Characteristics and risk factors for persistent breathlessness after hospitalisation for COVID-19

Background: Persisting breathlessness after COVID-19 infection is common and debilitating. We aimed to characterise and identify risk factors for patients with persistent breathlessness following COVID-19 hospitalisation. Method(s): PHOSP-COVID is a multi-centre prospective cohort study of UK adults hospitalised for COVID-19. Clinical data were collected during hospitalisation and at a research visit. Breathlessness was measured by a numeric rating scale of 0-10. We defined post-COVID breathlessness as an increase in score of 1 or more compared to the preCOVID-19 level. Multivariable logistic regression was used to identify risk factors. Result(s): We included 1,226 participants (37% female, median age 59 years, 22% mechanically ventilated). At a median five months after discharge, 50% reported post-COVID breathlessness. Risk factors for post-COVID breathlessness were socio-economic deprivation (adjusted odds ratio, 1.67;95% confidence interval, 1.14-2.44), pre-existing depression/anxiety (1.58;1.06-2.35), female sex (1.56;1.21-2.00) and admission duration (1.01;1.00- 1.02). Black ethnicity (0.56;0.35-0.89) and older age groups (0.31;0.14-0.66) were less likely to report post-COVID breathlessness. Post-COVID breathlessness was associated with worse performance on the shuttle walk test and forced vital capacity, but not with obstructive airflow limitation. Conclusion(s): Half of this national cohort of patients hospitalised for COVID-19 experienced persistent breathlessness at follow up. The risk factors identified for post-COVID breathlessness should inform mechanistic work to understand causal processes and develop future interventions to improve outcomes in this growing population.

Effectiveness of a remote pulmonary rehabilitation program for patients with Chronic Obstructive Pulmonary Disease: A case series

Introduction: During the Coronavirus Pandemic, face to face Pulmonary Rehabilitation was suspended and an adapted remote service was developed without direct evidence of clinical efficacy. Aim(s): To determine whether the remote PR programme was an effective intervention. Method(s): COPD patients were included if they had completed 8 or more of a total of 12 sessions of the remote PR programme and must have completed the required outcome measures, pre- and post-PR which included;the CAT questionnaire, Hospital Anxiety and Depression Scale (HADS) and One-minute Sit to Stand (1STS). The data were investigated to determine if any differences pre- and post were clinically and statistically significant. Result(s): 31 COPD patients were included in the data analyses with 13 (41.9%) female patients and a mean age of 70.7 (SD+/-8.93) years. All objective measures showed an improvement that exceeded the minimally clinically important difference which indicates a clinically significant improvement. Mean difference in CAT= 2.3 units, p=0.025, HADS= 3 units, p=0.013, 1STS= 5 units, p<0.001. Conclusion(s): This remote PR intervention showed a clinically and statistically significant improvement in outcome measures suggesting that remote PR programmes for COPD can be effective in improving patients' health outcomes.

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.

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

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.

What factors influence mental health burden in patients recovering from Covid-19?

Background Respiratory teams should perform a holistic assessment of patients recovering from COVID-19 to identify both physical and psychological needs.1Patients may develop psychological sequelae such as anxiety, dysfunctional breathing, depression and post-traumatic stress disorder (PTSD). We investigated the psychological burden at follow-up in people admitted with COVID-19 and the factors associated with this. Methods SARS-CoV-2 swab-positive patients from two hospital sites had telephone follow-up 8-10 weeks post discharge. We conducted screening questionnaires including the Patient Health Questionnaire 2-item (PHQ-2) for depression and Trauma Screening Questionnaire (TSQ) for PTSD. Demographic, admission, co-morbidity data and symptom burden at follow up (quantified by a numerical rating scale) were also collected. Results 782 patients completed both screening questionnaires. Patients' baseline characteristics are shown in table 1. 71 (9.1%) and 60 (7.7%) patients screened positive for depression and PTSD respectively. Patients with a background of depression and anxiety were more likely to have higher PHQ-2 scores (11.6% and 11.8%, p<0.001);those with anxiety had higher TSQ scores (8.5%, p=0.009). Patients who had a greater symptom burden both at admission and at follow-up were significantly more likely to have positive PHQ-2 and TSQ scores. No difference in scores was found in patients who received positive-airway pressure treatment (5.2%) or who were admitted to ITU (11.8%). Patients who returned to work (53.7%) were less likely to have positive TSQ scores (p=0.006). Discussion In this large cohort, patients with a higher physical symptom burden at admission and follow-up are more likely to also have psychological burden and this may impact their ability to return to work. Current guidelines1 highlight mental health screening only for patients who had more severe disease, but our data suggest any patient may be affected. Whilst more work in this field is required, we suggest clinicians who encounter patients still recovering from COVID-19 should proactively screen for psychological burden and liaise with local psychology services to ensure holistic care is offered.

'Long-COVID': The need for multi-disciplinary working

Background: Patients discharged from hospital following admission for COVID-19 may have on-going sequelae and require multidisciplinary input to ensure optimal recovery and early detection of complications. We evaluated our COVID-19 follow-up service to understand on-going patient needs. Methods: The respiratory team at Trust hospital sites established a virtual post-COVID-19 clinic. A bespoke questionnaire was developed to capture demographic data, symptom burden and mental health outcomes to identify those who needed further support. All patients were offered blood tests and a repeat chest radiograph (CXR) if abnormal pre-discharge. (Table presented) Results: Of patients admitted between March and August 2020 with COVID-19, 908 were eligible for follow-up. 643 (71%) have been assessed thus far. 133 (15%) declined or were unreachable. Patients' demographic data are summarised in table 1. All patients, including the 5.4% who received CPAP/NIV and 11.1% admitted to intensive care, were offered virtual follow-up. Median follow-up was 63 (54-79) days from discharge. Persistent symptoms (i.e. same or worse since admission) included cough (23.0%), breathlessness (16.5%), myalgia (15.7%) and fatigue (14.4%). Some patients developed new symptoms including 'fuzzy head' (12%), diarrhoea or abdominal pain (8%). 11% and 9.3% were at risk of depression and post-traumatic stress disorder respectively. Under half (44.5%) felt they had fully recovered. Of the 363 who were eligible to return to work, 31.4% felt able to do so. 57.9% were immediately discharged from secondary care after their follow-up assessment. 28% had further virtual follow-up arranged, while 20.8% were scheduled for face-to-face respiratory follow-up. 23.5% had a subsequent repeat CXR or CT scan arranged. Patients who scored highly on mental health questionnaires were offered referral to local psychology services and 49% (n=64) agreed. Discussion Our data demonstrates a significant proportion of hospital inpatients develop physical or psychological sequelae after COVID-19, 'Long-COVID'. A significant number felt unable to return to work 9 weeks after discharge. Our virtual clinic provided a structured way to identify patients' on-going symptoms and demonstrates the importance of establishing structured multi-disciplinary pathways, particularly with referrals to physiotherapy, cardiology and neurology. We strongly recommend the development of clear follow-up protocols prior to the next wave of disease.

S58 The impact of smoking on symptom and radiological severity at COVID-19 follow up

S58 Table 1Patient characteristics for smokers and never smokers with follow up dataVariable (%)Never-smokersEx/current SmokersP - valueN356181-DemographicsAge *(years)60 ± 1665 ± 16<0.0001Male Sex (%)212 (60)122 (67)0.076Black, Asian, Minority Ethnic (BAME) (%)183 (51)63 (35)<.0001ComorbiditiesHypertension155 (44)68 (38)0.382Ischaemic Heart Disease32 (9)25 (14)0.088Diabetes93 (26)41 (23)0.392Respiratory Background65 (18)45 (25)0.073Hospital AdmissionAdmission NEWS2 Score4 (2–6)5 (2–6.25)0.838Intensive Care Admission39 (11)24 (13.3)0.462Symptom Burden at follow upBreathlessness rating 0–100 (0–2)1 (0–3)0.037Cough rating 0–100 (0–1)0 (0–1)0.594Fatigue rating 0–102 (0–5)2 (0–5)0.933How close to 100% do they feel90 (75–100)90 (75–100)0.969Returned to Work92/179 (51)40/133 (30)0.013MRC Dyspnoea scale (1–5)1 (1–2)2 (1–3)0.005CXR at follow upNormal (%)86/120 (72)43/69 (62)0.184Significantly improved (%)25/120 (21)19/69 (28)0.294Unchanged (%)01/69 (2)0.186Significantly Worsened (%)9/120 (8)6/69 (5)0.770*normally distributed parametric data with mean and standard deviationAll other scale data was non-parametric with median and interquartile ranges shownAbbreviations: NEWS2 (National Early Warning Score 2);MRC (Medical Research Council)ConclusionIn 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.ReferenceZhao Q., et al. J Med Virol 2020 Apr 15.

P56 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

P56 Table 1Demographics, co-morbidities, investigations, observations and Continuous Positive Airway Pressure (CPAP) data for all patientsVariable CPAP Success CPAP Failure p - value N 9 32 - Demographics Age 54 ± 15.4 61 ± 9.9 0.104 Male Sex (%) 6 (66.7) 21 (65.6) 0.954 Ethnicity – BAME (%) 3 (33.3) 22 (68.7) 0.054 BMI* 30.3 (28.1 – 37.0) 24.9 (22.9 – 28.1) 0.005 Comorbidities Hypertension (%) 5 (55.5) 19 (59.4) 0.837 Diabetes (%) 5 (55.5) 10 (31.3) 0.181 Ischaemic Heart Disease (%) 1 (11.1) 1 (3.1) 0.326 Hypercholesterolaemia (%) 5 (55.5) 8 (25) 0.082 Respiratory disease (%) 0 (0) 4 (12.5) 0.256 Smoking history (%) 0/8 (0) 12 (37.5) 0.023 Respiratory function prior to CPAP SpO2%* 91 (75.8 – 97.2) 90 (86 – 93) 0.203 FiO2% 71.7 ± 17.0 78.1 ± 13.8 0.251 Respiratory Rate 32.9 ± 8.4 33.4 ± 7.4 0.852 CPAP Number of days* 2 (1.5 – 3) 1 (1–2) 0.103 Max PEEP* 9.75 (9.13 – 10) 10 (10–12) 0.255 *Non-parametric data, therefore median and interquartile ranges presented. All other data are presented as means ± standard deviationAbbreviations: CXR – Chest X-rayConclusionIn 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.ReferenceNightingale R., et al. BMJ Open Respir Res 2020 Jul;7(1):e000639.

S53 What factors influence mental health burden in patients recovering from COVID-19?

S53 Table 1Patient characteristics and outcomesVariablePHQ-2p - valueTSQp-valueNegativePositive NegativePositive N71171 72260 DemographicsAge *62.0 ± 16.660.5 ± 16.90.47162.2 ± 16.857.3 ± 14.20.028Sex – Male (%)429 (60.3)35 (49.3)0.071438 (60.7)26 (43.3)0.009Ethnicity – White (%)286/573 (49.9)37/70 (52.9)0.642290/585 (49.6)33/58 (56.9)0.287Co-morbiditiesTotal number of co-morbidities4 (3–5)5 (3–6)0.1701 (0–3)2 (1–3)0.239Depression (%)34/683 (5)11/68 (16.2)<0.00139/692 (5.6)6/59 (10.2)0.159Anxiety (%)14/683 (2)8/68 (11.8)<0.00117/692 (2.5)5/59 (8.5)0.009Admission dataDuration of symptoms at admission in days7 (5–11)7 (4.5–9)0.2877 (5–11)7 (5–10)0.357Total number of symptoms (out of 16)4 (3–5)5 (3–6)0.0144 (3–5)4 (3–6)0.001 Positive airway pressure (CPAP or NIV)39 (5.5)2 (2.8)0.33637 (5.1)4 (6.7)0.607Admission to intensive care unit (ITU)81/674 (12)11/69 (15.9)0.34682/683 (12)10/60 (16.7)0.293Follow up dataBreathlessness rating 0–100 (0–2)2 (0–5)0.0030 (0–3)2 (0–4)<0.001Cough rating 0–100 (0–0)0 (0–3)0.0120 (0–0.5)0 (0–2)0.023Fatigue rating 0–102 (0–4)5 (3–7)<0.0012 (0–4)5 (3–7)<0.001Sleep quality rating 0–100 (0–4)3 (2–6)<0.0010 (0–3)5 (3–8)<0.001Symptom burden at follow-up (out of 7)4 (3–5)5 (3–6)<0.0010 (0–1)2 (1–2)<0.001Back to work122/216 (56.5)10/30 (33.3)0.060121/213 (56.8)11/33 (33.3)0.006ReferenceBritish Thoracic Society ( 2020). Guidance on respiratory follow up of patients with a clinico-radiological diagnosis of COVID-19 pneumonia.

P9 Do persistent chest radiograph changes correlate with ongoing respiratory symptoms in patients recovering from COVID-19 pneumonia?

P9 Table 1Differences in symptom burden in patients with improved vs. non-improved chest radiographsDemographicChest radiograph appearancep-valueImprovers n=356 (93%)Non-improvers n=26 (7%)Age (years)58.9 ± 14.763.23 ± 12.70.103BMI (kg/m2)27.7 ± 5.4326.7 ± 4.500.331Male sex (n,%)224 (62.9)21 (80.8)0.154BAME (n,%)165 (46.3)10 (38.5)0.268Current or ex-smoker (n,%)112 (31.4)9 (34.6)0.008Underlying respiratory disease (n,%)62 (17.4)3 (11.5)0.737ITU admission (n,%)41 (11.5)10 (38.5)<0.001Symptoms Breathlessness*1 (0 – 3)2 (0 – 4)0.010Cough*0 (0 –1)0 (0 – 2.5)0.090Fatigue*2 (0 – 5)2 (0.5 – 4.5)0.773How close back to 100% of usual do you feel?*90 (80 – 100)85 (75 – 97.5)0.500MRC dyspnoea scale*1 (1 – 2)1 (1 – 3)0.021*non-parametric data presented as median and IQR, all other data are presented as mean ± standard deviationConclusionsIn our cohort, patients recovering from COVID-19 pneumonia with a ‘non-improver’ chest radiograph are more likely to have been admitted to ITU and remain breathless at follow-up. We conclude that ‘non-improver’ chest radiographs at follow-up are an indicator of who may have ongoing respiratory pathology. These patients can thus be prioritised for further respiratory investigation.ReferencesBritish Thoracic Society (2020). Guidance on Respiratory Follow Up of Patients with a Clinico-Radiological Diagnosis of COVID-19 Pneumonia. https://www.brit-thoracic.org.uk/document-library/quality-improvement/covid-19/resp-follow-up-guidance-post-covid-pneumonia/British Society of Thoracic Imaging (2020). Post-COVID-19 CXR Report Codes. https://www.bsti.org.uk/media/resources/files/BSTI_PostCOVIDCXRtemplatefinal.28.05.201.pdf