UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias

Biomedical image segmentation (BIS) task is challenging due to the variations in organ types, position, shape, size, scale, orientation, and image contrast. Conventional methods lack accurate and automated designs. Artificial intelligence (AI)-based UNet has recently dominated BIS. This is the first review of its kind that microscopically addressed UNet types by complexity, stratification of UNet by its components, addressing UNet in vascular vs. non-vascular framework, the key to segmentation challenge vs. UNet-based architecture, and finally interfacing the three facets of AI, the pruning, the explainable AI (XAI), and the AI-bias. PRISMA was used to select 267 UNet-based studies. Five classes were identified and labeled as conventional UNet, superior UNet, attention-channel UNet, hybrid UNet, and ensemble UNet. We discovered 81 variations of UNet by considering six kinds of components, namely encoder, decoder, skip connection, bridge network, loss function, and their combination. Vascular vs. non-vascular UNet architecture was compared. AP(ai)Bias 2.0-UNet was identified in these UNet classes based on (i) attributes of UNet architecture and its performance, (ii) explainable AI (XAI), and, (iii) pruning (compression). Five bias methods such as (i) ranking, (ii) radial, (iii) regional area, (iv) PROBAST, and (v) ROBINS-I were applied and compared using a Venn diagram. Vascular and non-vascular UNet systems dominated with sUNet classes with attention. Most of the studies suffered from a low interest in XAI and pruning strategies. None of the UNet models qualified to be bias-free. There is a need to move from paper-to-practice paradigms for clinical evaluation and settings.

THEMES AND CHALLENGES OF END OF LIFE CARE FOR COVID-19 PATIENTS REQUIRING NON-INVASIVE RESPIRATORY SUPPORT

Introduction The COVID-19 pandemic created new challenges due to the high numbers and the high symptom burden of end-of-life patients on respiratory support. Methods We conducted an audit of end-of-life patients on the respiratory HDU wards at Whipps Cross Hospital between 17/09/2020-30/01/2021. Results 84 patients receiving respiratory support (in the form of CPAP and HFNT) died during that time at a mean age of 77 (95% CI 67-87) and median of 79 years. All but one death, which followed a cardiac arrest, were expected. The most common clinical indicator for a patient approaching end-of-life was hypoxia on respiratory support, which was documented in 36 (43%) patients, followed by terminal agitation in 27 (32%) patients. Objections to the medical assessment of terminal illness were raised by 3 families and in 1 case the patient had conflicting wishes. The average time between recognition of a terminal deterioration and death was 1.4 days with a median of 2 days. 29 (35%) patients did not have a specialist palliative care review primarily due to the rapid patient deterioration. 25 (30%) patients were not visited by a relative due to the infection risk. 72 (86%) patients were weaned off respiratory support and those who continued did so due to a medical or patient decision. Despite most patients (82%) receiving continuous subcutaneous infusions with an opiate and benzodiazepine most patients had persistent terminal symptoms: 51 (74%) on infusions had agitation and 38 (55%) were persistently breathlessness. Discussion This data highlights some of the major difficulties faced in caring for patients with COVID on respiratory support and approaching end of life. With the inevitably persisting nature of this pandemic and the possibility of future pandemics still present, it is vital to be able to offer guidance and multidisciplinary input to ensure comfort and dignity for these patients.

Legal Challenges in Managing Human Resource due to COVID19

December 2019 saw the world changing, particularly in context of the manner in which work took place. People were confined to their homes, and were had to face hardships in managing their daily lives. The workplace was no different as working from home became the new normal. COVID19 brought a lot of challenges in managing the human resource due to the various legal challenges that were brought with it. For instance, the mental health issues while working from home, or the lack of vaccination raising safety and privacy concerns for others and for the employees, were among the few challenges that an HR manager had to keep up with. This work highlights some of such legal challenges that were and are being faced in managing the human resource.

Covishield (TM) (ChAdOx1) Vaccine Effectiveness and Epidemiological Risk Factors of COVID-19 Infection among Frontline Workers during Second Wave of COVID-19 Pandemic, New Delhi: A Case-Control Study

Background: Frontline workers were the first cohorts vaccinated with Covishield (TM) (ChAdOx1 nCoV-19) vaccine with dose-interval of 4-6 weeks. We evaluated vaccine effectiveness (VE) of Covishield and studied epidemiological risk factors associated with COVID-19 during second wave of COVID-19 pandemic. Methods: We conducted a 1:3 case-control community-based study, as per WHO protocol. We identified case-patients from COVID-19 surveillance system and recruited controls from the same community as per the WHO protocol. Information was obtained through questionnaire;and all potential confounders were identified to evaluate VE. Results: We enrolled 243 case-patients and 712 controls. Adjusted VE of fully vaccinated was 74% (95% confidence interval [CI]: 53%-86%) against infection and 91% (95% CI: 78%-97%) against moderately severe disease. Pre-infection high-risk exposure events such as ccontact with COVID-19-positive patient, visit to a crowded place, and attending social-gathering in confined space were significantly associated with contracting infection, with odds ratios 10.1 (95% CI: 5.6-18.3), 6.0 (95% CI: 1.8-20.2) and 3.9 (95% CI: 1.4-10.5) respectively. The use of double-mask and past COVID-19 infection was 60% and 70% protective, respectively. Conclusion: Covishield vaccine is highly effective against infection and mainly against disease-severity during high-transmission settings. We recommend three-layer shield to minimize breakthrough and re-infections comprising of vaccination, double-masking, and avoiding "pre-infection high-risk exposure events."

Five Strategies for Bias Estimation in Artificial Intelligence-based Hybrid Deep Learning for Acute Respiratory Distress Syndrome COVID-19 Lung Infected Patients using AP(ai)Bias 2.0: A Systematic Review

Coronavirus 2019 (COVID-19) has led to a global pandemic infecting 224 million people and has caused 4.6 million deaths. Nearly 80 Artificial Intelligence (AI) articles have been published on COVID-19 diagnosis. The first systematic review on the Deep Learning (DL)-based paradigm for COVID-19 diagnosis was recently published by Suri et al. [IEEE J Biomed Health Inform. 2021]. The above study used AtheroPoint’s “AP(ai)Bias 1.0”using 10 AI attributes in the DL framework. The proposed study uses “AP(ai)Bias 2.0”as part of the three quantitative paradigms for Risk-of-Bias quantification by using the best 40 dedicated Hybrid DL (HDL) studies and utilizing 39 AI attributes. In the first method, the radial-bias map (RBM) was computed for each AI study, followed by the computation of bias value. In the second method, the regional-bias area (RBA) was computed by the area difference between the best and the worst AI performing attributes. In the third method, ranking-bias score (RBS) was computed, where AI-based cumulative scores were computed for all the 40 studies. These studies were ranked, and the cutoff was determined, categorizing the HDL studies into three bins: low, moderate, and high. Using the Venn diagram, these three quantitative methods were benchmarked against the two qualitative non-randomized-based AI trial methods (ROBINS-I and PROBAST). Using the analytically derived moderate-high and low-moderate cutoff of 2.9 and 3.6, respectively, we observed 40%, 27.5%, 17.5%, 10%, and 20% of studies were low-biased for RBM, RBA, RBS, ROBINS-I, and PROBAST, respectively. We present an eight-point recommendation for AP(ai)Bias 2.0 minimization. IEEE

Bidirectional link between diabetes mellitus and coronavirus disease 2019 leading to cardiovascular disease: A narrative review. World journal of diabetes

Coronavirus disease 2019 (COVID-19) is a global pandemic where several comorbidities have been shown to have a significant effect on mortality. Patients with diabetes mellitus (DM) have a higher mortality rate than non-DM patients if they get COVID-19. Recent studies have indicated that patients with a history of diabetes can increase the risk of severe acute respiratory syndrome coronavirus 2 infection. Additionally, patients without any history of diabetes can acquire new-onset DM when infected with COVID-19. Thus, there is a need to explore the bidirectional link between these two conditions, confirming the vicious loop between “DM/COVID-19”. This narrative review presents (1) the bidirectional association between the DM and COVID-19, (2) the manifestations of the DM/COVID-19 loop leading to cardiovascular disease, (3) an understanding of primary and secondary factors that influence mortality due to the DM/COVID-19 loop, (4) the role of vitamin-D in DM patients during COVID-19, and finally, (5) the monitoring tools for tracking atherosclerosis burden in DM patients during COVID-19 and “COVID-triggered DM” patients. We conclude that the bidirectional nature of DM/COVID-19 causes acceleration towards cardiovascular events. Due to this alarming condition, early monitoring of atherosclerotic burden is required in “Diabetes patients during COVID-19” or “new-onset Diabetes triggered by COVID-19 in non-Diabetes patients”.

The Impact of Movement Control Order (MCO) during COVID-19 Pandemic on Air and Water Quality in Malaysia: A Mini Review

Air and water are essential aspects of life on earth, and any changes in the quality have a significant impact on human beings. Although the current COVID-19 pandemic has some adverse effects on the environment, there are also some benefits from this pandemic. One of the significant positive effects of this pandemic is the Movement Control Order (MCO) that the environment had rejuvenated during this period. Many reports worldwide, including Malaysia, had reported that the air and water quality had shown some improvement. This paper reviews the impact of MCO on air and water quality in Malaysia. The MCO effects on air and water pollution were reviewed, highlighting the latest research carried out in these areas. The reviewed studies showed a positive effect on air and water quality in Malaysia, where it was improved to a great extent. For instance, there is a reduction in carbon monoxide (CO), sulphur dioxide (SO2), nitrogen dioxide (NO2) and particulate matter (PM) during the MCO period. As for the water quality studies, all the reviewed studies showed a remarkable improvement in the Water Quality Index (WQI), compared to before MCO. The review also shows that there are few studies on the effect of water quality during the pandemic, compared to air quality, probably because Malaysia is still under the MCO period. © 2021 Italian Association of Chemical Engineering - AIDIC. All rights reserved.

Disease severity and patient recovery in COVID-19: an observational study comparing first and second wave admissions in London

P97 Table 1Demographics and clinical characteristics of participants at hospital admission and follow up for wave 1 and 2 admissions Wave 1 Wave 2 p-value N = 400 N = 400 Demographics and Lifestyle Age (years) (Median, IQR) 61 (50 -74) 61 (51 - 74) 0.59 Male gender (N,%) 247 (61.8%) 237 (59.3%) 0.47 Ethnicity (White) (N,%) 200 (50.0%) 195 (48.8%) 0.001* Smoking status – Never smoker (N,%) 215 (53.8%) 219 (54.8%) 0.58 BMI (kg/m2) (Median, IQR) 26.8 (24.1 - 29.4) 27.7 (24.3 - 31.6) 0.015 Underlying clinical status Clinical Frailty Score (Median, IQR) 2 (2, 4) N = 332 3 (2, 3) N = 384 0.001 Shielding Status (N,%) Extremely vulnerable HCP issued letter 32 (10.1%) 23 (7.2%) 39 (11.2%) 5 (1.4%) 0.001 Covid Admission Severity Parameters Total number of symptoms (Median, IQR) 4 (3 - 6) 3 (2 - 3) <0.0001 NEWS2 score (Median, IQR) 5 (2 - 7) N = 372 4 (3 - 6) N = 379 0.60 TEP status – For full escalation (N,%) 284/365 (77.8%) 361/400 (90.3%) <0.0001 Maximum respiratory support (N,%) CPAP NIV N= 377 10 (2.7%) 2 (0.5%) N = 400 32 (8.0%) 5 (1.3%) <0.0001 Received anti-viral or immunosuppressive drugs (N,%) 23/374 (6.2%) 127/400 (31.8%) <0.0001 ITU admission (N,%) 62/377 (16.5%) 43/400 (10.8%) 0.02 Intubation (N,%) 49/364 (13.5%) 19/400 (4.8%) <0.0001 Pulmonary Embolus (N,%) 22/360 (6.1%) 24/395 (6.1%) 0.98 Follow-up Outcomes N = 322 N = 365 Mental Health Outcomes PHQ2 score ≥ 3 (N,%) 47 (15.4%) 34 (9.9%) 0.04 TSQ score ≥ 5 (N,%) 44 (14.9%) 12 (3.3%) <0.0001 Physical Recovery and Symptoms Not returned to work (N,%) 76 (24.8%) 114 (33.6%) 0.03 Improved Sleep quality (N,%) 168 (61.5%) 265 (78.4%) <0.0001 Improved Fatigue (N,%) 241 (87.6%) 307 (88.7%) 0.91 Improved Cough (N,%) 194 (69.5%) 291 (84.8%) <0.0001 Improved Breathlessness (N,%) 213 (76.1%) 311 (89.6%) <0.0001 Total Number of Symptoms (Median, IQR) 1 (0 - 2) N=314 0 (0 – 1) N=364 Radiology outcomes (N,%) Normalised Significantly Improved Not significantly improved Worsened N=309 211 (68.3%) 55 (17.8%) 2 (0.7%) 30 (9.7%) N=279 187 (67.0%) 65 (23.3%) 13 (4.7%) 14 (5.0%) <0.0001 *p value likely attributable to differences in unknown ethnicityConclusionThese data suggest second wave pa ients, although frailer, presented with fewer symptoms and experienced improved hospital admission trajectory. They demonstrated improved self-reported mental health and physical recovery outcomes despite earlier follow-up, possibly attributed to improved in-hospital treatment. Supporting recovery remains a clinical priority given many patients had not returned to work.ReferenceSaito S, et al. First and second COVID-19 waves in Japan: comparison of disease severity and characteristics. J Infect. 2021;82(4):84-123.

Challenges with end-of-life care in COVID patients requiring non-invasive respiratory support

IntroductionThe COVID-19 pandemic has seen an unprecedented number of adults receiving non-invasive respiratory support (NIRS) with such patients having a high mortality rate.MethodsAs part of better elucidating the challenges of end of life care delivery in the COVID era, we conducted an audit of our respiratory HDU ward at Whipps Cross Hospital focusing on a 19-week period between 17/09/2020–30/01/2021 and on patients who did not survive their admission. We excluded patients that were transferred to ITU.ResultsOf a total of 309 patients receiving NIRS on our ward, 84 died during that time at a mean age of 77 (95% CI 67–87) and median of 79 years. 63 patients received CPAP, 67 received HFNT and 42 were first started on HFNT and converted to CPAP. The average length of stay was 10 days (4–16). The mean day of symptoms on presentation to hospital was 11.5 days (1.7–21.3). Average duration of symptoms prior to admission to our ward was 19.7 (9.1–30.3) days.One death was unexpected and followed a cardiac arrest. The most common indicator for a patient approaching end-of-life was hypoxia on NIRS, which was documented in 36 (43%) patients, followed by terminal agitation in 27 (32%) patients. The average time between recognising end-of-life and death was 1.4 days with a median of 2 days. 72 (86%) patients were weaned off NIRS and those who continued did so due to a medical or patient decision. Despite the vast majority (82% of patients) being on syringe drivers with an opiate and benzodiazepine most patients had persistent terminal symptoms: 51 (74%) had agitation and 38 (55%) were persistently breathlessness. Interestingly, no patient opted to rest in the prone position.DiscussionThis data primarily suggests the challenging nature of managing end-of-life care for COVID patients deteriorating on NIRS due to the high symptom load and the short time there is to achieve comfort for these individuals. Clinicians need to conduct frequent comfort reviews for such patients, consider subcutaneous infusions, as well as potentially an increase in medication doses, in conjunction with specialist palliative care input, in order to achieve comfort.

The impact of ethnicity on the long-term sequelae of COVID-19: follow-up from the first and second waves in North London

P137 Table 1Demographics, admission severity and follow-up symptomsVariable White N = 603 Asian N = 252 Black N = 130 Other N = 122 p-value Age 65 ± 16.5 59 ± 15.4 59 ± 13.9 59 ± 14.7 <0.001 Male (%) 372 (62) 148 (59) 72 (55) 81 (66) 0.28 Index of deprivation* 6 (3–7) 6 (4–8) 5 (3–7) 5 (3–7) 0.03 Body mass index 27.1 (23.5–30.5) 26.0 (23.7 – 29.2) 28.9 (25.9 – 34.7) 26.7 (25.1 – 30.9) <0.001 Hypertension (%) 244/583 (42) 113/247 (46) 72/125 (58) 40/119 (34) 0.001 Cardiovascular disease (%) 133/415 (32) 45/166 (27) 15/86 (17) 16/73 (22) 0.02 Diabetes (%) 122/583 (21) 80/247 (32) 45/125 (36) 40/119 (34) <0.001 Respiratory disease (%) 124/416 (30) 39/167 (23) 21/91 (23) 16/70 (23) 0.25 Chronic kidney disease (%) 61/583 (11) 29/247 (12) 27/125 (22) 9/119 (8) 0.002 Any mental health (%) 77/583 (13) 23/247 (9) 8/125 (6) 17/119 (14) 0.08 Smoking history (%) 250/587 (43) 43/244 (18) 44/127 (35) 44/118 (37) <0.001 Clinical frailty score 3 (2–4) 2 (2–4) 3 (2–4) 3 (2–3) 0.11 NEWS2 4 (2–6) 4.5 (3–6) 5 (3–6) 5 (3–7) 0.3 Respiratory support 80/564 (14) 47/236 (20) 23/116 (20) 21/118 (18) 0.15 Follow-up symptoms MRC score* 2 (1–3) 2 (1–3) 2 (1–3) 2 (1–2) 0.61 Cough improved (%) 414/553 (75) 177/232 (76) 85/118 (72) 87/113 (77) 0.8 Fatigue improved (%) 451/552 (82) 193/228 (85) 109/122 (89) 88/115 (77) 0.05 Sleep improved (%) 342/536 (64) 155/228 (68) 76/117 (65) 68/112 (61) 0.57 Burden of symptoms* 1 (0–2) 1 (0–2) 1 (0–2) 1 (0–2) 0.78 Returned to work (%) 142/256 (56) 77/139 (55) 29/64 (45) 41/71 (58) 0.45 Felt back to normal (%) 256/439 (55) 112/186 (60) 62/103 (60) 43/78 (55) 0.87 Positive PHQ-2 (depression screening) 65/580 (11) 40/242 (17) 12/126 (10) 11/116 (10) 0.09 Positive TSQ (post-traumatic stress screening) 42/601 (7) 16/248 (7) 13/130 (10) 8/122 (7) 0.6 *Non-parametric data presented as median ± interquartile range, all other data presented as mean ± standard deviation.DiscussionOur data demonstrate that despite having more co-morbidities associated with worse outcomes, adults from BAME backgrounds who are discharged from hospital following COVID-19 are no more likely to experience symptoms consistent with ‘Long CO ID’. However, given the increased risk of infection among BAME communities, we must ensure that reducing health inequalities remain central to the UK health agenda.ReferenceSze, et al. EClinicalMedicine 2020. doi:10.1016/j.eclinm.2020.100630

Exploring panic buying behavior during the COVID-19 pandemic: a developing country perspective

Purpose: This paper aims to identify factors that influence customers' panic buying behavior during the COVID-19 pandemic. Design/methodology/approach: A self-administered questionnaire was distributed to 357 participants in Fiji, and structural equation modeling to analyze the collected data. Findings: Results indicate that expected personal outcomes is positively associated with customers' attitudes while expected community-related outcomes negatively impact customers' attitudes. Factors such as attitude, subjective norms, scarcity, time pressure and perceived competition were found to positively influence customers' panic buying intention. Furthermore, scarcity and time pressure were confirmed to positively influence perceived competitiveness while perceived social detection risk negatively influences customer's panic buying intention. Practical implications: The findings highlight the need for better measures to ensure that every customer has access to goods and services and is not deprived of such necessities in times of a crisis. These results will assist store managers and policymakers in introducing better management, social policies and resource utilization mechanisms to mitigate panic buying during the pandemic. Originality/value: This study's findings contribute to the literature on customer's panic buying behavior during a global pandemic. Research in this area remain scarce, inconsistent and inconclusive. Novel insights are generated as this study is the first to combine the theory of planned behavior, privacy calculus theory and protection motivation theory. Applying these theories allows new relationships to be tested to better understand customer behavior during a global pandemic. With most studies on customer behavior during crises and disasters in developed countries, this study generates new insights by exploring customer behavior in a developing country. © 2021, Emerald Publishing Limited.

Supporting teachers moving online, using a MOOC, during the COVID-19 pandemic

Following campus closures due to the COVID-19 pandemic, many Ministries of Education around the world requested teachers to move their teaching online. This case study reflects on how the Commonwealth of Learning responded to requests from two countries to provide support in pedagogical and curricular change for online learning in this process. A Massive Open Online Course (MOOC) platform was used to upskill 11,568 teachers in two regions of the Commonwealth. Analytics from within the course, together with pre-, mid-and end-course surveys of participants’ perceptions indicated that while there was, and is, scope for improvement, the short course largely reached its objective of providing immediate support on an introductory level and that the approach adopted was largely appropriate for the purpose. © 2021, Commonwealth of Learning. All rights reserved.

The continuing saga of women's work during COVID-19

This paper employs a social reproduction framework to argue that the two main institutions of capitalism-the markets and the state-have failed to adequately provide for the working people of India during the pandemic while fostering gender inequities. While the demand for gender equity in the domestic sphere and the workplace is not new, the pandemic further underscores its urgency. © 2021 Economic and Political Weekly. All rights reserved.

Ward vs. emergency department discharge in patients with COVID-19: Does it make a difference to symptom burden and radiological severity at follow up?

Background During the COVID-19 pandemic patients were often discharged following assessment within the Emergency Department (ED). However, to our knowledge no data exists on whether these patients are likely to have a better trajectory of recovery. We investigated the symptom burden and radiological severity at follow-up for patients discharged directly from ED compared to those admitted. Methods Patients diagnosed with COVID-19 between 05.03.20 and 05.05.20 discharged from ED or the ward had telephone assessments 8-10 weeks post-discharge. Demographics, co-morbidities, symptom burden (quantified using a numerical rating scale) and psychological health data were collected. Patients were offered a follow-up chest radiograph (CXR) if abnormal on discharge. Results During this period we contacted 188 ED and 471 ward discharges, median (IQR) follow up 77.5 days (65-87) and 64 days (55-82) respectively. The baseline demographic data is shown in table 1. Ward patients were significantly older (62.5 vs. 53.8 years, p<0.001), more likely to be hypertensive (49% vs. 27%, p<0.001), diabetic (31% vs. 16%, p=0.004), frailer (median clinical frailty score 2(2-5) vs. 2(2-3), p<0.001) and have a higher NEWS2 score (5 (2-7) vs. 2 (1-4), p<0.001). There were no significant differences in other characteristics including ethnicity, heart disease and smoking. 115 (61%) ED and 340 (72%) ward patients completed follow-up calls. There were no significant differences in symptom burden (breathlessness, cough, fatigue, sleep quality) and psychological burden (assessed by screening questionnaires). No significant difference was noted in the proportion able to return to work (ED vs. ward: 70% vs. 59%, p=0.111). Finally, 5% of ED patients had an unchanged/worsening CXR compared to 9% discharged from the ward (p=0.42). Conclusion Our data confirms that patients admitted to hospital are likely to be more unwell, older, more frail and have hypertension and diabetes. Despite this, there were no significant differences in symptoms or radiological severity at follow up, suggesting that hospitalised patients do not appear to have worse physical or psychological sequelae compared to those discharged directly from ED. We should develop strategies to identify the patients who are more likely to suffer from longterm sequelae post COVID-19, to appropriately establish a targeted follow-up service.

Higher body mass index (bmi) is associated with Improved continuous positive airway pressure (cpap) outcomes in patients with hypoxic Respiratory failure secondary to covid-19

Background During the COVID-19 pandemic, the use of continuous positive airway pressure (CPAP) for type 1 respiratory failure (T1RF) has been shown to possibly delay or avoid the need for intubation.1 However, no study has identified patient characteristics that may be associated with more favourable outcomes. We hypothesised that patients with a higher body mass index (BMI) would have better outcomes with CPAP as they are more likely to have undiagnosed obstructive sleep apnoea (OSA) and upper airway resistance. Methods We retrospectively reviewed use of CPAP in a ward setting for T1RF secondary to COVID-19 between 20.3.20 and 20.4.20. In addition to patient demographic data and co-morbidities, we assessed: Oxygen requirements pre-CPAP, mean CPAP pressures and survival with CPAP alone (CPAP success). Results 41 ward patients received CPAP. Patients' baseline characteristics are shown in table 1. All were deemed suitable for intubation and ventilation (I&V) prior to commencing CPAP. Nine out of 41 (22%) did not require I&V and survived to discharge with CPAP alone. CPAP failed in 32 patients (78%);30 required I&V (ITU survival 67%) and two patients were palliated. Patients with CPAP success all had BMI >25 kg/m2 (median BMI 30.0 (28.1-37.0) kg/m2). This was significantly higher than in those where CPAP failed (47% had BMI >25 kg/m2;median 24.9 kg/m2 (22.9-28.1), p=0.005). 37.5% (n=12) of patients where CPAP failed had a smoking history, (of which only 1 (8.3%) had a diagnosis of COPD), compared to 0% of CPAP success patients (p=0.023). Conclusion In our small cohort, CPAP alone was successful in 22%. This was lower than another recent study (1), however, our patient cohort had more co-morbidities. Patients with a higher BMI had significantly greater CPAP success. This may be due to an increased number of undiagnosed OSA in this cohort and merits further investigation. While smokers had an increased risk of CPAP failure, none of the patients were current smokers and there was limited data on pack-year history. Further studies are necessary to identify factors that may point to greater CPAP success during COVID-19.

Do persistent chest radiograph changes Correlate with ongoing respiratory symptoms in patients recovering from covid-19 Pneumonia?

Introduction and Objectives In May 2020, BTS published guidelines on radiological follow-up for patients with COVID-19 pneumonia, advising an initial repeat chest radiograph at 12 weeks to assess resolution.1 It is unclear whether persistent chest radiograph changes are clinically significant. Our aim was to assess whether there is a correlation between post-COVID chest radiograph appearances and ongoing respiratory symptoms. Methods Inpatients at two trust hospital sites diagnosed with COVID-19, either clinically or from a positive nasopharyngeal swab, were followed-up via telephone approximately 6-8 weeks post-discharge. Patients were offered a chest radiograph and blood tests if abnormal and a symptomatic assessment via a proforma. Patients subjectively rated their degree of breathlessness, cough and fatigue using a numerical rating scale. Chest radiograph reports were coded by consultant radiologists as per BSTI guidelines2 and grouped into 'improvers' (PCVCX0/1) and 'non-improvers' (PCVCX2/3 i.e. static or worsening appearances). Patients who had both an initial and follow-up chest radiograph, and who completed a proforma were included for retrospective analysis Introduction and Objectives In May 2020, BTS published guidelines on radiological follow-up for patients with COVID-19 pneumonia, advising an initial repeat chest radiograph at 12 weeks to assess resolution.1 It is unclear whether persistent chest radiograph changes are clinically significant. Our aim was to assess whether there is a correlation between post-COVID chest radiograph appearances and ongoing respiratory symptoms. Methods Inpatients at two trust hospital sites diagnosed with COVID-19, either clinically or from a positive nasopharyngeal swab, were followed-up via telephone approximately 6-8 weeks post-discharge. Patients were offered a chest radiograph and blood tests if abnormal and a symptomatic assessment via a proforma. Patients subjectively rated their degree of breathlessness, cough and fatigue using a numerical rating scale. Chest radiograph reports were coded by consultant radiologists as per BSTI guidelines2 and grouped into 'improvers' (PCVCX0/1) and 'non-improvers' (PCVCX2/3 i.e. static or worsening appearances). Patients who had both an initial and follow-up chest radiograph, and who completed a proforma were included for retrospective analysis.

The impact of smoking on symptom and radiological severity at COVID-19 follow up

Background The relationship between smoking and COVID-19 disease severity is uncertain;one meta-analysis found smoking increases the risk of developing severe COVID-19 two-fold.1 No previous study has reported whether smokers have worse outcomes at follow-up. We hypothesised that smokers admitted to hospital with COVID-19 would have a greater symptom and radiological severity at follow-up. Methods We prospectively followed up swab-positive COVID-19 patients in two hospitals discharged between 03.05.20 and 19.06.20. Telephone calls were conducted 8-10 weeks post discharge. Demographics, co-morbidities, smoking history and symptom burden data were collected. Symptom burden was quantified using a numerical rating scale for breathlessness, cough and fatigue. Patients were offered a follow-up chest radiograph (CXR) if abnormal on discharge Results 782 patients were reviewed post-discharge, median (IQR) time to review: 63 (54-79) days. Smoking history was obtained for 537 patients. Outcomes for 181 (34%) current/ex-smokers were compared to 356 (66%) never-smokers. Table 1 demonstrates baseline characteristics and symptom burden between groups at follow-up. Never-smokers were significantly younger (59.5±16.3 vs. 65.1±15.5 years, p<0.001) and more likely to be from ethnic minority groups (51.4% vs 34.8%, p<0.001). Ex/current smokers had significantly increased self-reported breathlessness (1 (0-3) vs 0 (0-2);p=0.037) and higher Medical Research Council (MRC) dyspnoea score (2 (1-3) vs 1(1-2);p=0.013). They were less likely to have returned to work (30% vs 51%;p=0.013). Regression analyses demonstrated no significant impact of age and ethnicity on self-reported breathlessness (p=0.317) but demonstrated a significant impact of age on the MRC score (p<0.001). There were no significant differences in CXR findings at follow-up. Conclusion In this large clinical cohort, ex/current smokers had significantly increased self-reported breathlessness at follow-up. These results should be interpreted with caution as the burden of breathlessness prior to admission is unknown. Interestingly, there were no significant differences in other symptoms, nor any differences in radiology findings. Further work is required to understand the mechanisms underlying these findings in order to mitigate the effect of COVID-19 in current/ex smokers. We should continue to routinely and optimally treat current smokers for their tobacco dependence.