Your browser doesn't support javascript.
Respiratory Mechanics and Association With Inflammation in COVID-19-Related ARDS.
Bhatt, Alok; Deshwal, Himanshu; Luoma, Kelsey; Fenianos, Madelin; Hena, Kerry; Chitkara, Nishay; Zhong, Hua; Mukherjee, Vikramjit.
  • Bhatt A; Division of Pulmonary, Critical Care, and Sleep Medicine, New York University Grossman School of Medicine, New York, New York.
  • Deshwal H; Division of Pulmonary, Critical Care, and Sleep Medicine, New York University Grossman School of Medicine, New York, New York. himanshu.deshwal@gmail.com.
  • Luoma K; Division of Pulmonary, Critical Care, and Sleep, University of California, San Diego, San Diego, California.
  • Fenianos M; Department of Internal Medicine, Icahn School of Medicine at Mount Sinai Morningside and Mount Sinai West, New York, New York.
  • Hena K; Division of Pulmonary, Critical Care, and Sleep Medicine, New York University Grossman School of Medicine, New York, New York.
  • Chitkara N; Division of Pulmonary, Critical Care, and Sleep Medicine, New York University Grossman School of Medicine, New York, New York.
  • Zhong H; Department of Biostatistics, Epidemiology, and Research Design, New York University Grossman School of Medicine, New York, New York.
  • Mukherjee V; Division of Pulmonary, Critical Care, and Sleep Medicine, New York University Grossman School of Medicine, New York, New York.
Respir Care ; 66(11): 1673-1683, 2021 11.
Article in English | MEDLINE | ID: covidwho-1410801
ABSTRACT

BACKGROUND:

The novel coronavirus-associated ARDS (COVID-19 ARDS) often requires invasive mechanical ventilation. A spectrum of atypical ARDS with different phenotypes (high vs low static compliance) has been hypothesized in COVID-19.

METHODS:

We conducted a retrospective analysis to identify respiratory mechanics in COVID-19 ARDS. Berlin definition was used to categorize severity of ARDS. Correlational analysis using t test, chi-square test, ANOVA test, and Pearson correlation was used to identify relationship between subject variables and respiratory mechanics. The primary outcome was duration of mechanical ventilation. Secondary outcomes were correlation between fluid status, C- reactive protein, PEEP, and D-dimer with respiratory and ventilatory parameters.

RESULTS:

Median age in our cohort was 60.5 y with predominantly male subjects. Up to 53% subjects were classified as severe ARDS (median [Formula see text] = 86) with predominantly low static compliance (median Cst- 25.5 mL/cm H2O). The overall mortality in our cohort was 61%. The total duration of mechanical ventilation was 35 d in survivors and 14 d in nonsurvivors. High PEEP (r = 0.45, P < .001) and D-dimer > 2,000 ng/dL (P = .009) correlated with significant increase in physiologic dead space without significant correlation with [Formula see text]. Higher net fluid balance was inversely related to static compliance (r = -0.24, P = .045), and elevation in C- reactive protein was inversely related to [Formula see text] (r = -0.32, P = .02).

CONCLUSIONS:

In our cohort of mechanically ventilated COVID-19 ARDS subjects, high PEEP and D-dimer were associated with increase in physiologic dead space without significant effect on oxygenation, raising the question of potential microvascular dysfunction.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Respiratory Distress Syndrome / COVID-19 Type of study: Cohort study / Observational study / Prognostic study Topics: Variants Limits: Humans / Male Language: English Journal: Respir Care Year: 2021 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Respiratory Distress Syndrome / COVID-19 Type of study: Cohort study / Observational study / Prognostic study Topics: Variants Limits: Humans / Male Language: English Journal: Respir Care Year: 2021 Document Type: Article