Persistent somatic symptoms are key to individual illness perception at one year after COVID-19

BackgroundSequelae of Coronavirus disease 2019 (COVID-19) were investigated by both patient-initiated and academic initiatives. Patients subjective illness perceptions might differ from physicians clinical assessment results. Herein, we explored factors influencing patients perception during COVID-19 recovery. MethodsParticipants of the prospective observation CovILD study with persistent somatic symptoms or cardiopulmonary findings at the clinical follow-up one year after COVID-19 were analyzed (n = 74). Explanatory variables included baseline demographic and comorbidity data, COVID-19 course and one-year follow-up data of persistent somatic symptoms, physical performance, lung function testing (LFT), chest computed tomography (CT) and trans-thoracic echocardiography (TTE). Factors affecting illness perception (Brief Illness Perception Questionnaire, BIPQ) were identified by penalized multi-parameter regression and unsupervised clustering. ResultsIn modeling, 47% of overall illness perception variance at one year after COVID-19 was attributed to fatigue intensity, reduced physical performance, hair loss and baseline respiratory comorbidity. Overall illness perception was independent of LFT results, pulmonary lesions in CT or heart abnormality in TTE. As identified by clustering, persistent somatic symptom count, fatigue, diminished physical performance, dyspnea, hair loss and sleep problems at the one-year follow-up and severe acute COVID-19 were associated with the BIPQ domains of concern, emotional representation, complaints, disease timeline and consequences. ConclusionPersistent somatic symptoms rather than clinical assessment results, revealing lung and heart abnormalities, impact on severity and quality of illness perception at one year after COVID-19 and may foster unhelpful coping mechanisms. Besides COVID-19 severity, individual illness perception should be taken into account when allocating rehabilitation and psychological therapy resources. Study registrationClinicalTrials.gov: NCT04416100.

Comparison of different mechanical chest compression devices in the alpine rescue setting: a randomized triple crossover experiment.

BACKGROUND: Cardiopulmonary resuscitation in mountain environment is challenging. Continuous chest compressions during transport or hoist rescue are almost impossible without mechanical chest compression devices. Current evidence is predominantly based on studies conducted by urbane ambulance service. Therefore, we aimed to investigate the feasibility of continuous mechanical chest compression during alpine terrestrial transport using three different devices. METHODS: Randomized triple crossover prospective study in an alpine environment. Nineteen teams of the Austrian Mountain Rescue Service trained according to current ERC guidelines performed three runs each of a standardised alpine rescue-scenario, using three different devices for mechanical chest compression. Quality of CPR, hands-off-time and displacement of devices were measured. RESULTS: The primary outcome of performed work (defined as number of chest compressions x compression depth) was 66,062 mm (2832) with Corpuls CPR, 65,877 mm (6163) with Physio-Control LUCAS 3 and 40,177 mm (4396) with Schiller Easy Pulse. The difference both between LUCAS 3 and Easy Pulse (Δ 25,700; 95% confidence interval 21,118 - 30,282) and between Corpuls CPR and Easy Pulse (Δ 25,885; 23,590 - 28,181) was significant. No relevant differences were found regarding secondary outcomes. CONCLUSION: Mechanical chest compression devices provide a viable option in the alpine setting. For two out of three devices (Corpuls CPR and LUCAS 3) we found adequate quality of CPR. Those devices also maintained a correct placement of the piston even during challenging terrestrial transport. Adequate hands-off-times and correct placement could be achieved even by less trained personnel.

Investigating phenotypes of pulmonary COVID-19 recovery: a longitudinal observational prospective multicenter trial

BackgroundCOVID-19 is associated with long-term pulmonary symptoms and may result in chronic pulmonary impairment. The optimal procedures to prevent, identify, monitor, and treat these pulmonary sequelae are elusive. Research questionTo characterize the kinetics of pulmonary recovery, risk factors and constellations of clinical features linked to persisting radiological lung findings after COVID-19. Study design and methodsA longitudinal, prospective, multicenter, observational cohort study including COVID-19 patients (n = 108). Longitudinal pulmonary imaging and functional readouts, symptom prevalence, clinical and laboratory parameters were collected during acute COVID-19 and at 60-, 100- and 180-days follow-up visits. Recovery kinetics and risk factors were investigated by logistic regression. Classification of clinical features and study participants was accomplished by k-means clustering, the k-nearest neighbors (kNN), and naive Bayes algorithms. ResultsAt the six-month follow-up, 51.9% of participants reported persistent symptoms with physical performance impairment (27.8%) and dyspnea (24.1%) being the most frequent. Structural lung abnormalities were still present in 45.4% of the collective, ranging from 12% in the outpatients to 78% in the subjects treated at the ICU during acute infection. The strongest risk factors of persisting lung findings were elevated interleukin-6 (IL6) and C-reactive protein (CRP) during recovery and hospitalization during acute COVID-19. Clustering analysis revealed association of the lung lesions with increased anti-S1/S2 antibody, IL6, CRP, and D-dimer levels at the early follow-up suggesting non-resolving inflammation as a mechanism of the perturbed recovery. Finally, we demonstrate the robustness of risk class assignment and prediction of individual risk of delayed lung recovery employing clustering and machine learning algorithms. InterpretationSeverity of acute infection, and systemic inflammation is strongly linked to persistent post-COVID-19 lung abnormality. Automated screening of multi-parameter health record data may assist the identification of patients at risk of delayed pulmonary recovery and optimize COVID-19 follow-up management. Clinical Trial RegistrationClinicalTrials.gov: NCT04416100

Clinical validation of the quantitative Siemens SARS-CoV-2 spike IgG assay (sCOVG) reveals improved sensitivity and a good correlation with virus neutralization titers

ObjectivesSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections cause Coronavirus Disease 2019 (COVID-19) and induce a specific antibody response. Serological assays detecting IgG against the receptor binding domain (RBD) of the spike (S) protein are useful to monitor the immune response after infection or vaccination. The objective of our study was to evaluate the clinical performance of the Siemens SARS-CoV-2 IgG (sCOVG) assay. MethodsSensitivity and specificity of the Siemens sCOVG test were evaluated on 178 patients with SARS-CoV-2-infection and 160 pre-pandemic samples in comparison with its predecessor test COV2G. Furthermore, correlation with virus neutralization titers was investigated on 134 samples of convalescent COVID-19 patients. ResultsSpecificity of the sCOVG test was 99.4% and sensitivity was 90.5% (COV2G assay 78.7%; p<0.0001). S1-RBD antibody levels showed a good correlation with virus neutralization titers (r=0.843; p<0.0001) and an overall qualitative agreement of 98.5%. Finally, median S1-RBD IgG levels increase with age and were significantly higher in hospitalized COVID-19 patients (median levels general ward: 25.7 U/ml; intensive care: 59.5 U/ml) than in outpatients (3.8 U/ml; p<0.0001). ConclusionsPerformance characteristics of the sCOVG assay have been improved compared to the predecessor test COV2G. Quantitative SARS-CoV-2 S1-RBD IgG levels could be used as a surrogate for virus neutralization capacity. Further harmonization of antibody quantification might assist to monitor the humoral immune response after COVID-19 disease or vaccination.