Patient outcomes after hospitalisation with COVID-19 and implications for follow-up: results from a prospective UK cohort.

The longer-term consequences of SARS-CoV-2 infection are uncertain. Consecutive patients hospitalised with COVID-19 were prospectively recruited to this observational study (n=163). At 8-12 weeks postadmission, survivors were invited to a systematic clinical follow-up. Of 131 participants, 110 attended the follow-up clinic. Most (74%) had persistent symptoms (notably breathlessness and excessive fatigue) and limitations in reported physical ability. However, clinically significant abnormalities in chest radiograph, exercise tests, blood tests and spirometry were less frequent (35%), especially in patients not requiring supplementary oxygen during their acute infection (7%). Results suggest that a holistic approach focusing on rehabilitation and general well-being is paramount.

Toward Respiratory Assessment Using Depth Measurements from a Time-of-Flight Sensor.

Introduction: There is increasing interest in technologies that may enable remote monitoring of respiratory disease. Traditional methods for assessing respiratory function such as spirometry can be expensive and require specialist training to perform and interpret. Remote, non-contact tracking of chest wall movement has been explored in the past using structured light, accelerometers and impedance pneumography, but these have often been costly and clinical utility remains to be defined. We present data from a 3-Dimensional time-of-flight camera (found in gaming consoles) used to estimate chest volume during routine spirometry maneuvres. Methods: Patients were recruited from a general respiratory physiology laboratory. Spirometry was performed according to international standards using an unmodified spirometer. A Microsoft Kinect V2 time-of-flight depth sensor was used to reconstruct 3-dimensional models of the subject's thorax to estimate volume-time and flow-time curves following the introduction of a scaling factor to transform measurements to volume estimates. The Bland-Altman method was used to assess agreement of model estimation with simultaneous recordings from the spirometer. Patient characteristics were used to assess predictors of error using regression analysis and to further explore the scaling factors. Results: The chest volume change estimated by the Kinect camera during spirometry tracked respiratory rate accurately and estimated forced vital capacity (FVC) and vital capacity to within ± <1%. Forced expiratory volume estimation did not demonstrate acceptable limits of agreement, with 61.9% of readings showing >150 ml difference. Linear regression including age, gender, height, weight, and pack years of smoking explained 37.0% of the variance in the scaling factor for volume estimation. This technique had a positive predictive value of 0.833 to detect obstructive spirometry. Conclusion: These data illustrate the potential of 3D time-of-flight cameras to remotely monitor respiratory rate. This is not a replacement for conventional spirometry and needs further refinement. Further algorithms are being developed to allow its independence from spirometry. Benefits include simplicity of set-up, no specialist training, and cost. This technique warrants further refinement and validation in larger cohorts.

The physiological consequences of different distributions of diffuse pleural thickening on CT imaging.

OBJECTIVE: Diffuse pleural thickening (DPT) refers to extensive visceral pleural fibrosis with adhesion formation to the parietal pleura obliterating the pleural space. The radiological definition of DPT remains controversial with most of the literature requiring the presence of an obliterated costophrenic angle (CPA) for defining DPT. We conducted a study to investigate the variable distributions of DPT and associated lung function deficit. METHODS: 85 patients referred to a pleural clinic with suspected pleural thickening were screened for our study. Data were collected from 37 patients with DPT confirmed on CT by size criteria (≥3 mm thick, ≥5 cm wide and ≥8 cm in length), and 21 controls with pleural plaques but no other pleuroparenchymal pathology. 27 patients were excluded. Groups were matched to age, body mass index and smoking history. RESULTS: The percentage of predicted forced vital capacity showed a gradual decline from 98.9% for the control group to 83.5% in the DPT without CPA obliteration group (p < 0.05), to 79.5% in the unilateral DPT group (p < 0.001) and 66.7% in the bilateral group (p < 0.001). Similar reductions were seen in the percentage of predicted total lung capacity in the DPT with no CPA obliteration group and the bilateral DPT group. CONCLUSION: Our study shows an incremental reduction in the forced vital capacity and total lung capacity in DPT without CPA obliteration, unilateral and bilateral DPT when compared with a matched control group. Advances in knowledge: Different distributions of DPT including no CPA obliteration can cause respiratory impairment, with bilateral DPT being the worst affected.

Remote, Depth-Based Lung Function Assessment.

OBJECTIVE: We propose a remote, noninvasive approach to develop pulmonary function testing (PFT) using a depth sensor. METHOD: After generating a point cloud from scene depth values, we construct a three-dimensional model of the subject's chest. Then, by estimating the chest volume variation throughout a sequence, we generate volume-time and flow-time data for two prevalent spirometry tests: forced vital capacity (FVC) and slow vital capacity (SVC). Tidal volume and main effort sections of volume-time data are analyzed and calibrated separately to remove the effects of a subject's torso motion. After automatic extraction of keypoints from the volume-time and flow-time curves, seven FVC ( FVC, FEV1, PEF, FEF 25%, FEF 50%, FEF 75%, and FEF [Formula: see text]) and four SVC measures ( VC, IC, TV, and ERV) are computed and then validated against measures from a spirometer. A dataset of 85 patients (529 sequences in total), attending respiratory outpatient service for spirometry, was collected and used to evaluate the proposed method. RESULTS: High correlation for FVC and SVC measures on intra-test and intra-subject measures between the proposed method and the spirometer. CONCLUSION: Our proposed depth-based approach is able to remotely compute eleven clinical PFT measures, which gives highly accurate results when evaluated against a spirometer on a dataset comprising 85 patients. SIGNIFICANCE: Experimental results computed over an unprecedented number of clinical patients confirm that chest surface motion is linearly related to the changes in volume of lungs, which establishes the potential toward an accurate, low-cost, and remote alternative to traditional cumbersome methods, such as spirometry.