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Background: The digitalization of information systems allows automatic measurement of antimicrobial consumption (AMC), helping address antibiotic resistance from inappropriate drug use without compromising patient safety.

Objectives: Describe and characterize a new automated AMC surveillance service for intensive care units (ICUs), with data stratified by referral clinic and linked with individual patient risk factors, disease severity, and mortality.

Methods: An automated service collecting data from the electronic medical record was developed, implemented, and validated in a healthcare region in northern Sweden. We performed an observational study from January 1, 2018, to December 31, 2021, encompassing general ICU care for all ≥18-years-olds in a catchment population of 270000 in secondary care and 900000 in tertiary care. We used descriptive analyses to associate ICU population characteristics with AMC outcomes over time, including days of therapy (DOT), length of therapy, defined daily doses, and mortality.

Results: There were 5608 admissions among 5190 patients with a median age of 65 (IQR 48-75) years, 41.2% females. The 30-day mortality was 18.3%. Total AMC was 1177 DOTs in secondary and 1261 DOTs per 1000 patient days and tertiary care. AMC varied significantly among referral clinics, with the highest total among 810 general surgery admissions in tertiary care at 1486 DOTs per 1000 patient days. Case-mix effects on the AMC were apparent during COVID-19 waves highlighting the need to account for case-mix. Patients exposed to more than three antimicrobial drug classes (N = 242) had a 30-day mortality rate of 40.6%, with significant variability in their expected rates based on admission scores.

Conclusion: We introduce a new service and instructions for automating local ICU-AMC data collection. The versatile long-term ICU-AMC metrics presented, covering patient factors, referral clinics and mortality outcomes, are expected to be beneficial in refining antimicrobial drug use.

Background: Olfactory dysfunction together with neurological and cognitive symptoms are common after COVID-19. We aimed to study whether performance on olfactory and neuropsychological tests following infection predict post-COVID condition (PCC), persisting symptoms, and reduced health-related quality of life.

Methods: Both hospitalized (N = 10) and non-hospitalized individuals (N = 56) were enrolled in this prospective cohort study. Participants were evaluated 1–3 months after infection with an olfactory threshold test and neuropsychological tests, which was used as predictors of PCC. A questionnaire outlining persisting symptoms and the validated instrument EuroQol five-dimension five-level for health-related quality of life assessment were used as outcome data 1 year after infection (N = 59). Principal component analysis was used to identify relevant predictors for PCC at 1 year.

Results: Objectively assessed olfactory dysfunction at 1–3 months post infection, but not subjective olfactory symptoms, predicted post-COVID condition with reduced health-related quality of life (PCC+) at 1 year. The PCC+ group scored more often below the cut off for mild cognitive impairment on the Montreal Cognitive Assessment (61.5% vs. 21.7%) and higher on the Multidimensional Fatigue Inventory-20, compared to the group without PCC+.

Conclusion: Our results indicate that objectively assessed, olfactory dysfunction is a predictor for PCC+. These findings underscore the importance of objective olfactory testing. We propose that olfactory screening in the early post-acute phase of COVID-19 infection might identify individuals that are at higher risk of developing long-term health sequalae.

We previously demonstrated that the lungs of deceased COVID-19 patients were filled with a clear hydrogel consisting of hyaluronan (HA). In this translational study, we investigated the role of HA at all stages of COVID-19 disease to map the consequences of elevated HA on morbidity and identify the mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced HA production. A reduced alveolar surface area was observed in the lungs of deceased COVID-19 patients compared to healthy controls, as visualized by a 3D rendering of lung morphology using light-sheet fluorescence microscopy. We confirmed the presence of HA in lung biopsies and found large quantities of proinflammatory fragmented HA. The association of systemic HA in blood plasma and disease severity was assessed in patients with mild (WHO Clinical Progression Scale, WHO-CPS, 1–5) and severe COVID-19 (WHO-CPS, 6–9) during the acute and convalescent phases and related to lung function. We found that systemic levels of HA were high during acute COVID-19 disease, remained elevated during convalescence, and were associated with a reduced diffusion capacity. In vitro 3D-lung models, differentiated from primary human bronchial epithelial cells, were used to study the effects of SARS-CoV-2 infection on HA metabolism, and transcriptomic analyses revealed a dysregulation of HA synthases and hyaluronidases, both contributing to increased HA in apical secretions. Furthermore, corticosteroid treatment reduced the inflammation and downregulated HA synthases. Our findings demonstrate that HA plays a role in COVID-19 morbidity and that sustained elevated HA concentrations may contribute to long-term respiratory impairment.

Background: The long-term sequelae after COVID-19 constitute a challenge to public health and increased knowledge is needed. We investigated the prevalence of self-reported persistent symptoms and reduced health-related quality of life (HRQoL) in relation to functional exercise capacity, 6 months after infection, and explored risk factors for COVID-19 sequalae.

Methods: This was a prospective, multicenter, cohort study including 434 patients. At 6 months, physical exercise capacity was assessed by a 1-minute sit-to-stand test (1MSTST) and persistent symptoms were reported and HRQoL was evaluated through the EuroQol 5-level 5-dimension (EQ-5D-5L) questionnaire. Patients with both persistent symptoms and reduced HRQoL were classified into a new definition of post-acute COVID syndrome, PACS+. Risk factors for developing persistent symptoms, reduced HRQoL and PACS+ were identified by multivariable Poisson regression.

Results: Persistent symptoms were experienced by 79% of hospitalized, and 59% of non-hospitalized patients at 6 months. Hospitalized patients had a higher prevalence of self-assessed reduced overall health (28 vs. 12%) and PACS+ (31 vs. 11%). PACS+ was associated with reduced exercise capacity but not with abnormal pulse/desaturation during 1MSTST. Hospitalization was the most important independent risk factor for developing persistent symptoms, reduced overall health and PACS+.

Conclusion: Persistent symptoms and reduced HRQoL are common among COVID-19 survivors, but abnormal pulse and peripheral saturation during exercise could not distinguish patients with PACS+. Patients with severe infection requiring hospitalization were more likely to develop PACS+, hence these patients should be prioritized for clinical follow-up after COVID-19.

Background: Severe COVID-19 increases the risk for long-term respiratory impairment, but data after mild COVID-19 are scarce. Our aims were to determine risk factors for reduced respiratory function 3–6 months after COVID-19 infection and to investigate if reduced respiratory function would relate to impairment of exercise performance and breathlessness. Methods: Patients with COVID-19 were enrolled at the University Hospitals of Umeå and Örebro, and Karlstad Central Hospital, Sweden. Disease severity was defined as mild (nonhospitalized), moderate (hospitalized with or without oxygen treatment), and severe (intensive care). Spirometry, including diffusion capacity (DLCO), was performed 3–6 months after hospital discharge or study enrollment (for nonhospitalized patients). Breathlessness (defined as ≥1 according to the modified Medical Research Council scale) and functional exercise capacity (1-min sit-to-stand test; 1-MSTST) were assessed. Results: Between April 2020 and May 2021, 337 patients were enrolled in the study. Forced vital capacity and DLCO were significantly lower in patients with severe COVID-19. Among hospitalized patients, 20% had reduced DLCO, versus 4% in nonhospitalized. Breathlessness was found in 40.6% of the participants and was associated with impaired DLCO. A pathological desaturation or heart rate response was observed in 17% of participants during the 1-MSTST. However, this response was not associated with reduced DLCO. Conclusion: Reduced DLCO was the major respiratory impairment 3–6 months following COVID-19, with hospitalization as the most important risk factor. The lack of association between impaired DLCO and pathological physiological responses to exertion suggests that these physiological responses are not primarily related to decreased lung function.

Uncontrolled release of damage-associated molecular patterns (DAMPs) is suggested to be a major trigger for the dysregulated host immune response that leads to severe COVID-19. Cold-inducible RNA-binding protein (CIRP), is a newly identified DAMP that aggravates inflammation and tissue injury, and induces respiratory failure in sepsis. Whether CIRP contributes to the pathogenesis of respiratory failure in COVID-19 has not yet been explored.

Aim: To investigate if the concentration of extracellular CIRP (eCIRP) in serum associates with respiratory failure and lung involvement by chest computed tomography (CT) in COVID-19.

Methods: Herein we report a prospective observational study of patients with COVID-19 included at two University Hospitals in Sweden between April 2020 and May 2021. Serum from hospitalized patients in Örebro (N=97) were used to assess the association between eCIRP and the level of respiratory support and its correlation with pulmonary involvement on chest CT and inflammatory biomarkers. A cohort of hospitalized and non-hospitalized patients from Umeå (N=78) was used as an external validation cohort. The severity of disease was defined according to the highest degree of respiratory support; mild disease (no oxygen), non-severe hypoxemia (conventional oxygen or high-flow nasal oxygen, HFNO <50% FiO2), and severe hypoxemia (HFNO ≥50% FiO2, mechanical ventilation). Unadjusted and adjusted linear regression was used to evaluate peak eCIRP day 0-4 in respect to severity, age, sex, Charlson comorbidity score, symptom duration, and BMI.

Results: Peak eCIRP concentrations were higher in patients with severe hypoxemia and were independently associated with the degree of respiratory support in both cohorts (Örebro; p=0.01, Umeå; p<0.01). The degree of pulmonary involvement measured by CT correlated with eCIRP, r_s=0.30, p<0.01 (n=97).

Conclusion: High serum levels of eCIRP are associated with acute respiratory failure in COVID-19. Experimental studies are needed to determine if treatments targeting eCIRP reduces the risk of acute respiratory failure in COVID-19.

Background: Standard diagnostic methods for lower respiratory tract infections are currently too slow and insensitive to guide early clinical decisions concerning treatment and isolation. Syndrome-specific, diagnostic panels have potential to provide information about aetiology quickly. Available panels have been of limited use in lower respiratory tract infections due to slow turn-around-time, lack of quantification of important pathogens and lack of detection of resistance genes.

Materials/methods: We evaluated the newly developed Biofire(R) Filmarray(R) Pneumonia Panel plus (Biomerieux). Eighty-eight consecutive lower respiratory tract samples were analyzed by both standard microbiological methods, as requested by the referring clinician, and by the panel. The agreement with standard methods, empirical treatment coverage and possible impact on isolation practices were assessed by comparing the results from standard diagnostic methods with the panel results in relation to clinical data and information of antimicrobial therapy.

Results: Both qualitative and semi-quantitative results from the panel generally displayed good agreement with standard methods and by combining methods, a possible aetiology was detected in 73% of patients. Due to the panel approach, the panel detected viruses more frequently. In 25% of the 60 patients assessed for empirical treatment coverage, a pathogen not covered by current therapy was detected and in 30% of in-house patients the panel results were found to potentially influence clinical decisions related to isolation care.

Conclusions: The new diagnostic panel shows promise in improving aetiological diagnostics of lower respiratory tract infections. Correctly applied it has potential to offer support in clinical decision-making within hours of sampling.

Phospholipids, major constituents of bilayer cell membranes, are present in large amounts in pulmonary surfactant and play key roles in cell signaling. Here, we aim at finding clinically useful disease markers in community-acquired pneumonia (CAP) using comprehensive phospholipid profiling in blood and modeling of changes between sampling time points. Serum samples from 33 patients hospitalized with CAP were collected at admission, three hours after the start of intravenous antibiotics, Day 1 (at 12–24 h), Day 2 (at 36–48 h), and several weeks after recovery. A profile of 75 phospholipid species including quantification of the bioactive lysophosphatidylcholines (LPCs) was determined using liquid chromatography coupled to time-of-flight mass spectrometry. To control for possible enzymatic degradation of LPCs, serum autotaxin levels were examined. Twenty-two of the 33 patients with a clinical diagnosis of CAP received a laboratory-verified CAP diagnosis by microbial culture or microbial DNA detection by qPCR. All major phospholipid species, especially the LPCs, were pronouncedly decreased in the acute stage of illness. Total and individual LPC concentrations increased shortly after the initiation of antibiotic treatment, concentrations were at their lowest 3h after the initiation, and increased after Day 1. The total LPC concentration increased by a change ratio of 1.6–1.7 between acute illness and Day 2, and by a ratio of 3.7 between acute illness and full disease resolution. Autotaxin levels were low in acute illness and showed little changes over time, contradicting a hypothesis of enzymatic degradation causing the low levels of LPCs. In this sample of patients with CAP, the results demonstrate that LPC concentration changes in serum of patients with CAP closely mirrored the early transition from acute illness to recovery after the initiation of antibiotics. LPCs should be further explored as potential disease stage biomarkers in CAP and for their potential physiological role during recovery.

Community-acquired pneumonia (CAP) is a major cause of morbidity and mortality worldwide. Although there is wide variation in the microbial etiology, CAP may manifest with similar symptoms, making institution of proper treatment challenging. Therefore, etiological diagnosis is important to ensure that correct treatment and necessary infection control measures are instituted. This provides a challenge for conventional microbial diagnostic methods, typically based on culture and direct antigen tests. Moreover, existing molecular biomarkers have poor prognostic value. Few studies have investigated the global metabolic response during infection and virtually nothing is known about early responses after the start of antimicrobial treatment. The aim of this work was to improve diagnostic and predictive methods for CAP.

In paper I, a qPCR panel targeting 15 pathogens known to cause CAP was developed and evaluated. It combined identification of bacterial pathogens and viruses in the same diagnostic platform. The method proved to be robust and the results consistent with those obtained by standard methods. The panel approach, compared to conventional, selective diagnostics, detected a larger number of pathogens. In Paper II, whole blood samples from 65 patients with bacteremic sepsis were analyzed for metabolite profiles. Forty-nine patients with symptoms of sepsis, but later attributed to other diagnoses, were matched according to age and sex and served as a control group. Six metabolites were identified, all of which predicted growth of bacteria in blood culture. One of the metabolites, myristic acid, alone predicted bacteremic sepsis with a sensitivity of 100% and a specificity of 95%. Paper III and IV were based on a clinical study enrolling 35 patients with suspected CAP in need of hospital care. The aim was to study the metabolic response during the early phase of acute infection. The qPCR panel developed in Paper I was used to obtain the microbial etiological diagnosis. Paper IV focused on the global metabolic response and highlighted the dynamics of changes in major metabolic pathways during early recovery. A specific metabolite pattern for M. pneumoniae etiology was found. Four metabolites accurately predicted all but one patient as either M. pneumoniae etiology or not. Paper III looked at phospholipid levels during the first 48 hours after hospital admission. It was found that all major phospholipid species, especially the lysophosphatidyl-cholines, were pronouncedly decreased during acute infection. Levels started to increase the day after admission, reaching statistical significance at 48 hours. Paper II-IV showed that metabolomics might be used to study a number of different aspects of infection, such as etiology, disease progress and recovery. Knowledge of the metabolic profiles of patients may not only be utilized for biomarker discovery, as proposed in this work, but also for the future development of targeted therapies and supportive treatment.