Automated versus manual oxygen administration for patients admitted with acute cardiovascular disease - a study protocol of a randomised controlled trial.

INTRODUCTION: Oxygen treatment of hypoxaemia is considered an essential part of the treatment of patients who are acutely admitted with medical conditions affecting cardiovascular and/or pulmonary function. Despite the important role of oxygen administration for these patients, clinical evidence on how to control supplemental oxygen to avoid hypoxaemia and hyperoxia is limited. We aim to investigate whether an automatic closed-loop oxygen administration system (O2matic) may maintain normoxaemia better than usual care. METHODS: This study will be an investigator-initiated, prospective, randomised clinical trial. The patients are randomised during admission after informed consent is obtained, at a 1:1 ratio with conventional oxygen treatment or O2matic oxygen treatment for 24 hours. The primary outcome is time within the desired peripheral capillary oxygen saturation interval: 92-96%. CONCLUSION: This study will examine the clinical applicability of a novel automated feedback device termed O2matic and assess whether the device is superior to standard care in keeping the patients in the optimal saturation interval. We hypothesise that the O2matic will increase time within the desired saturation interval. FUNDING: Johannes Grand's salary during this project is supported by a research grant from the Danish Cardiovascular Academy funded by Novo Nordisk Foundation grant number NNF20SA0067242 and by The Danish Heart Foundation. CLINICALTRIALS: gov (ClinicalTrials.gov Identifier: NCT05452863). Registered on 11 July 2022.

Whole-cycle analysis of echocardiographic tissue Doppler velocities as a marker of biological age.

Purpose: Tissue Doppler imaging (TDI) is a sensitive marker of impaired cardiac function and different phases of the TDI curve carry different prognostic information. It is not known how continuous TDI curves change with age in normal subjects, and whether these changes differ from changes seen in individuals at risk of future cardiac events. Methods: A total of 1,763 individuals from the general population were examined with color TDI at the septal and lateral mitral sites. A low-risk group was defined as without cardiac risk factors (hypertension, diabetes or ischemic heart disease) at baseline and without any cardiac events (cardiovascular death or admission due to either heart failure or acute myocardial infarction) during 10-years follow-up. All TDI curves were corrected for heart rate, and whole-cycle analysis of age-related changes to TDI velocities was performed in both low-risk (n = 881) and high-risk individuals (n = 882). Results: In the low-risk population, four phases where myocardial velocity differed most (p < 10-10) according to age were identified [in a standardized cardiac cycle of 1 second (s)]: Systolic peak (0.09-0.13 s), systolic plateau (0.18-0.27 s), early diastole (0.43-0.54 s) and late diastole (0.88-0.95 s). With increasing age, systolic velocities decreased, early diastolic velocities decreased and had delayed peak, and late diastolic velocities increased until age 70 and then stopped increasing. In the high-risk population, comparison to corresponding age groups of the low-risk population showed: Lower early diastolic velocities in 20-40-year-olds; higher late diastolic velocities and lower peak systolic velocities in 40-60-year-olds; further decreased systolic velocities including the systolic plateau and decreased late diastolic velocities in 60-year-olds. The time segments around the systolic peak (p = 0.002) and early diastole (p < 0.001) differed significantly between the high-risk and low-risk population, thus making it possible to use the individual age gap between a TDI-derived biological age and the real chronological age as a tool to discriminate high-risk individuals from low-risk individuals. Conclusion: We found that individuals with cardiac risk factors display findings compatible with an accelerated aging of the heart and thus propose TDI-derived biological age as a tool to identify high-risk patients.