The study was designed as a cross-sectional study. It was conducted from June 2022 to April 2023 at the Klinik Bad Reichenhall, a pulmonary rehabilitation clinic owned by German pension fund (Deutschen Rentenversicherung Bayern-Süd; DRV Bayern-Süd). The study was registered in the German Register of Clinical Studies (DRKS-ID: DRKS00029236). It was approved by the Ethics Committee of the Medical Faculty of the Technical University of Munich (2022-199-S-SR).

Participation in the study was voluntary; neither refusal nor a later revision of the willingness to participate was associated with negative consequences for treatment and/or follow-up care. Inclusion criteria were a minimum age of 18, admission diagnosis of PCS, asthma or COPD, and sufficient German language skills. In Germany, inpatient rehabilitation is offered for patients with severe chronic diseases that could potentially lead to a reduction in work capacity. The diagnosis of PCS was accepted as a hospital admission diagnosis in the presence of persistent symptoms. The diagnoses of asthma or COPD were confirmed clinically by a pulmonologist on admission, using lung function investigation with whole-body plethysmography^18,21. The rehabilitation program is structured in accordance with the national and international recommendation guidelines for pulmonary rehabilitation^18,21. It comprises medical diagnostics and supervision, a graded physical exercise program, respiratory physiotherapy, patient education, and psychosocial support. The program is tailored to each patient’s individual needs. Furthermore, patients with PCS received psychological group therapy to help patients cope with their disease, and neurocognitive training sessions if symptoms of cognitive impairment persisted. All three rehabilitation programs are scheduled for 3 weeks.

Patients were informed about the study during the initial medical consultation and asked to participate. They received standardized written patient information which included general information about the study and its purpose as well as details on voluntariness, right of withdrawal, and data protection. All patients who agreed to participate completed a written informed consent form. The diagnoses were collected as part of routine admission diagnostics so that no additional effort was required from the patients. The aim was to include 200 patients with PCS,100 patients with asthma, and 100 with COPD. Given these sample sizes, even very low diagnostic accuracies – measured by the area under the receiver operating characteristic curves – of 0.58 and 0.61 would be detectable with a power of 80% at the 5% significance level under the conservative assumption of a low prevalence of 10% for the investigated outcome²⁵.

Data collection and questionnaires

Patients were given a list of the most common post-COVID symptoms³. Patients were asked to select each symptom that they experienced and that they subjectively attributed to the SARS-CoV-2 infection or asthma or COPD. Beyond that, patients were asked if they experienced DLI due to the SARS-CoV-2 infection or asthma or COPD. The response options were ‘no limitation’, ‘persistent sick leave’, ‘retired due to COVID-19 infection’, ‘I cannot do my everyday tasks as well as before the infection (e.g. shopping, household)’, ‘I cannot be as active in my leisure activities and hobbies as before the infection’. Multiple answers could be given. Beyond that, sociodemographic data like family status, education, and employment were inquired.

SSD is operationalized via the combined application of the Patient Health Questionnaire-15 (PHQ-15) and the Somatic Symptom Disorder-B Criteria Scale (SDD-12). The PHQ-15 assesses the presence and severity of frequent somatic symptoms (A-criterion according to DSM-5) within the last 4 weeks using 15 items. Each item refers to a symptom and is scaled as being ‘Not bothered at all’, ‘Bothered a little’ or ‘Bothered a lot’²⁶. The SSD-12 is a questionnaire consisting of 12 items to assess the B-criteria of SSD according to DSM-5 (psychological symptom burden in SSD). Each item is scaled on a 5-point Likert-scale ranging from 0 to 4 (0 = ‘never’, 1 = ‘rarely’, 2 = ‘sometimes’, 3 = ‘often’, 4 = ‘very often’)²⁷. When combining the PHQ-15 and SSD-12 in screening for SSD, good diagnostic accuracy was achieved by applying a cut-off of ≥ 9 points in the PHQ-15 and ≥ 23 points in the SSD-12²⁷.

Depression was captured with the Patient Health Questionnaire-9 (PHQ-9). The PHQ-9 comprises nine items that are scaled on a 4-point Likert-scale ranging from 0 (‘Not at all’) to 3 (‘nearly every day’). For the analysis, the item scores are summed up²⁸. The critical cut-off value is reported to be 10²⁹. A potentially existing comorbid anxiety disorder was determined with the Generalized Anxiety Disorder 7 (GAD-7) questionnaire. It comprises 7 Items that are scaled and analyzed such as the ones of the PHQ-9. Scores ≥ 5, ≥ 10, and ≥ 15 represent mild, moderate, and severe symptom severity, respectively³⁰.

Potential chronic fatigue or fatigue symptoms were assessed using the Fatigue Assessment Scale (FAS). The questionnaire consists of 10 items scaled on a 5-point Likert scale (1 =’never’, 2 = ‘sometimes’, 3 = ‘regularly’, 4 = ‘often’, 5 = ‘always’). A sum score of ≥ 22 to 34 points corresponds to mild to moderate fatigue. Scores ≥ 35 imply severe fatigue³¹.

The European Quality of Life 5 Dimensions 5 Level Version (EQ-5D-5 L) questionnaire measures the 5 dimensions of mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. The range extends from 0 (‘very poor’) to 1 (‘best possible state of health’). Another component of this questionnaire is the visual analog scale (EQ-VAS), scaled from 0 (minimum) to 100 (maximum quality of life). In COPD patients, the relevant clinical difference (‘minimally important difference’) was 0.051 for the EQ-5D-5 L and 6.9 for the EQ-VAS³².

Pulmonary function measurement was carried out as part of the routine examination using whole-body plethysmography. We assessed the following lung function parameters: forced expiratory volume in 1 s (FEV1), vital capacity (VC), and the measurement of the diffusion capacity of carbon monoxide (DLCO)³³. In addition, pre-existing diagnoses, and the basic data age, gender, and BMI were extracted from the patient file.

Data analysis

The distribution of baseline data, psychometric scales, and lung function parameters is presented using descriptive statistics. Group differences were tested for statistical significance using Mann-Whitney-U tests and chi-square tests. To determine the predictive value of the questionnaires and symptoms for DLI, univariable binary logistic regression models were calculated to estimate the odds ratios with 95% confidence intervals. DLI was dichotomized into ‘at least one impairment present’ versus ‘no impairment present’. DLI served as the dependent variable. The questionnaire scales were dichotomized using the above cut-off values and served as independent variables in separate models. Beyond that, the most common PCS symptoms ´fatigue´, ´shortness of breath´, and ´impaired cognition´^4,5 were used as independent variables. For this purpose, the symptoms ´concentration disorder´ and ´memory disorder´ were combined to form the variable ´impaired cognition´. An interaction effect between the predictor and a group indicator was included in each regression model to test for group differences. Receiver operating characteristics curves (ROC) were used to quantify the diagnostic performance of predictors for the prediction of everyday life impairment on their original scale, i.e. without dichotomization. In addition, the combined performance of multiple predictors was assessed using the predictions of the respective multiple binary regression models in this ROC analysis. The resulting areas under the curves (AUC) were compared between the groups using the DeLong test³⁴. AUC values ≥ 0.9 indicate ‘outstanding’, ≥ 0.8 ‘excellent’, and ≥ 0.7 ‘acceptable’ discrimination³⁵. All data available for each analysis was used in case of missing values. Statistical analysis was performed using R 4.1.3 (The R Foundation for Statistical Computing, Vienna, Austria) and SPSS 28.0 (IBM Corp., Armonk, NY).