees from Pfizer, personal fees from Arena, personal fees from Avillion, personal fees from Bristol Myers Squibb, personal fees from Boehringer Ingelheim, outside the submitted work. Prof. Smith reports grants from Abbvie, Sanofi, Novartis, and Pfizer and through consortia with multiple academic partners (psort.org.uk, BIOMAP-IMI.eu), outside the submitted work. Dr. Torres reports grants and personal fees from AbbVie, Almirall, Amgen, Arena Pharmaceuticals, Biogen, Biocad, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, LEO Pharma, MSD, Novartis, Pfizer, Samsung-Bioepis, Sandoz, during the conduct of the study. Dr. Waweru is on the Board of the International Federation of Psoriasis Associations who have received grants from Abbvie, Almirall, Amgen, Bristol Meyers Squibb, Boehringer Ingelheim, Celgene, Janssen, Leo Pharma, Eli Lilly, Novartis, Sun Pharma, Pfizer, and UCB, outside the submitted work. Mr. Urmston reports grants from Almirall, grants from Abbvie, grants from Amgen, grants from Celgene, grants from Dermal Laboratories, grants from Eli Lilly, grants from Janssen, grants from LEO Pharma, grants from T and R Derma, grants from UCB, outside the submitted work. Ms. McAteer reports grants from Abbvie, grants from Almirall, grants from Amgen, grants from Celgene, grants from Dermal Laboratories, grants from Eli Lilly, grants from Janssen, grants from LEO Pharma, grants from UCB, grants from T and R Derma, outside the submitted work. We acknowledge financial support from the Department of Health via the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London, the NIHR Manchester Biomedical Research Centre and the Psoriasis Association. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. SKM is funded by a Medical Research Council (MRC) Clinical Academic Research Partnership award (MR/T02383X/1). ND is funded by Health Data Research UK (MR/S003126/1), which is funded by the UK MRC, Engineering and Physical Sciences Research Council; Economic and Social Research Council; Department of Health & Social Care (England); Chief Scientist Office of the Scottish Government Health and Social Care Directorates; Health and Social Care Research and Development Division (Welsh Government); Public Health Agency (Northern Ireland); British Heart Foundation; and Wellcome Trust. ZZNY is funded by an NIHR Academic Clinical Lectureship through the University of Manchester. CEMG is an NIHR Emeritus Senior Investigator and is funded in part by the MRC (MR/101 1808/1). CEMG and RBW are in part supported by the NIHR Manchester Biomedical Research Centre. SML is supported by a Wellcome senior research fellowship in clinical science (205039/Z/16/Z); this research was funded in whole or in part by the Wellcome Trust [205039/Z/16/Z]. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript (AAM) version arising from this submission. SML is also supported by Health Data Research UK (grant no. LOND1), which is funded by the UK MRC, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome Trust. The pre-print for this manuscript has been archived in the MedRxiv server: https://www.medrxiv.org/content/10.1101/2021.05.04.21256507v1.
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)
 scale(5.56106)'%3e%3ccircle r='1'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cpath id='b' d='M.195-.98 0-1.39l-.195.408' transform='rotate(11.25)'/%3e%3cuse xlink:href='%23b' transform='rotate(22.5)'/%3e%3cuse xlink:href='%23b' transform='rotate(45)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(67.5)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='scale(-1 1)'/%3e%3c/g%3e%3cg transform='translate(0 58.787) scale(8.1434)'%3e%3ccircle r='1'/%3e%3cg id='g'%3e%3cg id='f'%3e%3cpath id='e' d='M.259.966 0 1.576l-.259-.61'/%3e%3cuse xlink:href='%23e' transform='rotate(180)'/%3e%3c/g%3e%3cuse xlink:href='%23f' transform='rotate(90)'/%3e%3c/g%3e%3cuse xlink:href='%23g' transform='rotate(30)'/%3e%3cuse xlink:href='%23g' transform='rotate(60)'/%3e%3c/g%3e%3c/g%3e%3c/svg%3e)
'%3e%3cpath id='a' fill='%23FF0' d='M0 0v6h4' transform='rotate(18)'/%3e%3cuse xlink:href='%23a' transform='scale(-1 1)'/%3e%3c/g%3e%3cg id='c' transform='rotate(72)'%3e%3cuse xlink:href='%23b'/%3e%3cuse xlink:href='%23b' transform='rotate(72)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='scale(-1 1)'/%3e%3c/svg%3e)