Publications

After induction of cecal perforation, 20 anesthetized sheep were randomized to be treated, when arterial blood pressure fell below 75 mm Hg, with vasopressin (fixed dose of 0.02 U/minute), norepinephrine (0.5-5 microg/kg/minute titrated to maintain mean arterial pressure between 75 and 85 mm Hg), vasopressin + norepinephrine (vasopressin at fixed dose 0.01 U/minute plus norepinephrine titrated as for norepinephrine only group), or no vasopressor (Ringer's lactate [control]). Mean arterial pressure was well maintained in all treatment groups. Superior mesenteric arterial blood flow was significantly lower in the vasopressin + norepinephrine group than in the vasopressin group. Vasopressin alone or combined with norepinephrine limited the increase in blood lactate concentration and ileal PCO2-gap compared with control and norepinephrine groups. Urine output was higher in the vasopressin group than in control and norepinephrine groups. Survival time was longer in the vasopressin (30 +/- 6 hours) and vasopressin + norepinephrine (30 +/- 3 hours) groups than in the norepinephrine group (20 +/- 1 hours, p < 0.05) and in all treatment groups than in the control group (17 +/- 2 hours, p < 0.05). Tissue injury was less severe in the vasopressin and vasopressin + norepinephrine groups than in the others. In this clinically relevant model of septic shock due to peritonitis, vasopressin administration (alone or with norepinephrine) can prolong survival.

Fontana, Vito; Dell’Anna, Antonio; Chase, J Geoffrey; Desaive, Thomas; Vincent, Jean-Louis; Preiser, Jean-Charles; Oddo, Mauro; Taccone, Fabio Silvio

Red cell distribution width (RDW) is a quantitative measure of the variability in size of erythrocytes and it is used for the differential diagnosis of anemia. Moreover, in critically ill patients, high RDW values have been associated with increased hospital mortality. No data on the impact of RDW on the outcome of patients resuscitated from cardiac arrest (CA) are available.

Introduction: β-lactams are widely used as first-line treatment in critically ill patients. It has been shown that creatinine clearance (CrCl) influences the pharmacodynamics of these drugs. Hypothesis: Variations in CrCl are correlated with changes in β-lactams concentrations. Methods: We reviewed the data of all adult patients admitted to our Dept of Intensive Care (ICU) from January 2010 to June 2012, in whom routine therapeutic drug monitoring (TDM) of broad-spectrum β-lactams (ceftazidime, cefepime, piperacillin and meropenem) was performed. Patients were included if they had at least two TDMs during their ICU stay for the same antibiotic and if they were not concomitantly treated by any extracorporeal replacement therapy. Serum drug concentrations were measured by high-performance liquid chromatography (HPLC-UV). Blood samples were taken twice during the elimination phase after a 30-min intravenous drug administration. Antibiotic PKs were calculated using a one-compartment model and the percentage of time spent above four times the MIC (%T>4xMIC) for Pseudomonas aeruginosa as well as antibiotic clearance (ATB-CL) were obtained. CrCl was measured using 24-hours urine collection on the same period than TDM. Results: We included 56 patients (median age 59 years; 40/56 male gender, median APACHE II score on admission 19; 73% treated by mechanical ventilation, ICU mortality 20%). Median time from the start of antibiotic therapy to the first and second TDM was 2 and 5 days, respectively. We found that %T>4xMIC and ATB-CL were significantly correlated with CrCl on the first TDM (Spearman r = -0.41, p=0.002; r = 0.56, p<0.001, respectively) and the second TDM (Spearman r = -0.61, p<0.001; r = 0.62, p<0.001, respectively). Nevertheless, the changes in the %T>4xMIC and ATB-CL were not correlated to the changes in CrCl (Spearman r =0.22, p=0.09 and Spearman r = -0.17, p=0.2). Conclusions: Although CrCl was significantly correlated with the concentrations of broad-spectrum β-lactams, changes in CrCl do not reliably predict variations in drug clearance and pharmacodynamics.

<b><i>Purpose:</i></b> To document and describe the use of a hospital-wide, 24-hour cardiorespiratory physiotherapy service run by an intensive care unit (ICU) team of physiotherapists. <b><i>Methods:</i></b> We prospectively collected data on all non-ICU hospital patients who used the 24-hours-per-day cardiorespiratory physiotherapy service over a 1-year period between July 2013 and June 2014. The ICU physiotherapists documented the reason, origin of referral, time of call, and type and frequency of treatment of each patient. <b><i>Results:</i></b> Over the 1-year period, the ICU physiotherapists administered 2,192 out-of-hours cardiorespiratory physiotherapy treatments (<i>n</i>=685 patients) outside the ICU. Most referrals originated from the emergency department (25%), the cardiopulmonary transplant unit (20%), and the pulmonology department (16%). Referrals were from a physiotherapist in 49% of cases, from a nurse in 32%, and from a physician in 19%. Of these, 89% were made between 4:00 p.m. and 8:00 a.m., and sputum retention was the most frequent reason (86%). <b><i>Conclusion:</i></b> Although proving its cost effectiveness is difficult, organizing a 24-hours-per-day, 7-days-per-week cardiorespiratory physiotherapy service in a large hospital is feasible.

Therapeutic agents for the novel coronavirus disease 2019 (COVID-19) have been proposed, but evidence supporting their use is limited. A machine learning algorithm was developed in order to identify a subpopulation of COVID-19 patients for whom hydroxychloroquine was associated with improved survival; this population might be relevant for study in a clinical trial. A pragmatic trial was conducted at six United States hospitals. We enrolled COVID-19 patients that were admitted between 10 March and 4 June 2020. Treatment was not randomized. The study endpoint was mortality; discharge was a competing event. Hazard ratios were obtained on the entire population, and on the subpopulation indicated by the algorithm as suitable for treatment. A total of 290 patients were enrolled. In the subpopulation that was identified by the algorithm, hydroxychloroquine was associated with a statistically significant (<i>p</i> = 0.011) increase in survival (adjusted hazard ratio 0.29, 95% confidence interval (CI) 0.11-0.75). Adjusted survival among the algorithm indicated patients was 82.6% in the treated arm and 51.2% in the arm not treated. No association between treatment and mortality was observed in the general population. A 31% increase in survival at the end of the study was observed in a population of COVID-19 patients that were identified by a machine learning algorithm as having a better outcome with hydroxychloroquine treatment. Precision medicine approaches may be useful in identifying a subpopulation of COVID-19 patients more likely to be proven to benefit from hydroxychloroquine treatment in a clinical trial.