Abstrakt
A total of 3,831 participants without hypertension at baseline were included in simulation analyses. Included participants had ≥ 28 days of nightly apnea-hypopnea index (AHI) recordings via an under-mattress sensor and ≥ three separate BP measurements over a 3-month baseline period followed by ≥ three separate BP measurements 6 to 9 months postbaseline. Incident hypertension was defined as a mean systolic BP ≥ 140 mm Hg or a mean diastolic BP ≥ 90 mm Hg. Simulated trials (1,000) were performed, using bootstrap methods to investigate the effect of variable numbers of nights (x = 1-56 per participant) to quantify AHI and the ability to detect associations between OSA and incident hypertension via logistic regression adjusted for age, sex, and BMI.
A total of 3,831 participants without hypertension at baseline were included in simulation analyses. Included participants had ≥ 28 days of nightly apnea-hypopnea index (AHI) recordings via an under-mattress sensor and ≥ three separate BP measurements over a 3-month baseline period followed by ≥ three separate BP measurements 6 to 9 months postbaseline. Incident hypertension was defined as a mean systolic BP ≥ 140 mm Hg or a mean diastolic BP ≥ 90 mm Hg. Simulated trials (1,000) were performed, using bootstrap methods to investigate the effect of variable numbers of nights (x = 1-56 per participant) to quantify AHI and the ability to detect associations between OSA and incident hypertension via logistic regression adjusted for age, sex, and BMI.
Əsas mətn
The implications of muscle mass in different clinical scenarios have modified the way we think about muscle; it is now considered a crucial element in metabolism with endocrine and paracrine functions,
rather than simply a mechanical organ. The study of muscle quality and quantity is one of the variables that define sarcopenia,
and the distinction between these terms should always be acknowledged.
Low muscle mass has been identified as a negative predictor for chronic diseases such as cancer or cirrhosis, and more recently with COVID-19.
In this issue of
CHEST, van Bakel et al
describe an association between low cross-sectional area (CSA) muscle mass in CT scans of COVID-19 patients and in-hospital mortality. Although other studies have found low muscle mass to be involved in adverse outcomes in COVID-19 patients,
the significance of this novel work is that this association remains in multivariate analysis after adjusting with the 4C mortality score. The precise mechanism of this association is yet to be determined, but a relationship between muscle mass and physiological reserve should be explored.
One strength of this work is that it finally provides an example of how to intertwine a clinical score, such as the 4C mortality score for COVID-19, with muscle mass assessment. However, whether this extra effort is worth it is unclear. In this case, adding muscle mass to an already validated score
did not significantly increase its discriminatory performance, limiting the clinical applications of muscle mass.
The use of muscle mass as a clinic parameter is still far from being widely available, for several reasons. First, there is no universal form of assessment, beginning with the fact that there are different software programs to analyze imaging CSA, which need a human hand to determine CSA, and assessment is time consuming. Second, a uniform cutoff value to define low muscular mass has not been agreed on, although efforts to expand these evaluations have been made.
Third, CSA requires either a CT, which exposes the patient to radiation, or an MRI,
which avoids radiation but is expensive and not widely available. Moreover, performing any of these imaging studies solely to assess body composition is not recommended. In the future, artificial intelligence would be a key tool to assess muscle mass more efficiently,
as van Bakel et al
discussed in their paper, and it will be a turning point in the process of developing a database
of body composition in different populations for further understanding of their metabolic profiles. This will be a step forward in individualized medicine in any case scenario.
Currently, most body composition literature is retrospective. But eventually, muscle mass measurement will be available for most patients, just like any other clinical parameter we use in our daily assessment, such as weight, and prospective studies will be developed to understand the complex and dynamic relationships between muscle and disease prognosis, so we would be able to incorporate these data into clinical scores as van Bakel et al
did.
Prompt identification of a patient with low muscle mass is important because it can be optimized with preconditioning programs, such as before surgery.
However, would this be as possible or as favorable in an acute condition as in COVID-19? Unfortunately, we still do not have an answer to this question. Nevertheless, it has been described that simple interventions such as adjusting hospital menus can improve or prevent patients’ muscle loss.
Furthermore, if avoidance of muscle wasting by pharmacologic means ever becomes a real option, it may be the key to modifying the course of acute diseases. We have evidence that IL-6 receptor antibodies have been shown to decrease the detrimental effect of this cytokine in mice muscle
; research in this area remains to be explored.
Although research in the field of body composition has answered some questions, it has also raised more areas for researchers to ideally evaluate not only muscle mass but also function and quality, as well as its physiologic role in acute disease and possible treatments.
Financial/Nonfinancial Disclosures
None declared.
