Tracheal intubation and invasive mechanical ventilation initiation is a procedure at high risk for arterial hypotension in intensive care unit. However, little is known about the relationship between pre-existing peripheral microvascular alteration and post-intubation hemodynamic instability (PIHI).

Prospective observational monocenter study conducted in an 18-bed medical ICU. Consecutive patients requiring tracheal intubation were eligible for the study. Global hemodynamic parameters (blood pressure, heart rate, cardiac function) and tissue perfusion parameters (arterial lactate, mottling score, capillary refill time [CRT], toe-to-room gradient temperature) were recorded before, 5 min and 2 h after tracheal intubation (TI). Post intubation hemodynamic instability (PIHI) was defined as any hemodynamic event requiring therapeutic intervention.

During 1 year, 120 patients were included, mainly male (59%) with a median age of 68 [57–77]. The median SOFA score and SAPS II were 6 [4–9] and 47 [37–63], respectively. The main indications for tracheal intubation were hypoxemia (51%), hypercapnia (13%), and coma (29%). In addition, 48% of patients had sepsis and 16% septic shock. Fifty-one (42%) patients develop PIHI. Univariate analysis identified several baseline factors associated with PIHI, including norepinephrine prior to TI, sepsis, tachycardia, fever, higher SOFA and high SAPSII score, mottling score ≥ 3, high lactate level and prolonged knee CRT. By contrast, mean arterial pressure, baseline cardiac index, and ejection fraction were not different between PIHI and No-PIHI groups. After adjustment on potential confounders, the mottling score was associated with a higher risk for PIHI (adjusted OR: 1.84 [1.21–2.82] per 1 point increased; p  = 0.005). Among both global haemodynamics and tissue perfusion parameters, baseline mottling score was the best predictor of PIHI (AUC: 0.72 (CI 95% [0.62–0.81]).

In non-selected critically ill patients requiring invasive mechanical ventilation, tissue hypoperfusion parameters, especially the mottling score, could be helpful to predict PIHI.