BackgroundA standardised approach to assessing COVID-19 survivors has not been established, largely due to the paucity of data on medium- and long-term sequelae. Interval chest radiograph is recommended following community-acquired pneumonia, however its utility in monitoring recovery from COVID-19 pneumonia remains unclear.MethodsProspective single-centre observational cohort study. Patients hospitalised with severe COVID-19 pneumonia (admission duration ≥48 h and oxygen requirement ≥40% or critical care admission) underwent face-to-face assessment 4–6 weeks post-discharge. Primary outcome: radiological resolution of COVID-19 pneumonitis (Radiographic Assessment of Lung Oedema score <5). Secondary outcomes: clinical outcomes, symptom questionnaires, mental health screening (Trauma Screening Questionnaire, GAD-7, PHQ-9), physiological testing (4-metre gait speed (4MGS), 1-minute sit-to-stand test (STS)).Results119 patients assessed between 3rd June and 2nd July 2020 at median (IQR) 61 (51–67) days post-discharge. Mean±sd age 58.7±14.4 years, body mass index 30.0 (25.9–35.2) kg·m−2, 62% male, 68% ethnic minority. Despite radiographic resolution of pulmonary infiltrates in 87%, mMRC breathlessness scores were above pre-COVID baseline in 46% and patients reported persistent fatigue (68%), sleep disturbance (57%) and breathlessness (32%). Screening thresholds were breached for post-traumatic stress disorder (25%), anxiety (22%) and depression (18%). 4MGS was slow (<0.8 m·s−1) in 38%, 35% desaturated by ≥4% during STS. Of 56 thoracic computed tomography scans performed, 75% demonstrated COVID-related interstitial and/or airways disease.ConclusionsPersistent symptoms, adverse mental health outcomes and physiological impairment are common 2 months after severe COVID-19 pneumonia. Follow-up chest radiograph is a poor marker of recovery, therefore holistic face-to-face assessment is recommended to facilitate early recognition and management of post-COVID sequelae.

There have been significant recent advances in the understanding of the pathophysiology of pulmonary hypertension, and a growing number of therapeutic agents have become available to the treating physician. Traditional methods of diagnosing and monitoring this condition have comprised echocardiography and right heart catheterisation, in addition to functional measures, such as estimation of functional class and the 6-min walk test. An increasing number of biomarkers have been described that are elevated in pulmonary hypertension and which may assist the clinician in diagnosis and in the assessment of disease severity and response to treatment.The present article details the more important biomarkers, their potential applications and the evidence supporting their use.

BackgroundOver 30% of adult patients with pleural infection either die and/or require surgery. There is no robust means of predicting at baseline presentation which patients will suffer a poor clinical outcome. A validated risk prediction score would allow early identification of high-risk patients, potentially directing more aggressive treatment thereafter.ObjectivesTo prospectively assess a previously described risk score (RAPID - Renal (urea), Age, fluid Purulence, Infection source, Dietary (albumin)) in adults with pleural infection.MethodsProspective observational cohort study recruiting patients undergoing treatment for pleural infection. RAPID score and risk category were calculated at baseline presentation. The primary outcome was mortality at 3 months; secondary outcomes were mortality at 12 months, length of hospital stay, need for thoracic surgery, failure of medical treatment, and lung function at 3 months.ResultsMortality data were available in 542 of 546 (99.3%) patients recruited. Overall mortality was 10% (54/542) at 3 months and 19% (102/542) at 12 months. The RAPID risk category predicted mortality at 3 months; low-risk (RAPID score 0–2) mortality 5/222 (2.3%, 95%CI 0.9 to 5.7), medium-risk (RAPID score 3–4) mortality 21/228 (9.2%, 95%CI 6.0 to 13.7), and high-risk (RAPID score 5–7) mortality 27/92 (29.3%, 95%CI 21.0 to 39.2). C-statistics for the score at 3 and 12 months were 0.78 (95%CI 0.71 to 0.83) and 0.77 (95%CI 0.72 to 0.82) respectively.ConclusionsThe RAPID score stratifies adults with pleural infection according to increasing risk of mortality and should inform future research directed at improving outcomes in this patient population.

Exhaled breath contains hundreds of volatile organic compounds (VOCs) that may be used as non-invasive markers of lung disease. Electronic noses (e-noses) can analyse VOCs by composite nanosensor arrays with learning algorithms. This study investigated the use of an e-nose (Cyranose C320) to distinguish the breath of smokers from that of non-smokers. Smoking and non-smoking subjects exhaled from total lung capacity into a 2 L Tedlar bag and these samples were introduced offline to the e-nose in a random order. Two classes of breath, 'smoker' and 'non-smoker', were established and this model was then cross-validated. Principal component analysis then identified the maximal point of difference between classes. Smellprints of breath from smokers were separated from those of non-smokers (cross-validation value, 95%; Mahalanobis distance, 3.96). Subsequently, 15 smokers (mean age 37.9 ± 4.78 years, FEV(1) 3.15 ± 0.21 L), and 24 non-smokers (add mean age and FEV1 as for smokers) were sampled to revalidate the model. The e-nose correctly identified the smoking status in 37 of the 39 subjects. This demonstrates that the e-nose is simple to use in clinical practice and can differentiate the breath of smokers from that of non-smokers. It may prove to be a useful, non-invasive tool for further breath assessment of exposure to other inhaled noxious substances as well as disease monitoring.

Non-invasive biomarker assessment may provide useful information in exacerbation of obstructive lung diseases, particularly sputum IP-10 and neopterin and EBC pH.