Sequential organ failure assessment score is an excellent operationalization of disease severity of adult patients with hospitalized community acquired pneumonia - results from the prospective observational PROGRESS study

Time‑dependent ROC curve analysis to determine the predictive capacity of seven clinical scales for mortality in patients with COVID‑19: Study of a hospital cohort with very high mortality

Clinical data from hospital admissions are typically utilized to determine the prognostic capacity of Coronavirus disease 2019 (COVID-19) indices. However, as disease status and severity markers evolve over time, time-dependent receiver operating characteristic (ROC) curve analysis becomes more appropriate. The present analysis assessed predictive power for death at various time points throughout patient hospitalization. In a cohort study involving 515 hospitalized patients (General Hospital Number 1 of Mexican Social Security Institute, Colima, Mexico from February 2021 to December 2022) with COVID-19, seven severity indices [Pneumonia Severity Index (PSI) PaO2/FiO2 arterial oxygen pressure/fraction of inspired oxygen (Kirby index), the Critical Illness Risk Score (COVID-GRAM), the National Early Warning Score 2 (NEWS-2), the quick Sequential Organ Failure Assessment score (qSOFA), the Fibrosis-4 index (FIB-4) and the Viral Pneumonia Mortality Score (MuLBSTA were evaluated using time-dependent ROC curves. Clinical data were collected at admission and at 2, 4, 6 and 8 days into hospitalization. The study calculated the area under the curve (AUC), sensitivity, specificity, and predictive values for each index at these time points. Mortality was 43.9%. Throughout all time points, NEWS-2 demonstrated the highest predictive power for mortality, as indicated by its AUC values. PSI and COVID-GRAM followed, with predictive power increasing as hospitalization duration progressed. Additionally, NEWS-2 exhibited the highest sensitivity (>96% in all periods) but showed low specificity, which increased from 22.9% at admission to 58.1% by day 8. PSI displayed good predictive capacity from admission to day 6 and excellent predictive power at day 8 and its sensitivity remained >80% throughout all periods, with moderate specificity (70.6-77.3%). COVID-GRAM demonstrated good predictive capacity across all periods, with high sensitivity (84.2-87.3%) but low-to-moderate specificity (61.5-67.6%). The qSOFA index initially had poor predictive power upon admission but improved after 4 days. FIB-4 had a statistically significant predictive capacity in all periods (P=0.001), but with limited clinical value (AUC, 0.639-0.698), and with low sensitivity and specificity. MuLBSTA and IKIRBY exhibited low predictive power at admission and no power after 6 days. In conclusion, in COVID-19 patients with high mortality rates, NEWS-2 and PSI consistently exhibited predictive power for death during hospital stay, with PSI demonstrating the best balance between sensitivity and specificity.

Validation of risk scores for prediction of severe pneumonia in kidney transplant recipients hospitalized with community-acquired pneumonia

PURPOSE

Risk scores for community-acquired pneumonia (CAP) are widely used for standardized assessment in immunocompetent patients and to identify patients at risk for severe pneumonia and death. In immunocompromised patients, the prognostic value of pneumonia-specific risk scores seems to be reduced, but evidence is limited. The value of different pneumonia risk scores in kidney transplant recipients (KTR) is not known.

METHODS

Therefore, we retrospectively analyzed 310 first CAP episodes after kidney transplantation in 310 KTR. We assessed clinical outcomes and validated eight different risk scores (CRB-65, CURB-65, DS-CRB-65, qSOFA, SOFA, PSI, IDSA/ATS minor criteria, NEWS-2) for the prognosis of severe pneumonia and in-hospital mortality. Risk scores were assessed up to 48 h after admission, but always before an endpoint occurred. Multiple imputation was performed to handle missing values.

RESULTS

In total, 16 out of 310 patients (5.2%) died, and 48 (15.5%) developed severe pneumonia. Based on ROC analysis, sequential organ failure assessment (SOFA) and national early warning score 2 (NEWS-2) performed best, predicting severe pneumonia with AUC of 0.823 (0.747-0.880) and 0.784 (0.691-0.855), respectively.

CONCLUSION

SOFA and NEWS-2 are best suited to identify KTR at risk for the development of severe CAP. In contrast to immunocompetent patients, CRB-65 should not be used to guide outpatient treatment in KTR, since there is a 7% risk for the development of severe pneumonia even in patients with a score of zero.

Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia

BACKGROUND

No multivariable model incorporating erector spinae muscle (ESM) has been developed to predict clinical outcomes in older patients with severe community-acquired pneumonia (SCAP). This study aimed to construct a nomogram based on ESM to predict in-hospital mortality in patients with SCAP.

METHODS

Patients aged ≥ 65 years with SCAP were enrolled in this prospective observational study. Least absolute selection and shrinkage operator and multivariable logistic regression analyses were used to identify risk factors for in-hospital mortality. A nomogram prediction model was constructed. The predictive performance was evaluated using the concordance index (C-index), calibration curve, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis.

RESULTS

A total of 490 patients were included, and the in-hospital mortality rate was 36.1%. The nomogram included the following independent risk factors: mean arterial pressure, peripheral capillary oxygen saturation, Glasgow Coma Scale score (GCS), lactate, lactate dehydrogenase, blood urea nitrogen levels, and ESM cross-sectional area. Incorporating ESM into the base model with other risk factors significantly improved the C-index from 0.803 (95% confidence interval [CI], 0.761-0.845) to 0.836 (95% CI, 0.798-0.873), and these improvements were confirmed by category-free NRI and IDI. The ESM-based nomogram demonstrated a high level of discrimination, good calibration, and overall net benefits for predicting in-hospital mortality compared with the combination of confusion, urea, respiratory rate, blood pressure, and age ≥ 65 years (CURB-65), Pneumonia Severity Index (PSI), Acute Physiology and Chronic Health Evaluation II (APACHEII), and Sequential Organ Failure Assessment (SOFA).

CONCLUSIONS

The proposed ESM-based nomogram for predicting in-hospital mortality among older patients with SCAP may help physicians to promptly identify patients prone to adverse outcomes.

TRIAL REGISTRATION

This study was registered at www.chictr.org.cn (registration number Chi CTR-2300070377).

Prehospital Respiratory Early Warning Score for airway management in-ambulance: A score comparison

BACKGROUND

Prehospital Respiratory Early Warning Scores to estimate the requirement for advanced respiratory support is needed. To develop a prehospital Respiratory Early Warning Score to estimate the requirement for advanced respiratory support.

METHODS

Multicentre, prospective, emergency medical services (EMS)-delivered, longitudinal cohort derivationvalidation study carried out in 59 ambulances and five hospitals across five Spanish provinces. Adults with acute diseases evaluated, supported and discharged to the Emergency Department with high priority were eligible. The primary outcome was the need for invasive or non-invasive respiratory support (NIRS or IRS) in the prehospital scope at the first contact with the patient. The measures included the following: epidemiological endpoints, prehospital vital signs (respiratory rate, pulse oximetry saturation, fraction of inspired oxygen, systolic and diastolic mean blood pressure, heart rate, tympanic temperature and consciousness level by the GCS).

RESULTS

Between 26 Oct 2018 and 26 Oct 2021, we enrolled 5793 cases. For NIRS prediction, the final model of the logistic regression included respiratory rate and pulse oximetry saturation/fraction of inspired oxygen ratio. For the IRS case, the motor response from the Glasgow Coma Scale was also included. The REWS showed an AUC of 0.938 (95% CI: 0.918-0.958), a calibration-in-large of 0.026 and a higher net benefit as compared with the other scores.

CONCLUSIONS

Our results showed that REWS is a remarkably aid for the decision-making process in the management of advanced respiratory support in prehospital care. Including this score in the prehospital scenario could improve patients' care and optimise the resources' management.

Comparison of Pneumonia Severity Indices, qCSI, 4C-Mortality Score and qSOFA in Predicting Mortality in Hospitalized Patients with COVID-19 Pneumonia

This is a retrospective and observational study on 1511 patients with SARS-CoV-2, who were diagnosed with COVID-19 by real-time PCR testing and hospitalized due to COVID-19 pneumonia. 1511 patients, 879 male (58.17%) and 632 female (41.83%) with a mean age of 60.1 ± 14.7 were included in the study. Survivors and non-survivors groups were statistically compared with respect to survival, discharge, ICU admission and in-hospital death. Although gender was not statistically significant different between two groups, 80 (60.15%) of the patients who died were male. Mean age was 72.8 ± 11.8 in non-survivors vs. 59.9 ± 14.7 in survivors (p < 0.001). Overall in-hospital mortality was found to be 8.8% (133/1511 cases), and overall ICU admission was 10.85% (164/1511 cases). The PSI/PORT score of the non-survivors group was higher than that of the survivors group (144.38 ± 28.64 versus 67.17 ± 25.63, p < 0.001). The PSI/PORT yielding the highest performance was the best predictor for in-hospital mortality, since it incorporates the factors as advanced age and comorbidity (AUROC 0.971; % 95 CI 0.961−0.981). The use of A-DROP may also be preferred as an easier alternative to PSI/PORT, which is a time-consuming evaluation although it is more comprehensive.

The Expansion of Myeloid-Derived Suppressor Cells Correlates With the Severity of Pneumonia in Kidney Transplant Patients

Background

Pneumonia is one of the most frequent but serious infectious complications post kidney transplantation. Severe pneumonia induces sustained immunosuppression, but few parameters concerning immune status are used to assess the severity of pneumonia. Myeloid-derived suppressor cells (MDSCs) are induced under infection and have the strong immunosuppressive capacity, but the correlation between MDSCs and pneumonia in kidney transplant recipients (KTRs) is unknown.

Methods

Peripheral blood MDSCs were longitudinally detected in 58 KTRs diagnosed with pneumonia using flow cytometry and in 29 stable KTRs as a control. The effectors of MDSCs were detected in the plasma. Spearman's rank correlation analysis was performed to determine the correlation between MDSCs and the severity of pneumonia as well as lymphopenia.

Results

The frequency of MDSCs and effectors, including arginase-1, S100A8/A9, and S100A12, were significantly increased in the pneumonia group compared with the stable group. CD11b⁺CD14⁺HLA-DR^low/−CD15⁻ monocytic-MDSCs (M-MDSCs) were higher in the pneumonia group but showed no significant difference between the severe and non-severe pneumonia subgroups. CD11b⁺CD14⁻CD15⁺ low-density granulocytic-MDSCs (G-MDSCs) were specifically increased in the severe pneumonia subgroup and correlated with the severity of pneumonia as well as lymphopenia. During the study period of 2 weeks, the frequencies of MDSCs and G-MDSCs were persistently increased in the severe pneumonia subgroup.

Conclusions

MDSCs and G-MDSCs were persistently increased in KTRs with pneumonia. G-MDSCs were correlated with the severity of pneumonia and could thus be an indicator concerning immune status for assessing pneumonia severity.

Borderline microscopic organism and lockdown impacted across the borders-global shakers

Viruses are the potential cause of several diseases including novel corona virus-19, flu, small pox, chicken pox, acquired immunodeficiency syndrome, severe acute respiratory syndrome etc. The objectives of this review article are to summarize the reasons behind the epidemics caused by several emerging viruses and bacteria, how to control the infection and preventive strategies. We have explained the causes of epidemics along with their preventive measures, the impact of lockdown on the health of people and the economy of a country. Several reports have revealed the transmission of infection during epidemic from the contact of an infected person to the public that can be prevented by implementing the lockdown by the government of a country. Though lockdown has been considered as one of the significant parameters to control the diseases, however, it has some negative consequences on the health of people as they can be more prone to other ailments like obesity, diabetes, cardiac problems etc. and drastic decline in the economy of a country. Therefore, the transmission of diseases can be prevented by warning the people about the severity of diseases, avoiding their public transportation, keeping themselves isolated, strictly following the guidelines of lockdown and encouraging regular exercise.

Genetic Regulation of Cytokine Response in Patients with Acute Community-Acquired Pneumonia

Background: Community-acquired pneumonia (CAP) is an acute disease condition with a high risk of rapid deteriorations. We analysed the influence of genetics on cytokine regulation to obtain a better understanding of patient’s heterogeneity. Methods: For up to N = 389 genotyped participants of the PROGRESS study of hospitalised CAP patients, we performed a genome-wide association study of ten cytokines IL-1β, IL-6, IL-8, IL-10, IL-12, MCP-1 (MCAF), MIP-1α (CCL3), VEGF, VCAM-1, and ICAM-1. Consecutive secondary analyses were performed to identify independent hits and corresponding causal variants. Results: 102 SNPs from 14 loci showed genome-wide significant associations with five of the cytokines. The most interesting associations were found at 6p21.1 for VEGF (p = 1.58 × 10⁻²⁰), at 17q21.32 (p = 1.51 × 10⁻⁹) and at 10p12.1 (p = 2.76 × 10⁻⁹) for IL-1β, at 10p13 for MIP-1α (CCL3) (p = 2.28 × 10⁻⁹), and at 9q34.12 for IL-10 (p = 4.52 × 10⁻⁸). Functionally plausible genes could be assigned to the majority of loci including genes involved in cytokine secretion, granulocyte function, and cilial kinetics. Conclusion: This is the first context-specific genetic association study of blood cytokine concentrations in CAP patients revealing numerous biologically plausible candidate genes. Two of the loci were also associated with atherosclerosis with probable common or consecutive pathomechanisms.

Sequential Organ Failure Assessment Outperforms Quantitative Chest CT Imaging Parameters for Mortality Prediction in COVID-19 ARDS

(1) Background: Respiratory insufficiency with acute respiratory distress syndrome (ARDS) and multi-organ dysfunction leads to high mortality in COVID-19 patients. In times of limited intensive care unit (ICU) resources, chest CTs became an important tool for the assessment of lung involvement and for patient triage despite uncertainties about the predictive diagnostic value. This study evaluated chest CT-based imaging parameters for their potential to predict in-hospital mortality compared to clinical scores. (2) Methods: 89 COVID-19 ICU ARDS patients requiring mechanical ventilation or continuous positive airway pressure mask ventilation were included in this single center retrospective study. AI-based lung injury assessment and measurements indicating pulmonary hypertension (PA-to-AA ratio) on admission CT, oxygenation indices, lung compliance and sequential organ failure assessment (SOFA) scores on ICU admission were assessed for their diagnostic performance to predict in-hospital mortality. (3) Results: CT severity scores and PA-to-AA ratios were not significantly associated with in-hospital mortality, whereas the SOFA score showed a significant association (p < 0.001). In ROC analysis, the SOFA score resulted in an area under the curve (AUC) for in-hospital mortality of 0.74 (95%-CI 0.63–0.85), whereas CT severity scores (0.53, 95%-CI 0.40–0.67) and PA-to-AA ratios (0.46, 95%-CI 0.34–0.58) did not yield sufficient AUCs. These results were consistent for the subgroup of more critically ill patients with moderate and severe ARDS on admission (oxygenation index <200, n = 53) with an AUC for SOFA score of 0.77 (95%-CI 0.64–0.89), compared to 0.55 (95%-CI 0.39–0.72) for CT severity scores and 0.51 (95%-CI 0.35–0.67) for PA-to-AA ratios. (4) Conclusions: Severe COVID-19 disease is not limited to lung (vessel) injury but leads to a multi-organ involvement. The findings of this study suggest that risk stratification should not solely be based on chest CT parameters but needs to include multi-organ failure assessment for COVID-19 ICU ARDS patients for optimized future patient management and resource allocation.

qSOFA predicted pneumonia mortality better than minor criteria and worse than CURB-65 with robust elements and higher convergence

BACKGROUND

Limited data are available on the discriminatory capacity of quick sequential [sepsis-related] organ failure assessment (qSOFA) versus IDSA/ATS minor criteria for predicting mortality in patients with community-acquired pneumonia (CAP).

METHODS

An observational prospective cohort study of 2116 patients with CAP was performed. Construct validity was determined using Cronbach α. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC) and net reclassification improvement (NRI).

RESULTS

Overall in-hospital mortality was 6.43%. Mortality was 25.96% for patients with a qSOFA score of 2 or higher versus 3.05% for those with a qSOFA score less than 2 (odds ratio for mortality 6.57, P < 0.0001), and 13.85% for patients with at least 3 minor criteria versus 2.03% for those with 2 or fewer minor criteria (odds ratio for mortality 2.27, P < 0.0001). qSOFA had a higher correlation with mortality than minor criteria, as well as higher internal consistency (Cronbach alpha 0.43 versus 0.14) and diagnostic values of individual elements (larger AUROCs and higher Youden's indices). qSOFA ≥2 was less sensitive but more specific for predicting mortality than ≥3 minor criteria (qSOFA sensitivity 59.6%, specificity 88.3% and positive likelihood ratio 5.11 versus ≥3 minor criteria sensitivity 80.1%, specificity 65.8% and positive likelihood ratio 2.34). The predictive validity of qSOFA was good for mortality (AUROC = 0.868), was statistically greater than minor criteria, was equal to pneumonia severity index, and was inferior compared with CURB-65 (AUROC, 0.824, 0.902, 0.919; NRI, 0.088, -0.068, -0.103; respectively).

CONCLUSIONS

The qSOFA predicted mortality in CAP better than IDSA/ATS minor criteria and worse than CURB-65 with robust elements and higher convergence. qSOFA as a bedside prompt might be positioned as a proxy for minor criteria and increase the recognition and thus merit more appropriate management of CAP patients likely to fare poorly, which might have implications for more accurate clinical triage decisions.

A literature review of severity scores for adults with influenza or community-acquired pneumonia - implications for influenza vaccines and therapeutics

Influenza vaccination and antiviral therapeutics may attenuate disease, decreasing severity of illness in vaccinated and treated persons. Standardized assessment tools, definitions of disease severity, and clinical endpoints would support characterizing the attenuating effects of influenza vaccines and antivirals. We review potential clinical parameters and endpoints that may be useful for ordinal scales evaluating attenuating effects of influenza vaccines and antivirals in hospital-based studies. In studies of influenza and community-acquired pneumonia, common physiologic parameters that predicted outcomes such as mortality, ICU admission, complications, and duration of stay included vital signs (hypotension, tachypnea, fever, hypoxia), laboratory results (blood urea nitrogen, platelets, serum sodium), and radiographic findings of infiltrates or effusions. Ordinal scales based on these parameters may be useful endpoints for evaluating attenuating effects of influenza vaccines and therapeutics. Factors such as clinical and policy relevance, reproducibility, and specificity of measurements should be considered when creating a standardized ordinal scale for assessment.

A Comparative Analysis of the Respiratory Subscore of the Sequential Organ Failure Assessment Scoring System

Rationale: The Sequential Organ Failure Assessment (SOFA) tool is a commonly used measure of illness severity. Calculation of the respiratory subscore of SOFA is frequently limited by missing arterial oxygen pressure (PaO2) data. Although missing PaO2 data are commonly replaced with normal values, the performance of different methods of substituting PaO2 for SOFA calculation is unclear. Objectives: The study objective was to compare the performance of different substitution strategies for missing PaO2 data for SOFA score calculation. Methods: This retrospective cohort study was performed using the Weill Cornell Critical Care Database for Advanced Research from a tertiary care hospital in the United States. All adult patients admitted to an intensive care unit (ICU) from 2011 to 2019 with an available respiratory SOFA score were included. We analyzed the availability of the PaO2/fraction of inspired oxygen (FiO2) ratio on the first day of ICU admission. In those without a PaO2/FiO2 ratio available, the ratio of oxygen saturation as measured by pulse oximetry to FiO2 was used to calculate a respiratory SOFA subscore according to four methods (linear substitution [Rice], nonlinear substitution [Severinghaus], modified respiratory SOFA, and multiple imputation by chained equations [MICE]) as well as the missing-as-normal technique. We then compared how well the different total SOFA scores discriminated in-hospital mortality. We performed several subgroup and sensitivity analyses. Results: We identified 35,260 unique visits, of which 9,172 included predominant respiratory failure. PaO2 data were available for 14,939 (47%). The area under the receiver operating characteristic curve for each substitution technique for discriminating in-hospital mortality was higher than that for the missing-as-normal technique (0.78 [0.77-0.79]) in all analyses (modified, 0.80 [0.79-0.81]; Rice, 0.80 [0.79-0.81]; Severinghaus, 0.80 [0.79-0.81]; and MICE, 0.80 [0.79-0.81]) (P < 0.01). Each substitution method had a higher accuracy for discriminating in-hospital mortality (MICE, 0.67; Rice, 0.67; modified, 0.66; and Severinghaus, 0.66) than the missing-as-normal technique. Model calibration for in-hospital mortality was less precise for the missing-as-normal technique than for the other substitution techniques at the lower range of SOFA and among the subgroups. Conclusions: Using physiologic and statistical substitution methods improved the total SOFA score's ability to discriminate mortality compared with the missing-as-normal technique. Treating missing data as normal may result in underreporting the severity of illness compared with using substitution. The simplicity of a direct oxygen saturation as measured by pulse oximetry/FiO2 ratio-modified SOFA technique makes it an attractive choice for electronic health record-based research. This knowledge can inform comparisons of severity of illness across studies that used different techniques.

Prognostic accuracy of Quick SOFA in older adults hospitalised with community acquired urinary tract infection

INTRODUCTION

Quick [Sepsis-related] Sequential Organ Failure Assessment (qSOFA) is a prognostic score based on sepsis-3 definition, easy to carry out, whose application has been studied in older adults with sepsis from different sources and respiratory sepsis. However, to date no study has analysed its prognostic accuracy in older adults admitted to hospital with community urinary tract infection.

METHODS

In a prospective study of 282 older adults admitted to hospital with community acquired urinary tract infection, the application of qSOFA to predict hospital mortality was analysed. The predictive capacity of qSOFA for in-hospital mortality was compared with Systemic Inflammatory Response Syndrome score (SIRS) and Sequential Organ Failure Assessment (SOFA), which require laboratory test in order to be calculated.

RESULTS

In a population with a median age of 81 years, where 51.8% were males and 10.6% had septic shock, qSOFA showed sensibility and specificity of 88.46 and 75.78% and area under the receiver operating characteristic curves (AUROC) of 0.810. AUROC for qSOFA was significantly higher than that of SIRS (AUROC 0.597, P = .005) and with no statistical differences with SOFA (AUROC 0.841, P = .635).

CONCLUSION

qSOFA showed a better predictive prognostic accuracy than SIRS and similar to SOFA in older adults admitted to hospital with community acquired urinary tract infection, having the advantage of not requiring laboratory tests.

External Validation and Recalibration of the CURB-65 and PSI for Predicting 30-Day Mortality and Critical Care Intervention in Multiethnic Patients with COVID-19

OBJECTIVES

To validate and recalibrate the CURB-65 and pneumonia severity index (PSI) in predicting 30-day mortality and critical care intervention (CCI) in a multiethnic population with COVID-19, along with evaluating both models in predicting CCI.

METHODS

Retrospective data was collected for 1181 patients admitted to the largest hospital in Qatar with COVID-19 pneumonia. The area under the curve (AUC), calibration curves, and other metrics were bootstrapped to examine the performance of the models. Variables constituting the CURB-65 and PSI scores underwent further analysis using the Least Absolute Shrinkage and Selection Operator (LASSO) along with logistic regression to develop a model predicting CCI. Complex machine learning models were built for comparative analysis.

RESULTS

The PSI performed better than CURB-65 in predicting 30-day mortality (AUC 0.83, 0.78 respectively), while CURB-65 outperformed PSI in predicting CCI (AUC 0.78, 0.70 respectively). The modified PSI/CURB-65 model (respiratory rate, oxygen saturation, hematocrit, age, sodium, and glucose) predicting CCI had excellent accuracy (AUC 0.823) and good calibration.

CONCLUSIONS

Our study recalibrated, externally validated the PSI and CURB-65 for predicting 30-day mortality and CCI, and developed a model for predicting CCI. Our tool can potentially guide clinicians in Qatar to stratify patients with COVID-19 pneumonia.

Krueppel-Like Factor 4 Expression in Phagocytes Regulates Early Inflammatory Response and Disease Severity in Pneumococcal Pneumonia

The transcription factor Krueppel-like factor (KLF) 4 fosters the pro-inflammatory immune response in macrophages and polymorphonuclear neutrophils (PMNs) when stimulated with Streptococcus pneumoniae, the main causative pathogen of community-acquired pneumonia (CAP). Here, we investigated the impact of KLF4 expression in myeloid cells such as macrophages and PMNs on inflammatory response and disease severity in a pneumococcal pneumonia mouse model and in patients admitted to hospital with CAP. We found that mice with a myeloid-specific knockout of KLF4 mount an insufficient early immune response with reduced levels of pro-inflammatory cytokines and increased levels of the anti-inflammatory cytokine interleukin (IL) 10 in bronchoalveolar lavage fluid and plasma and an impaired bacterial clearance from the lungs 24 hours after infection with S. pneumoniae. This results in higher rates of bacteremia, increased lung tissue damage, more severe symptoms of infection and reduced survival. Higher KLF4 gene expression levels in the peripheral blood of patients with CAP at hospital admission correlate with a favourable clinical presentation (lower sequential organ failure assessment (SOFA) score), lower serum levels of IL-10 at admission, shorter hospital stay and lower mortality or requirement of intensive care unit treatment within 28 days after admission. Thus, KLF4 in myeloid cells such as macrophages and PMNs is an important regulator of the early pro-inflammatory immune response and, therefore, a potentially interesting target for therapeutic interventions in pneumococcal pneumonia.

[Management of Adult Community-Acquired Pneumonia and Prevention - Update 2021 - Guideline of the German Respiratory Society (DGP), the Paul-Ehrlich-Society for Chemotherapy (PEG), the German Society for Infectious Diseases (DGI), the German Society of Medical Intensive Care and Emergency Medicine (DGIIN), the German Viological Society (DGV), the Competence Network CAPNETZ, the German College of General Practitioneers and Family Physicians (DEGAM), the German Society for Geriatric Medicine (DGG), the German Palliative Society (DGP), the Austrian Society of Pneumology Society (ÖGP), the Austrian Society for Infectious and Tropical Diseases (ÖGIT), the Swiss Respiratory Society (SGP) and the Swiss Society for Infectious Diseases Society (SSI)]

The present guideline provides a new and updated concept of the management of adult patients with community-acquired pneumonia. It replaces the previous guideline dating from 2016.The guideline was worked out and agreed on following the standards of methodology of a S3-guideline. This includes a systematic literature search and grading, a structured discussion of recommendations supported by the literature as well as the declaration and assessment of potential conflicts of interests.The guideline has a focus on specific clinical circumstances, an update on severity assessment, and includes recommendations for an individualized selection of antimicrobial treatment.The recommendations aim at the same time at a structured assessment of risk for adverse outcome as well as an early determination of treatment goals in order to reduce mortality in patients with curative treatment goal and to provide palliation for patients with treatment restrictions.

Severity Scores in COVID-19 Pneumonia: a Multicenter, Retrospective, Cohort Study

BACKGROUND

Identification of patients on admission to hospital with coronavirus infectious disease 2019 (COVID-19) pneumonia who can develop poor outcomes has not yet been comprehensively assessed.

OBJECTIVE

To compare severity scores used for community-acquired pneumonia to identify high-risk patients with COVID-19 pneumonia.

DESIGN

PSI, CURB-65, qSOFA, and MuLBSTA, a new score for viral pneumonia, were calculated on admission to hospital to identify high-risk patients for in-hospital mortality, admission to an intensive care unit (ICU), or use of mechanical ventilation. Area under receiver operating characteristics curve (AUROC), sensitivity, and specificity for each score were determined and AUROC was compared among them.

PARTICIPANTS

Patients with COVID-19 pneumonia included in the SEMI-COVID-19 Network.

KEY RESULTS

We examined 10,238 patients with COVID-19. Mean age of patients was 66.6 years and 57.9% were males. The most common comorbidities were as follows: hypertension (49.2%), diabetes (18.8%), and chronic obstructive pulmonary disease (12.8%). Acute respiratory distress syndrome (34.7%) and acute kidney injury (13.9%) were the most common complications. In-hospital mortality was 20.9%. PSI and CURB-65 showed the highest AUROC (0.835 and 0.825, respectively). qSOFA and MuLBSTA had a lower AUROC (0.728 and 0.715, respectively). qSOFA was the most specific score (specificity 95.7%) albeit its sensitivity was only 26.2%. PSI had the highest sensitivity (84.1%) and a specificity of 72.2%.

CONCLUSIONS

PSI and CURB-65, specific severity scores for pneumonia, were better than qSOFA and MuLBSTA at predicting mortality in patients with COVID-19 pneumonia. Additionally, qSOFA, the simplest score to perform, was the most specific albeit the least sensitive.

Admission lysophosphatidylethanolamine acyltransferase level predicts the severity and prognosis of community-acquired pneumonia

PURPOSE

Early diagnosis and prognosis of patients with community-acquired pneumonia (CAP) are still difficult clinical challenges. This study aimed to investigate the role of lysophosphatidylethanolamine acyltransferase (LPEAT) in CAP and to evaluate the effectiveness of this enzyme as an indicator of disease severity and risk of death in CAP.

METHODS

This retrospective, multi-center study was conducted in 2017. A total of 267 patients with CAP were included. Of these 267 patients, 175 patients had non-severe CAP (non-SCAP) and 92 patients had severe CAP (SCAP). In addition, we recruited 15 healthy volunteers and 42 hospitalized disease controls in our study. The demographic and clinical characteristics were recorded for all participants. Admission levels of LPEAT were determined by quantitative enzyme-linked immunosorbent assay.

RESULTS

Admission levels of LPEAT in patients with SCAP were significantly higher, particularly in non-survivors and were not affected by the causative etiology. Furthermore, when the patients were stratified according to PSI and CURB-65 scores, the patients with high severity scores had higher LPEAT levels upon admission than patients with low severity scores. LPEAT also performed well in predicting SCAP in patients with CAP. Moreover, LPEAT could predict the 30-day mortality rate of patients with CAP, and combining LPEAT with the clinical severity score further improved the accuracy of mortality prediction.

CONCLUSION

Elevated LPEAT levels can reliably predict the severity of illness in patients with CAP at the time of admission. Adding LPEAT to clinical scoring methods could improve prognostic accuracy. Trial registration ClinicalTrials.gov, NCT03093220. Registered on March 28th, 2017.

The role of qSOFA score and biomarkers in assessing severity of community-acquired pneumonia in adults

Introduction: Community-acquired pneumonia (CAP) is the primary cause of severe sepsis. Severity assessment scores have been created, in order to help physicians decide the proper management of CAP. The purpose of this study was to examine the correlations between different CAP severity scores, including qSOFA, several biomarkers and their predictive value in the 30 day follow-up period, regarding adverse outcome.

Materials and methods: One hundred and thirty nine adult patients with CAP, admitted in the Teaching Hospital of Infectious Diseases, Cluj-Napoca, Romania from December 2015 to February 2017, were enrolled in this study. Pneumonia Severity Index (PSI), CURB-65, SMART-COP and the qSOFA scores were calculated at admittance. Also, C-reactive protein (CRP), procalcitonin (PCT) and albumin levels were used to determine severity.

Results: The mean PSI of all patients was 93.30±41.135 points, for CURB-65 it was 1.91±0.928 points, for SMART-COP it was 1.69±1.937 points. The mean qSOFA was 1.06±0.522 points, 21 (14.9%) were at high risk of in-hospital mortality. In the group of patients with qSOFA of ≥2, all pneumonia severity scores and all biomarkers tested were higher than those with scores <2. We found significant correlations between biomarkers and severity scores, but none regarding adverse outcome.

Conclusion: The qSOFA score is easier to use and it is able to accurately evaluate the severity of CAP, similar to other scores. Biomarkers are useful in determining the severity of the CAP. Several studies are needed to assess the prediction of these biomarkers and severity scores in pneumonia regarding adverse outcome.

Incidence of Antibiotic Treatment Failure in Patients with Nursing Home-Acquired Pneumonia and Community Acquired Pneumonia

Purpose: Nursing home-acquired pneumonia (NHAP) patients are at higher risk of multi-drug resistant infection (MDR) than those with community-acquired pneumonia (CAP). Recent evidence suggests a single risk factor for MDR does not accurately predict the need for broad-spectrum antibiotics. The goal of this study was to compare the rate antibiotic failure between NHAP and CAP patients. Methods: Demographic characteristics, co-morbidities, clinical and laboratory variables, antibiotic therapy, and mortality data were collected retrospectively for all patients with pneumonia admitted to an Internal Medicine Service between April 2017 and April 2018. Results: In total, 313 of 556 patients had CAP and 243 had NHAP. NHAP patients were older, and were more likely to be dependent, to have recent antibiotic use, and to experience treatment failure (odds ratio (OR) 1.583; 95% CI 1.102–2.276; p = 0.013). In multivariate analysis, patient’s origin did not predict treatment failure (OR 1.083; 95% CI 0.726–1.616; p = 0.696). Discussion: Higher rates of antibiotic failure and mortality in NHAP patients were explained by the presence of other risk factors such as comorbidities, more severe presentation, and age. Admission from a nursing home is not a sufficient condition to start broader-spectrum antibiotics.

Prediction value of procalcitonin combining CURB-65 for 90-day mortality in community-acquired pneumonia

Background: Due to its high mortality rate, immediate and reliable severity assessment and accurate prediction of prognosis at hospital admission is critical for the management of community-acquired pneumonia (CAP) patients.Methods: Consecutive patients with primary diagnosis of CAP and hospitalized at our hospital from January 2013 to December 2015 were screened for this retrospective study. Demographic information, clinical and laboratory examination, severity model scoring, and 90-day outcomes were studied. Area under the curve (AUC) of receiver operating characteristic curve (ROC) was analyzed to compare the predictive value of different prognostic scoring methods.Results: 2099 CAP patients with a median age of 60 (IQR 44.0-73.0) years-old were included in this study. Median length of stay was 10 days (IQR 8.0-13.0). The all-cause 90-day mortality was found in 2.19% (46/2099) of all patients. PCT was identified as an independent predictor for the prognosis of CAP patients. CURB-65 in combination with PCT outperformed other predictive methods in 90-day mortality with the optimal AUC of 0.900 and Youden's Index of 0.706.Conclusions: PCT is a good marker for the assessment of severity and 90-day mortality of CAP patients. The combination of PCT and CURB-65 was more accurate than other prognostic models in predicting 90-day mortality.

qSOFA Score Is Useful to Assess Disease Severity in Patients With Heart Failure in the Setting of a Heart Failure Unit (HFU)

Aims: There is no gold standard to predict outcome in acute decompensated heart failure (ADHF). Several scores for mortality prediction of patients with ADHF have been developed and mostly consist of complex regression models. None of these models has been widely adopted by clinicians. The quick SOFA score (qSOFA) is a simple score including three parameters (systolic blood pressure ≤ 100 mmHg, respiratory rate ≥22 breathes/min, and GCS <15) and is validated for discrimination of mortality risk in septic patients. Here, we adapted qSOFA score to patients admitted to a Heart Failure Unit (HFU) and assessed the prognostic accuracy.

Methods and Results: qSOFA, SOFA score, and SIRS criteria were assessed at admission. Clinical, laboratory, and echocardiographic parameters were recorded. A follow-up was performed 30 days after discharge. Primary outcome was all-cause mortality or readmission to hospital due do worsening of heart failure symptoms. Of 240 patients (73% male, 16–93 years), 25 patients (10%) had a qSOFA ≥2 points and 126 patients (53%) fulfilled none of qSOFA criteria. Within 30 days, the primary endpoint occurred in 46 patients (19%). Seventeen patients (7%) died and 34 patients (14%) were readmitted to hospital due to worsening heart failure. Patients with qSOFA ≥2 reached this endpoint more frequently (48 vs. 19%, p = 0.002), had more often dyspnea NYHA III-IV (OR 2.4, p = 0.005) and a higher risk for multi organ failure during hospital stay (28 vs. 9%, P = 0.005).

Conclusions: qSOFA is useful to identify patients with heart failure at high risk for worse outcome and to operationalize severity of decompensation.

Managing COVID-19-positive Solid Organ Transplant Recipients in the Community: What a Community Healthcare Provider Needs to Know

Supplemental Digital Content is available in the text.

Background.

The current surge of coronavirus 2019 (COVID-19) cases in certain parts of the country has burdened the healthcare system, limiting access to tertiary centers for many. As a result, COVID-19-positive Solid Organ Transplant (SOT) recipients are increasingly being managed by local healthcare providers. It is crucial for community providers to understand disease severity and know if COVID-19-impacted SOT recipients have a different clinical course compared with COVID-19-negative SOT recipients with a similar presentation.

Methods.

We conducted a retrospective analysis on SOT recipients suspected to have COVID-19 infection tested during March 14, 2020–April 30, 2020. Patients were followed from time of testing to May 31, 2020.

Results.

One hundred sixty SOT recipients underwent testing: 22 COVID-19 positive and 138 COVID-19 negative. COVID-19-positive patients were more likely to have rapid progression of symptoms (median 3 vs 6 d, P = 0.002), greater hospitalizations (78% vs 64%, P < 0.017), and need for intensive care unit care (45% vs 17%, P < 0.001) Severe COVID-19 infection was not observed in patients on Belatacept for immunosuppression (30% vs 87%,P = 0.001). COVID- 19 positive patients in the intensive care unit were more likely to have multifocal opacities on radiological imaging in comparison to those admitted to the medical floor (90% vs 11%). Survival probability was similar in both cohorts.

Conclusion.

COVID-19-infected SOT recipients have a propensity for rapid clinical decompensation. Local providers need to be work closely with transplant centers to appropriately triage and manage COVID-19 SOT recipients in the community.

Clinical predictors of COVID-19 disease progression and death: Analysis of 214 hospitalised patients from Wuhan, China

INTRODUCTION

COVID-19 has spread rapidly worldwide and has been declared a pandemic.

OBJECTIVES

To delineate clinical features of COVID-19 patients with different severities and prognoses and clarify the risk factors for disease progression and death at an early stage.

METHODS

Medical history, laboratory findings, treatment and outcome data from 214 hospitalised patients with COVID-19 pneumonia admitted to Eastern Campus of Renmin Hospital, Wuhan University in China were collected from 30 January 2020 to 20 February 2020, and risk factors associated with clinical deterioration and death were analysed. The final date of follow-up was 21 March 2020.

RESULTS

Age, comorbidities, higher neutrophil cell counts, lower lymphocyte counts and subsets, impairment of liver, renal, heart, coagulation systems, systematic inflammation and clinical scores at admission were significantly associated with disease severity. Ten (16.1%) moderate and 45 (47.9%) severe patients experienced deterioration after admission, and median time from illness onset to clinical deterioration was 14.7 (IQR 11.3-18.5) and 14.5 days (IQR 11.8-20.0), respectively. Multivariate analysis showed increased Hazards Ratio of disease progression associated with older age, lymphocyte count <1.1 × 10⁹/L, blood urea nitrogen (BUN)> 9.5 mmol/L, lactate dehydrogenase >250 U/L and procalcitonin >0.1 ng/mL at admission. These factors were also associated with the risk of death except for BUN. Prediction models in terms of nomogram for clinical deterioration and death were established to illustrate the probability.

CONCLUSIONS

These findings provide insights for early detection and management of patients at risk of disease progression or even death, especially older patients and those with comorbidities.

The mNCP-SPI Score Predicting Risk of Severe COVID-19 among Mild-Pneumonia Patients on Admission

Purpose

To predict the risk of developing severe pneumonia among mild novel coronavirus pneumonia (mNCP) patients on admission.

Methods

A retrospective cohort study was conducted at three hospitals in Shanghai and Wuhan from January 2020 to February 2020. Real-time polymerasechain–reaction assays were used to detect COVID-19. A total of 529 patients diagnosed with NCP were recruited from three hospitals and classified by four severity types during hospitalization following the standards of the Chinese Diagnosis and Treatment of Pneumonia Caused by New Coronavirus Infection (eighth version). Patients were excluded if admitted by ICU on admission (n=92, on a general ward while meeting the condition of severe or critical type on admission (n=25), or there was insufficient clinical information (n=64). In sum, 348 patients with mNCP were finally included, and 68 developed severe pneumonia.

Results

mNCP severity prognostic index values were calculated based on multivariate logistic regression: history of diabetes (OR 2.064, 95% CI 1.010–4.683; p=0.043), time from symptom onset to admission ≥7 days (OR 1.945, 95% CI 1.054–3.587; p=0.033), lymphocyte count ≤0.8 (OR 1.816, 95% CI 1.008–3.274; p=0.047), myoglobin ≥90 mg/L (OR 2.496, 95% CI 1.235–5.047; p=0.011), and D-dimer ≥0.5 mg/L (OR 2.740, 95% CI 1.395–5.380; p=0.003). This model showed a c-statistics of 0.747, with sensitivity and specificity 0.764 and 0.644, respectively, under cutoff of 165.

Conclusion

We designed a clinical predictive tool for risk of severe pneumonia among mNCP patients to provided guidance for medicines. Further studies are required for external validation.

Validation of the qSOFA score compared to the CRB-65 score for risk prediction in community-acquired pneumonia

OBJECTIVE

The qSOFA (quick sepsis-related organ failure assessment) score shows similarities to the CRB-65 pneumonia score, but its prognostic accuracy in patients with community-acquired pneumonia (CAP) has not been extensively evaluated. Our aim was to validate the qSOFA (-65) score in a large cohort of CAP patients.

METHODS

We conducted a retrospective population-based cohort study including all CAP cases hospitalized between 1st January 2014 and 31st December 2018 from the German nationwide mandatory quality assurance programme. We excluded cases transferred from another hospital, with mechanical ventilation present on admission, and without documented respiratory rate. Predefined outcomes were hospital mortality and need for mechanical ventilation.

RESULTS

Among the 1,262,250 included cases, hospital mortality was 12.4% and the mechanical ventilation rate was 7.1%. All CRB and qSOFA criteria were associated with both outcomes, but the qSOFA had inferior sensitivity compared to the CRB-65 for mortality prediction. Including the age criterion ≥65 years, qSOFA-65 and CRB-65 performed similarly (AUC 0.69, 95%CI 0.69-0.69 versus 0.68, 95%CI 0.68-0.68). A qSOFA-65 of 0 was associated with fewer missed deaths (3328, 2.0%) compared to a CRB-65 of 0 (5480, 2.4%). The sensitivity of the suggested qSOFA cut-off of ≥2 for sepsis was low (mortality 25.8%, 95%CI 25.6-26.0%; mechanical ventilation 24.1%, 95%CI 23.8-24.4%). Results were similar when frail and palliative patients were excluded.

CONCLUSIONS

The qSOFA parameters show prognostic accuracy similar to the CRB parameters in CAP, but the sepsis cut-off of ≥2 lacked sensitivity. For sensitive mortality prediction, the age criterion ≥65 years should be added to the qSOFA.

Outcome prediction value of National Early Warning Score in septic patients with community-acquired pneumonia in emergency department: A single-center retrospective cohort study

BACKGROUND

To evaluate the accuracy of National Early Warning Score (NEWS) in predicting clinical outcomes (28-day mortality, intensive care unit [ICU] admission, and mechanical ventilation use) for septic patients with community-acquired pneumonia (CAP) compared with other commonly used severity scores (CURB65, Pneumonia Severity Index [PSI], Sequential Organ Failure Assessment [SOFA], quick SOFA [qSOFA], and Mortality in Emergency Department Sepsis [MEDS]) and admission lactate level.

METHODS

Adult patients diagnosed with CAP admitted between January 2017 and May 2019 with admission SOFA ≥2 from baseline were enrolled. Demographic characteristics were collected. The primary outcome was the 28-day mortality after admission, and the secondary outcome included ICU admission and mechanical ventilation use. Outcome prediction value of parameters above was compared using receiver operating characteristics (ROC) curves. Cox regression analyses were carried out to determine the risk factors for the 28-day mortality. Kaplan-Meier survival curves were plotted and compared using optimal cut-off values of qSOFA and NEWS.

RESULTS

Among the 340 enrolled patients, 90 patients were dead after a 28-day follow-up, 62 patients were admitted to ICU, and 84 patients underwent mechanical ventilation. Among single predictors, NEWS achieved the largest area under the receiver operating characteristic (AUROC) curve in predicting the 28-day mortality (0.861), ICU admission (0.895), and use of mechanical ventilation (0.873). NEWS+lactate, similar to MEDS+lactate, outperformed other combinations of severity score and admission lactate in predicting the 28-day mortality (AUROC 0.866) and ICU admission (AUROC 0.905), while NEWS+lactate did not outperform other combinations in predicting mechanical ventilation (AUROC 0.886). Admission lactate only improved the predicting performance of CURB65 and qSOFA in predicting the 28-day mortality and ICU admission.

CONCLUSIONS

NEWS could be a valuable predictor in septic patients with CAP in emergency departments. Admission lactate did not predict well the outcomes or improve the severity scores. A qSOFA ≥2 and a NEWS ≥9 were strongly associated with the 28-day mortality, ICU admission, and mechanical ventilation of septic patients with CAP in the emergency departments.

Dynamics of cytokines, immune cell counts and disease severity in patients with community-acquired pneumonia - Unravelling potential causal relationships

BACKGROUND

Community acquired pneumonia (CAP) is a severe and often rapidly deteriorating disease. To better understand its dynamics and potential causal relationships, we analyzed time series data of cytokines, blood and clinical parameters in hospitalized CAP patients.

METHODS

Time series data of 10 circulating cytokines, blood counts and clinical parameters were related to baseline characteristics of 403 CAP patients using univariate mixed models. Bivariate mixed models were applied to analyze correlations between the time series. To identify potential causal relationships, we inferred cross-lagged relationships between pairs of parameters using latent curve models with structured residuals.

RESULTS

IL-6 levels decreased faster over time in younger patients (P_adj = 0.06). IL-8, VCAM-1, and IL-6 correlated strongly with disease severity as assessed by the sequential organ failure assessment (SOFA) score (r = 0.49, 0.48, 0.46, respectively; all P_adj < 0.001). IL-6 and bilirubin correlated with respect to their mean levels and slopes over time (r = 0.36 and r = 0.46, respectively; P_adj < 0.001). A number of potential causal relationships were identified, e.g., a negative effect of ICAM-1 on MCP-1, or a positive effect of the level of creatinine on the subsequent VCAM-1 concentration (P < 0.001).

CONCLUSIONS

These results suggest that IL-6 trajectories of CAP patients are associated with age and run parallel to bilirubin levels. The time series analysis also unraveled directed, potentially causal relationships between cytokines, blood parameters and clinical outcomes. This will facilitate the development of mechanistic models of CAP, and with it, improvements in treatment or surveillance strategies for this disease.

TRIAL REGISTRATION

clinicaltrials.gov NCT02782013, May 25, 2016, retrospectively registered.

Serological chemiluminescence immunoassay for the diagnosis of SARS-CoV-2 infection

Objective

Dynamic monitoring of the concentration variation of IgM and IgG in patients with SARS‐CoV‐2 infections and exploring their diagnostic value for coronavirus disease‐19 (COVID‐19).

Methods

A total of 15 patients with SARS‐CoV‐2 infection were enrolled as the COVID‐19 group, and 50 patients were enrolled as the control group. The concentrations of SARS‐CoV‐2‐specific antibodies (IgM and IgG) were detected by a chemiluminescence immunoassay (CLIA).

Results

According to the cutoff value recommended by the manufacturer (cutoff = 10 AU/mL), the sensitivity, specificity, Youden index (YI), positive predictive value (PPV), and negative predictive value (NPV) of IgM were 60%, 100%, 60%, 100%, and 89.29%, respectively; and 86.67%, 100%, 86.67%, 100%, and 96.15%, respectively, for IgG. We reassessed the cutoff value of IgM. When the cutoff value for SARS‐CoV‐2 IgM was 1.83 AU/mL, the sensitivity, specificity, YI, PPV, and NPV were 93.33%, 98%, 91.33%, 93.33%, and 98%, respectively. During dynamic monitoring of the concentrations of IgM and IgG in COVID‐19 patients, we found the shortest times before a patient became IgM and IgG seropositive after symptom onset were 1.5 and 2 days, respectively. The longest times were 7 and 8 days, respectively. The positive rates of SARS‐CoV‐2 IgM and IgG both reached 100% in 8‐14 days after symptom onset.

Conclusion

The IgM cutoff value of 1.83 AU/mL for the diagnosis of COVID‐19 was much better than the cutoff suggested by the manufacturer. SARS‐CoV‐2 infection can be ruled out if antibodies against SARS‐CoV‐2 are still undetectable 14 days after symptom onset.

Predicting Bacterial Versus Viral Infection, or None of the Above: Current and Future Prospects of Biomarkers

Sepsis and pneumonia cause significant morbidity and mortality worldwide. Despite improvements in diagnostic methodologies for organism identification, the early recognition and further risk stratification of these infections can be challenging. Although traditional clinical scoring systems are beneficial for the management of sepsis and pneumonia, biomarkers supporting the diagnosis and management of these infectious diseases are needed. Many biomarkers have been identified and there is no lack of studies and meta-analyses assessing the utility of biomarkers. Focusing primarily on sepsis and pneumonia, this article discusses the most commonly used biomarkers for which clinical laboratory testing methods are available.

SARS-CoV-2 Infection and Cardiovascular Disease: COVID-19 Heart

Coronavirus disease (COVID-19) is a serious illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The symptoms of the disease range from asymptomatic to mild respiratory symptoms and even potentially life-threatening cardiovascular and pulmonary complications. Cardiac complications include acute myocardial injury, arrhythmias, cardiogenic shock and even sudden death. Furthermore, drug interactions with COVID-19 therapies may place the patient at risk for arrhythmias, cardiomyopathy and sudden death. In this review, we summarise the cardiac manifestations of COVID-19 infection and propose a simplified algorithm for patient management during the COVID-19 pandemic.

[Self-reported infections in the German National Cohort (GNC) in the context of the current research landscape]

BACKGROUND

Infectious diseases continue to play an important role for disease perception, health-economic considerations and public health in Germany. In recent years, infectious diseases have been linked to the development of non-communicable diseases. Analyses of the German National Cohort (GNC) may provide deeper insights into this issue and pave the way for new targeted approaches in disease prevention.

OBJECTIVES

The aim was to describe the tools used to assess infectious diseases and to present initial data on infectious disease frequencies, as well as to relate the GNC assessment tools to data collection methods in other studies in Germany.

METHODS

As part of the baseline examination, questions regarding infectious diseases were administered using both an interview and a self-administered touchscreen questionnaire. Data from the initial 101,787 GNC participants were analysed.

RESULTS

In the interview, 0.2% (HIV/AIDS) to 8.6% (shingles) of respondents reported ever having a medical diagnosis of shingles, postherpetic neuralgia (in cases where shingles was reported), hepatitis B/C, HIV/AIDS, tuberculosis or sepsis if treated in hospital. In the questionnaire, 12% (cystitis) to 81% (upper respiratory tract infections) of respondents reported having experienced at least one occurrence of upper or lower respiratory tract infections, gastrointestinal infections, cystitis or fever within the past 12 months.

OUTLOOK

The cross-sectional analyses of data and tools presented here - for example on determinants of susceptibility to self-reported infections - can be anticipated from the year 2021 onward. Beyond that, more extensive research into infectious disease epidemiology will follow, particularly once analyses of GNC biological materials have been performed.

Markov State Modelling of Disease Courses and Mortality Risks of Patients with Community-Acquired Pneumonia

Community-acquired pneumonia (CAP) is one of the most frequent infectious diseases worldwide, with high lethality. Risk evaluation is well established at hospital admission, and re-evaluation is advised for patients at higher risk. However, severe disease courses may develop from all levels of severity. We propose a stochastic continuous-time Markov model describing daily development of time courses of CAP severity. Disease states were defined based on the Sequential Organ Failure Assessment (SOFA) score. Model calibration was based on longitudinal data from 2838 patients with a primary diagnosis of CAP from four clinical studies (PROGRESS, MAXSEP, SISPCT, VISEP). We categorized CAP severity into five disease states and estimated transition probabilities for CAP progression between these states and corresponding sojourn times. Good agreement between model predictions and clinical data was observed. Time courses of mortality were correctly predicted for up to 28 days, including validation with patient data not used for model calibration. We conclude that CAP disease course follows a Markov process, suggesting the necessity of daily monitoring and re-evaluation of patient's risk. Our model can be used for regular updates of risk assessments of patients and could improve the design of clinical trials by estimating transition rates for different risk groups.