Polysomnographic findings in the ultra-rare McLeod syndrome: further documentation of sleep apnea as a possible feature.

Study Objectives: McLeod syndrome is a very rare multisystemic neurodegenerative disease linked to mutations in the gene. It has cardiac, neurologic, and neuromuscular manifestations and shares similarities with Huntington's disease. The aim of this study was to evaluate sleep patterns of patients affected by McLeod syndrome.

Higher in-hospital mortality in SARS-CoV-2 omicron variant infection compared to influenza infection-Insights from the CORONA Germany study.

Background: With the emergence of new subvariants, the disease severity of Severe Acute Respiratory Syndrome Coronavirus-2 has attenuated. This study aimed to compare the disease severity in patients hospitalized with omicron variant infection to those with influenza infection.

Methods: We compared data from the multicenter observational, prospective, epidemiological "CORONA Germany" (Clinical Outcome and Risk in hospitalized COVID-19 patients) study on patients infected with Severe Acute Respiratory Syndrome Coronavirus-2 to retrospective data on influenza infection cases from November 2016 to August 2022.

Comparison of machine learning methods with logistic regression analysis in creating predictive models for risk of critical in-hospital events in COVID-19 patients on hospital admission.

Background: Machine learning (ML) algorithms have been trained to early predict critical in-hospital events from COVID-19 using patient data at admission, but little is known on how their performance compares with each other and/or with statistical logistic regression (LR). This prospective multicentre cohort study compares the performance of a LR and five ML models on the contribution of influencing predictors and predictor-to-event relationships on prediction model´s performance.

Methods: We used 25 baseline variables of 490 COVID-19 patients admitted to 8 hospitals in Germany (March-November 2020) to develop and validate (75/25 random-split) 3 linear (L1 and L2 penalty, elastic net [EN]) and 2 non-linear (support vector machine [SVM] with radial kernel, random forest [RF]) ML approaches for predicting critical events defined by intensive care unit transfer, invasive ventilation and/or death (composite end-point: 181 patients).

Predicting the effectiveness of high-flow oxygen therapy in COVID-19 patients: a single-centre observational study.

Background: High-flow nasal cannula (HFNC) therapy is a helpful tool in the treatment of hypoxaemic respiratory failure. However, the clinical parameters predicting the effectiveness of HFNC in coronavirus-19 disease (COVID-19) patients remain unclear.

Methods: Sixteen COVID-19 patients undergoing HFNC in the Asklepios Lung Clinic Munich-Gauting, Germany between 16 March and 3 June 2020 were retrospectively included into the study.

Tackling the Waves of COVID-19: A Planning Model for Intrahospital Resource Allocation.

The current pandemic requires hospitals to ensure care not only for the growing number of COVID-19 patients but also regular patients. Hospital resources must be allocated accordingly. To provide hospitals with a planning model to optimally allocate resources to intensive care units given a certain incidence of COVID-19 cases.

Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through 'reverse phenotyping'.

The in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients.

Automated quantitative thin slice volumetric low dose CT analysis predicts disease severity in COVID-19 patients.

Purpose: This study aimed to identify predictive (bio-)markers for COVID-19 severity derived from automated quantitative thin slice low dose volumetric CT analysis, clinical chemistry and lung function testing.

Methods: Seventy-four COVID-19 patients admitted between March 16th and June 3rd 2020 to the Asklepios Lung Clinic Munich-Gauting, Germany, were included in the study. Patients were categorized in a non-severe group including patients hospitalized on general wards only and in a severe group including patients requiring intensive care treatment.

Investigation of various types of neurocardiogenic response to head-up tilting by extended hemodynamic and neurohumoral monitoring.

Background: The pathophysiology of neurocardiogenic syncope is heterogeneous. This study aim was to analyze whether extended monitoring during tilt-table testing provided additional information on the hemodynamic and vegetative state prior to neurocardiogenic syncope.

Methods: This retrospective analysis is based on data of head-up tilt-table testing of 40 unselected consecutive patients with a history of unexplained syncope.