Challenges in understanding host genetics and severity of community-acquired pneumonia

A heritable predisposition to early death due to infection was observed three decades ago [1]. Apart from exciting discoveries in the field of primary immunodeficiencies, genetic variants predisposing to severe infection and outcome at a population level remain largely elusive [2, 3]. Genetic association studies on sepsis were largely based on a candidate gene approach. In 2015, Rautanenet al. [4] reported the first genome-wide association study (GWAS) in sepsis. A meta-analysis of three independent cohorts of critically ill patients with sepsis recruited in numerous centres from Europe, Canada, United States, Australia, New Zealand and South Africa was performed. They reported that the C allele of the single-nucleotide variant (SNV) rs4957796 at the FER gene was associated with a protective additive effect in 28-day survival only in patients with pneumonia, but not in those with other causes of sepsis. Schönewecket al. [5] did not replicate the findings Rautanenet al. [4] in a mixed cohort of patients of European ancestry with severe sepsis admitted at German intensive care units (ICUs). However, their study was underpowered for mortality. Hinzet al.[6], in a cohort of white patients with acute respiratory distress syndrome (ARDS) due to pneumonia from a single Centre in Germany, found that the rs4957796 TT genotype was associated with a higher 90-day mortality exclusively in the small subgroup of patients with severe ARDS.

This study found no association of the top two associated FER variants with severity of community-acquired pneumonia. Precise characterisation of phenotypes may be required in order to unravel the genetic mechanisms predisposing to poor outcome in sepsis.https://bit.ly/3jc9SmR

Usefulness of cephalometry in sparing polysomnography of patients with suspected obstructive sleep apnea

The aim of this investigation was to evaluate the contribution of cephalometry to a statistical model integrating clinical, physical, and oximetric variables, to reduce demands for polysomnographies. Two hundred and twenty-five consecutive patients that had been referred to the sleep clinic for suspected obstructive sleep apnea (OSA) were studied. The clinical assessment of all patients consisted of a sleep related questionnaire, the Epworth sleepiness scale, and a physical examination. In addition, they all underwent spirometry, cephalometry, and a full polysomnography. The clinical variables related with OSA were questions concerning witnessing of apneas by bed partners, intensity of snoring, a history of hypertension, and nocturia. A significant relation was also found with score on the Epworth scale, sex, age, body mass index, neck and waist circumferences, total number and frequency of oxygen desaturations, and the lowest oxygen saturation value. Significant cephalometric measurements were: the linear distance from gonion to gnathion, from the hyoid bone to the mandibular plane, and from the posterior nasal spine to the tip of the soft palate, and the thickness of the uvula as well. A statistical model was built to estimate a patient's probability of having OSA based on clinical variables, physical examination, pulse oximetry, and cephalometry. The validation of this model demonstrated a remarkable ability in reducing the number of polysomnographic studies. We conclude that cephalometry combined with clinical variables, physical examination, and nocturnal oximetry is useful in the diagnosis of OSA and enables the sparing of a considerable number of polysomnographies.