Data on the relationship between antimicrobial resistance and mortality remain scarce, and this relationship needs to be investigated in intensive care units (ICUs). The aim of this study was to compare the ICU mortality rates between patients with ICU-acquired pneumonia due to highly antimicrobial-resistant (HAMR) bacteria and those with ICU-acquired pneumonia due to non-HAMR bacteria. We conducted a multicenter, retrospective cohort study using the French National Surveillance Network for Healthcare Associated Infection in ICUs (“REA-Raisin”) database, gathering data from 200 ICUs from January 2007 to December 2016. We assessed all adult patients who were hospitalized for at least 48 h and presented with ICU-acquired pneumonia caused by S. aureus, Enterobacteriaceae, P. aeruginosa, or A. baumannii. The association between pneumonia caused by HAMR bacteria and ICU mortality was analyzed using the whole sample and using a 1:2 matched sample. Among the 18,497 patients with at least one documented case of ICU-acquired pneumonia caused by S. aureus, Enterobacteriaceae, P. aeruginosa, or A. baumannii, 3081 (16.4%) had HAMR bacteria. The HAMR group was associated with increased ICU mortality (40.3% vs. 30%, odds ratio (OR) 95%, CI 1.57 [1.45–1.70], P < 0.001). This association was confirmed in the matched sample (3006 HAMR and 5640 non-HAMR, OR 95%, CI 1.39 [1.27–1.52], P < 0.001) and after adjusting for confounding factors (OR ranged from 1.34 to 1.39, all P < 0.001). Our findings suggest that ICU-acquired pneumonia due to HAMR bacteria is associated with an increased ICU mortality rate, ICU length of stay, and mechanical ventilation duration.
This study aimed to assess the viability of using the venous-to-arterial carbon dioxide partial pressure difference (P(v–a)CO2) to predict clinical worsening of septic shock, depending on central venous oxygen saturation (ScvO2). The prospective, observational, multicentric study conducted in three intensive care units (ICUs) included all patients with a septic shock episode during the first 6 h, with 122 patients assessed. Clinical worsening was defined as an increase of sequential organ failure assessment (SOFA) scores ≥1 (ΔSOFA ≥1) within 2 days. To assess the ability of P(v–a)CO2 to predict clinical worsening, univariate and multivariate analyses were performed according to ΔSOFA. A receiver-operating characteristic (ROC) analysis was used to confirm model predictions. Associations between P(v–a)CO2 and mortality were explored using correlations. Using multivariate analyses, two independent factors associated with ΔSOFA at least 1 were identified: an averaged 6-h value of lactate concentration (Lac [1–6]) (odds ratios [ORs], 2.43 [95% confidence interval, CI, 1.20–4.89]; P = 0.013) and an averaged 6-h value of P(v–a)CO2 (P(v–a)CO2 [1–6]) (OR, 1.49 [95% CI, 1.04–2.15]; P = 0.029). ROC analysis confirmed that Lac [1–6] and P(v–a)CO2 [1–6] were significantly associated with ΔSOFA at least 1, whereas ScvO2 [1–6] was not. Finally, ΔSOFA at least 1 was associated with higher 28-day (76% vs. 10%, P = 0.001) and ICU (83% vs. 12%, P = 0.001) mortality rates, which were higher in patients with P(v–a)CO2 [1–6] more than 5.8 mmHg (57% vs. 33%; P = 0.012). In conclusion, P(v–a)CO2 may help predict outcomes for septic shock patients regardless of ScvO2 values.
Our goal was to determine the relevant variables and patient phenotypes to predict sepsis outcomes. We performed an ancillary study concerning 119 patients from three intensive care units (ICUs) in septic shock at ICU admittance (T0). We de ned clinical worsening as having an increased Sequential Organ Failure Assessment (SOFA) score ≥ 1 48 hours after admission (ΔSOFA ≥ 1). We performed univariate and multivariate analyses according to 28-day mortality rate and ΔSOFA ≥ 1, and determined three patient phenotypes: safe, intermediate and poor. Persistence of the intermediate and poor phenotypes after T0 were de ned as poor outcomes. At T0, the multivariate analysis showed two variables associated with 28-day mortality rate: norepinephrine dose and serum lactate concentration. Regarding ΔSOFA ≥ 1, we identi ed three variables at T0: norepinephrine dose, serum lactate concentration and venous-to-arterial carbon dioxide partial pressure difference (P(v-a)CO 2 ). At T0, the three phenotypes (safe, intermediate, and poor) were distributed in 28 (24%), 70 (59%) and 21 (18%) patients, respectively.We thus suggested an algorithm featuring norepinephrine dose, serum lactate concentration and P(va)CO 2 to predict patient outcomes and obtained an area under the curve (AUC) of 74% (63-85%). In conclusion, our ndings underline that identifying relevant variables and phenotypes may help physicians recognize patient outcomes.
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