Background/aim: This study aimed to distinguish different phenotypes of long COVID through the post-COVID syndrome (PCS) score based on long-term persistent symptoms following COVID-19 and evaluate whether these symptoms affect general health and work ability. In addition, the study identified predictors for severe long COVID. Method: This cluster analysis included cross-sectional data from three cohorts of patients after COVID-19: non-hospitalized (n = 401), hospitalized (n = 98) and those enrolled at the post-COVID outpatient’s clinic (n = 85). All the subjects responded to the survey on persistent long-term symptoms and sociodemographic and clinical factors. K-Means cluster analysis and ordinal logistic regression were used to create PCS scores that were used to distinguish patients’ phenotypes. Results: 506 patients with complete data on persistent symptoms were divided into three distinct phenotypes: none/mild (59%), moderate (22%) and severe (19%). The patients with severe phenotype, with the predominating symptoms were fatigue, cognitive impairment and depression, had the most reduced general health status and work ability. Smoking, snuff, body mass index (BMI), diabetes, chronic pain and symptom severity at COVID-19 onset were factors predicting severe phenotype. Conclusion: This study suggested three phenotypes of long COVID, where the most severe was associated with the highest impact on general health status and working ability. This knowledge on long COVID phenotypes could be used by clinicians to support their medical decisions regarding prioritizing and more detailed follow-up of some patient groups.

Rationale: Postbronchodilator spirometry is used for the diagnosis of chronic obstructive pulmonary disease. However, prebronchodilator reference values are used for spirometry interpretation. Objectives: To compare the resulting prevalence rates of abnormal spirometry and study the consequences of using pre- or postbronchodilator reference values generated within SCAPIS (Swedish CArdioPulmonary bioImage Study) when interpreting postbronchodilator spirometry in a general population. Methods: SCAPIS reference values for postbronchodilator and prebronchodilator spirometry were based on 10,156 and 1,498 never-smoking, healthy participants, respectively. We studied the associations of abnormal spirometry, defined by using pre- or postbronchodilator reference values, with respiratory burden in the SCAPIS general population (28,851 individuals). Measurements and Main Results: Bronchodilation resulted in higher predicted medians and lower limits of normal (LLNs) for FEV1/FVC ratios. The prevalence of postbronchodilator FEV1/FVC ratio lower than the prebronchodilator LLN was 4.8%, and that of postbronchodilator FEV1/FVC lower than the postbronchodilator LLN was 9.9%, for the general population. An additional 5.1% were identified as having an abnormal postbronchodilator FEV1/FVC ratio, and this group had more respiratory symptoms, emphysema (13.5% vs. 4.1%; P < 0.001), and self-reported physician-diagnosed chronic obstructive pulmonary disease (2.8% vs. 0.5%, P < 0.001) than subjects with a postbronchodilator FEV1/FVC ratio greater than the LLN for both pre- and postbronchodilation. Conclusions: Pre- and postbronchodilator spirometry reference values differ with regard to FEV1/FVC ratio. Use of postbronchodilator reference values doubled the population prevalence of airflow obstruction; this was related to a higher respiratory burden. Using postbronchodilator reference values when interpreting postbronchodilator spirometry might enable the identification of individuals with mild disease and be clinically relevant.

Background: Exertional breathlessness is a key symptom in cardiorespiratory disease and can be quantified using incremental exercise testing, but its prognostic significance is unknown. We evaluated the ability of abnormally high breathlessness intensity during incremental cycle exercise testing to predict all-cause, respiratory, and cardiac mortality. Study design and methods: Longitudinal cohort study of adults referred for exercise testing followed prospectively for mortality assessed using the Swedish National Causes of Death Registry. Abnormally high exertional breathlessness was defined as a breathlessness intensity response (Borg 0–10 scale) > the upper limit of normal using published reference equations. Mortality was analyzed using multivariable Cox regression, unadjusted and adjusted for age, sex, and body mass index. A further mortality analysis was also done adjusted for select common comorbidities in addition to age, sex and body mass index. Results: Of the 13,506 people included (46% female, age 59±15 years), 2,867 (21%) had abnormally high breathlessness during exercise testing. Over a median follow up of 8.0 years, 1,687 (12%) people died. No participant was lost to follow-up. Compared to those within normal predicted ranges, people with abnormally high exertional breathlessness had higher mortality from all causes (adjusted hazard ratio [aHR] 2.3, [95% confidence interval] 2.1–2.6), respiratory causes (aHR 5.2 [3.4–8.0]) and cardiac causes (aHR 3.0 [2.5–3.6]). Even among people with normal exercise capacity (defined as peak Watt ≥75% of predicted exercise capacity, n = 10,284) those with abnormally high exertional breathlessness were at greater risk of all-cause mortality than people with exertional breathlessness within the normal predicted range (aHR 1.5 [1.2–1.8]). Conclusion: Among people referred for exercise testing, abnormally high exertional breathlessness, quantified using healthy reference values, independently predicted all-cause, respiratory and cardiac mortality.

Fractional exhaled nitric oxide (FE_NO) is a marker of type 2 airway inflammation used in clinical practice in asthma. However, reference values are needed to broaden the clinical use of FE_NO and this is within the scope of a newly started Global Lung Function Initiative task force. We aim to study FE_NO levels with special emphasis on the upper limit of normal (ULN) in relation to the type and degree of IgE sensitisation. FE_NO was measured in 1855 non-smoking, respiratory healthy subjects from the Swedish CArdioPulmonary bioImage Study (SCAPIS). Atopic subjects (n = 424), defined as being IgE-sensitised to aeroallergens (ImmunoCAP Phadiatop™, ≥0.35 PAU/l) were compared to non-atopic subjects (<0.35 PAU/l, n = 1431). Atopic subjects were further characterised according to their grade of IgE sensitisation (IgE antibody tertiles: (T13.72 PAU/l) and sensitisation to perennial (cat or mite) or seasonal (birch) allergens. Subjects IgE-sensitised to cat or mite had higher FE_NO compared to non-atopic subjects (FE_NO (ppb): median 20.0 vs. 15.0, and ULN 50.4 vs. 33.0, p < 0.001). This was seen to a lesser extent for subjects IgE-sensitised to birch only (median 18.0 vs. 15.0, and ULN 38.0 vs. 33.0, p = 0.048). Atopic subjects with a high degree of IgE sensitisation (Phadiatop: >3.72 PAU/l) had the highest FE_NO compared to non-atopic subjects (median 20.0 vs. 15.0, and ULN 56.0 vs. 33.0, p < 0.001). The type and degree of IgE sensitisation should be considered in generating FE_NO reference values.

This study aimed to determine whether the EQ-5D-5L tool captures the most common persistent symptoms, such as fatigue, memory/concentration problems and dyspnea, in patients with post-COVID-19 conditions while also investigating if adding these symptoms improves the explained variance of the health-related quality of life (HRQoL). In this exploratory cross-sectional study, two cohorts of Swedish patients (n = 177) with a history of COVID-19 infection answered a questionnaire covering sociodemographic characteristics and clinical factors, and their HRQoL was assessed using EQ-5D-5L with the Visual Analogue Scale (EQ-VAS). Spearman rank correlation and multiple regression analyses were employed to investigate the extent to which the most common persistent symptoms, such as fatigue, memory/concentration problems and dyspnea, were explained by the EQ-5D-5L. The explanatory power of EQ-5D-5L for EQ-VAS was also analyzed, both with and without including symptom(s). We found that the EQ-5D-5L dimensions partly captured fatigue and memory/concentration problems but performed poorly in regard to capturing dyspnea. Specifically, the EQ-5D-5L explained 55% of the variance in memory/concentration problems, 47% in regard to fatigue and only 14% in regard to dyspnea. Adding fatigue to the EQ-5D-5L increased the explained variance of the EQ-VAS by 5.7%, while adding memory/concentration problems and dyspnea had a comparatively smaller impact on the explained variance. Our study highlights the EQ-5D-5L’s strength in capturing fatigue and memory/concentration problems in post-COVID-19 patients. However, it also underscores the challenges in assessing dyspnea in this group. Fatigue emerged as a notably influential symptom, significantly enhancing the EQ-5D-5L’s predictive ability for these patients’ EQ-VAS scores.