Variations and Predictors of Post-COVID Syndrome Severity in Patients Attending a Post-COVID Outpatient Clinic.
Christina LemhöferThomas BahmerPhilipp BaumbachBianca BesteherAndrea BoekelKathrin FinkeKatrin KatzerKatja Lehmann-PohlJan-Christoph LewejohannDana Loudovici-KrugMatthias NowkaChristian PutaStefanie QuickertPhilipp Alexander ReukenMartin WalterAndreas StallmachPublished in: Journal of clinical medicine (2023)
A relevant proportion of patients suffer from long-lasting impairments following an acute SARS-CoV-2 infection. The proposed post-COVID syndrome (PCS) score may improve comparison in the course and classification of affected patients. A prospective cohort of 952 patients presenting to the post-COVID outpatient clinic at Jena University Hospital, Germany, was enrolled. Patients received a structured examination. PCS score was calculated per visit. A total of 378 (39.7%) and 129 (13.6%) patients of the entire population visited the outpatient clinic two or three times, respectively (female: 66.4%; age: 49.5 (SD = 13) years). The initial presentation took place, on average, 290 (SD = 138) days after acute infection. The most frequently reported symptoms were fatigue (80.4%) and neurological impairments (76.1%). The mean PCS scores of patients with three visits were 24.6 points (SD = 10.9), 23.0 points (SD = 10.9) and 23.5 points (SD = 11.5) ( p = 0.407), indicating moderate PCS. Female sex ( p < 0.001), preexisting coagulation disorder ( p = 0.021) and coronary artery disease ( p = 0.032) were associated with higher PCS scores. PCS is associated with a multitude of long-lasting problems. The PCS score has proven its capability to objectify and quantify PCS symptoms in an outpatient setting. The influence of therapeutic measures on various PCS aspects should be the subject of further analyses.
Keyphrases
- end stage renal disease
- ejection fraction
- chronic kidney disease
- coronavirus disease
- sars cov
- coronary artery disease
- prognostic factors
- peritoneal dialysis
- machine learning
- mental health
- cardiovascular disease
- deep learning
- acute coronary syndrome
- brain injury
- atrial fibrillation
- left ventricular
- patient reported
- extracorporeal membrane oxygenation
- acute respiratory distress syndrome