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Letter to the editor.

The aim was to study discrimination, with a focus on gender and sexual harassment among medical students at Uppsala University in Sweden. A survey was sent via email to all registered medical students in the spring semester of 2020. Data were compared with two previous studies. Questions about gender and sexual harassment were the same as in the study conducted in 2002 and 2013. In addition, the 2020 survey included a question about other grounds of discrimination. Forty percent, that is, 453 out of 1,130 medical students, participated. The proportion of students reporting gender-based discrimination during the preclinical semesters was similar for females and males. During the clinical semesters, significantly more females than males reported gender discrimination (41% vs. 21.5%, p = 0.005) and sexual harassment (22% vs. 5%, p = 0.001). Physicians were the most commonly reported perpetrator. Reports about not being respected had increased from 2% to 20% between 2013 and 2020 among female clinical students. The prevalence of those who experienced several sexually harassing behaviors increased for the female and male clinical students and the female preclinical students. Receiving an unwelcome touch increased from 1% to 7% for the female clinical students. Discrimination due to ethnicity was reported by 36% of the students born in a country other than Sweden compared to 3% of those born in Sweden. Our findings confirm that experiences of different forms of discrimination exist in this medical school, and females and minorities are particularly affected.

BACKGROUND: Impulse oscillometry (IOS) is sensitive in detecting lung function impairment. In small studies, impaired IOS relates better to respiratory symptoms than spirometry. We studied how IOS related to spirometry and respiratory symptoms in a large population of individuals (n=10 360) in a cross-sectional analysis. METHODS: Normal values for IOS and spirometry were defined in healthy, never-smoking individuals, aged 50-64 years, from the Swedish CArdioPulmonary bioImage Study (n=3664 for IOS and 3608 for spirometry). For IOS, abnormal values for resistance at 5 Hz (R5) and at 20 Hz and area of reactance were defined using the 95th percentile. Abnormal reactance at 5 Hz for IOS and abnormal conventional spirometry indices (forced expiratory volume in 1 s (FEV1), forced and slow vital capacity and their ratios) were defined using the 5th percentile. RESULTS: Abnormal IOS parameters were found in 16% of individuals and were associated with increased odds ratios for nearly all respiratory symptoms when adjusted for age, gender and smoking. In individuals with normal spirometry, abnormal IOS resistance was related to cough and dyspnoea, while abnormal reactance was related to wheeze. In these individuals, the combination of abnormal R5 with abnormal reactance resulted in approximately two-fold higher likelihood for having cough, chronic bronchitis and dyspnoea, even when further adjusting for FEV1, expressed as % predicted. CONCLUSIONS: Abnormal IOS is related to increased respiratory burden in middle-aged individuals with normal spirometry, especially when resistance and reactance parameters are combined. The different relationships between respiratory symptoms and reactance and resistance warrant further research.

This study presents a separable nonlinear least squares (SNLLS) implementation of the minimum distance (MD) estimator employing a fixed-weight matrix for estimating structural equation models (SEMs). In contrast to the standard implementation of the MD estimator, in which the complete set of parameters is estimated using nonlinear optimization, the SNLLS implementation allows a subset of parameters to be estimated using (linear) least squares (LS). The SNLLS implementation possesses a number of benefits, such as faster convergence, better performance in ill-conditioned estimation problems, and fewer required starting values. The present work demonstrates that SNLLS, when applied to SEM estimation problems, significantly reduces the estimation time. Reduced estimation time makes SNLLS particularly useful in applications involving some form of resampling, such as simulation and bootstrapping.

Background: Allergic disease is common. The aim of this study was to look at the change in asthma and rhinitis over time and to characterise factors contributing to remission and persistence of disease. Methods: This cohort study included 255 individuals with or without asthma and or rhinitis that participated in a population survey and a follow-up 10 years later. The participants were tested for allergic sensitisation, total IgE, multiplex allergen component analysis and type-2 inflammatory markers: exhaled nitric oxide (FENO), eosinophil cationic protein (ECP) and eosinophil-derived neurotoxin (EDN). Results: Of the 132 healthy individuals, 112 remained healthy, 16 developed rhinitis, 4 asthma and rhinitis over the 10 years. Out of 82 subjects with rhinitis, 26 went into remission, 53 remained unchanged and 3 developed asthma in addition to rhinitis. None of the 41 participants with asthma and rhinitis went into remission. Subjects with persistent rhinitis and asthma had higher levels of total IgE (odds ratio [OR] 95% confidence interval [CI]: 6.16 [3.05-12.5]) at baseline and after 10 years, and FENO and ECP at baseline (OR per log unit increase, 95% CI 5.21 [1.20-22.7] and 6.32 [1.52-26.4], respectively), compared with those that remained healthy. Subjects with persistent rhinitis were more likely to be sensitised to grass pollen and had higher total IgE levels than those that went into remission. Individuals with persistent asthma were more likely to be sensitised to tree pollen and furry animals than those with only persistent rhinitis (OR 95% CI: 3.50 [1.29-9.49] and 6.73 [2.00-22.6], respectively). Conclusion: IgE sensitisation and total IgE levels are associated with the persistence of rhinitis and asthma. Participants with persistent allergic disease had higher levels of allergen sensitisation and type 2 inflammation markers at baseline than those who remained healthy.

BACKGROUND: Epidemiological studies have shown that impaired lung function is common and associated with increased risk of cardiovascular disease. Increased levels of several inflammatory and cardiovascular disease-related plasma proteins have been associated with impaired lung function. The aim was to study the association between plasma proteomics and forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC ratio. METHODS: We used a discovery and replication approach in two community-based cohorts, EpiHealth and the Malmö Offspring Study (total n=2874), to cross-sectionally study 242 cardiovascular disease- and metabolism-linked proteins in relation to FEV1, FVC (both % predicted) and FEV1/FVC ratio. A false discovery rate of 5% was used as the significance threshold in the discovery cohort. RESULTS: Plasma fatty acid-binding protein 4, interleukin-1 receptor antagonist, interleukin-6 and leptin were negatively associated with FEV1 and paraoxonase 3 was positively associated therewith. Fatty acid-binding protein 4, fibroblast growth factor 21, interleukin-1 receptor antagonist, interleukin-6 and leptin were negatively associated with FVC and agouti-related protein, insulin-like growth factor-binding protein 2, paraoxonase 3 and receptor for advanced glycation end products were positively associated therewith. No proteins were associated with FEV1/FVC ratio. A sensitivity analysis in EpiHealth revealed only minor changes after excluding individuals with known cardiovascular disease, diabetes or obesity. CONCLUSIONS: Five proteins were associated with both FEV1 and FVC. Four proteins associated with only FVC and none with FEV1/FVC ratio, suggesting associations mainly through lung volume, not airway obstruction. However, additional studies are needed to investigate underlying mechanisms for these findings.

RATIONALE: Post-bronchodilator (BD) spirometry is used for diagnosis of chronic obstructive pulmonary disease (COPD). However, pre-BD 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 post-BD reference values generated within the Swedish CArdioPulmonary bioImage Study (SCAPIS) when interpreting post-BD spirometry in a general population. METHODS: SCAPIS reference values for post-BD and pre-BD 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 post-BD reference values, with respiratory burden in the SCAPIS general population (28,851 individuals). MEASUREMENTS AND MAIN RESULTS: Bronchodilation resulted in higher predicted median and lower limit of normal (LLN) for FEV1/FVC ratio. The prevalence of post-BD FEV1/FVC < pre-bronchodilator LLN was 4.8% and that of post-BD FEV1/FVC < post-bronchodilator LLN was 9.9% for the general population. An additional 5.1% was identified as having an abnormal post-BD FEV1/FVC ratio and this group had more respiratory symptoms, emphysema (13.5% vs. 4.1%, p<0.001) and self-reported physician-diagnosed COPD (2.8% vs. 0.5%, p<0.001) than subjects with post-BD FEV1/FVC ratio > LLN for both pre- and post-bronchodilation). CONCLUSIONS: Pre- and post-bronchodilator spirometry reference values differ with regard to FEV1/FVC ratio. Use of post-bronchodilator reference values doubled the population prevalence of airflow obstruction; this was related to a higher respiratory burden. Using post-bronchodilator reference values when interpreting post-bronchodilator spirometry might enable identification of individuals with mild disease and be clinically relevant.

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.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with variable mortality risk. The aim of our investigation was to validate a simple clinical algorithm for long-term mortality previously proposed by Burgel et al. in 2017. Subjects with COPD from two cohorts, the Swedish PRAXIS study (n = 784, mean age (standard deviation (SD)) 64.0 years (7.5), 42% males) and the Rotterdam Study (n = 735, mean age (SD) 72 years (9.2), 57% males), were included. Five clinical clusters were derived from baseline data on age, body mass index, dyspnoea grade, pulmonary function and comorbidity (cardiovascular disease/diabetes). Cox models were used to study associations with 9-year mortality. The distribution of clinical clusters (1-5) was 29%/45%/8%/6%/12% in the PRAXIS study and 23%/26%/36%/0%/15% in the Rotterdam Study. The cumulative proportion of deaths at the 9-year follow-up was highest in clusters 1 (65%) and 4 (72%), and lowest in cluster 5 (10%) in the PRAXIS study. In the Rotterdam Study, cluster 1 (44%) had the highest cumulative mortality and cluster 5 (5%) the lowest. Compared with cluster 5, the meta-analysed age- and sex-adjusted hazard ratio (95% confidence interval) for cluster 1 was 6.37 (3.94-10.32) and those for clusters 2 and 3 were 2.61 (1.58-4.32) and 3.06 (1.82-5.13), respectively. Burgel's clinical clusters can be used to predict long-term mortality risk. Clusters 1 and 4 are associated with the poorest prognosis, cluster 5 with the best prognosis and clusters 2 and 3 with intermediate prognosis in two independent cohorts from Sweden and the Netherlands.

This study presents a separable nonlinear least squares (SNLLS) implementation of the minimum distance (MD) estimator employing a fixed-weight matrix for estimating structural equation models (SEMs). In contrast to the standard implementation of the MD estimator, in which the complete set of parameters is estimated using nonlinear optimization, the SNLLS implementation allows a subset of parameters to be estimated using (linear) least squares (LS). The SNLLS implementation possesses a number of benefits, such as faster convergence, better performance in ill-conditioned estimation problems, and fewer required starting values. The present work demonstrates that SNLLS, when applied to SEM estimation problems, significantly reduces the estimation time. Reduced estimation time makes SNLLS particularly useful in applications involving some form of resampling, such as simulation and bootstrapping.

To search for colorectal cancer (CRC) risk loci, Swedish samples were used for a genome-wide haplotype analysis. A logistic regression model was employed in 2663 CRC cases and 1642 controls in the discovery analysis. Three analyses were done, on all, familial-, and nonfamilial CRC samples and only results with odds ratio (OR) > 1 were analyzed. single nucleotide polymorphism (SNP) analysis did not generate any statistically significant results. Haplotype analysis suggested novel loci, on chromosome 2q36.1 (OR = 1.71, p value = 5.6924 × 10-8 ) in all CRC samples, chromosome 1q43 (OR = 4.04 p value = 3.24 × 10-8 ) in familial CRC samples, and two hits in nonfamilial CRC samples, chromosomes 2q36.1 (OR = 1.71 p value = 5.69 × 10-8 ) and 3p24.3 (OR = 1.62 p value = 6.21 × 10-9 ). Moreover, one locus on chromosome 20q13.33 was suggested in analyses of all samples, and five more novel loci were suggested on chromosomes 10q25.3, 15q,22.31, 17p11.2, 1p34.2, and 3q24. The haplotypes from the analysis of all samples were replicated in a second study of CRC cases and controls from the same part of Sweden. In summary, using haplotype analysis in Swedish CRC samples, the best hits were novel loci and the locus on chromosomes 2q36.1 and 20q13.33 suggested in the analysis of all samples were confirmed in a second cohort. The ORs were often higher than ORs from published genome-wide association study (GWAS). The study suggested it was possible that a risk locus could involve more than one gene, and that haplotypes could give information on the gene or genes possibly involved in the risk at specific locus.

Impulse oscillometry (IOS) can be used to assess the mechanical properties of the respiratory airways. The method is easy to perform as it requires only tidal breathing and may provide complimentary information beyond that from dynamic spirometry. For the method to be clinically useful, reference values appropriate with regard to methodology and population are needed. The IOS equipment producer recommended reference values are derived from a German population[1], while method specific reference values for healthy non-smoking adult Caucasian are available from smaller datasets from Europe[2] and Australia[3].