Purpose:The optimal ventilatory settings in patients after cardiac arrest and their association with outcome remain unclear. The aim of this study was to describe the ventilatory settings applied in the first 72 h of mechanical ventilation in patients after out-of-hospital cardiac arrest and their association with 6-month outcomes.Methods: Preplanned sub-analysis of the Target Temperature Management-2 trial. Clinical outcomes were mortality and functional status (assessed by the Modified Rankin Scale) 6 months after randomization.Results: A total of 1848 patients were included (mean age 64 [Standard Deviation, SD = 14] years). At 6 months, 950 (51%) patients were alive and 898 (49%) were dead. Median tidal volume (V T ) was 7 (Interquartile range, IQR = 6.2-8.5) mL per Predicted Body Weight (PBW), positive end expiratory pressure (PEEP) was 7 (IQR = 5-9) cmH 2 0, plateau pressure was 20 cmH 2 0 (IQR = 17-23), driving pressure was 12 cmH 2 0 (IQR = 10-15), mechanical power 16.2 J/min (IQR = 12.1-21.8), ventilatory ratio was 1.27 (IQR = 1.04-1.6), and respiratory rate was 17 breaths/minute (IQR = 14-20). Median partial pressure of oxygen was 87 mmHg (IQR = 75-105), and partial pressure of carbon dioxide was
Background Optimal oxygen targets in patients resuscitated after cardiac arrest are uncertain. The primary aim of this study was to describe the values of partial pressure of oxygen values (PaO2) and the episodes of hypoxemia and hyperoxemia occurring within the first 72 h of mechanical ventilation in out of hospital cardiac arrest (OHCA) patients. The secondary aim was to evaluate the association of PaO2 with patients’ outcome. Methods Preplanned secondary analysis of the targeted hypothermia versus targeted normothermia after OHCA (TTM2) trial. Arterial blood gases values were collected from randomization every 4 h for the first 32 h, and then, every 8 h until day 3. Hypoxemia was defined as PaO2 < 60 mmHg and severe hyperoxemia as PaO2 > 300 mmHg. Mortality and poor neurological outcome (defined according to modified Rankin scale) were collected at 6 months. Results 1418 patients were included in the analysis. The mean age was 64 ± 14 years, and 292 patients (20.6%) were female. 24.9% of patients had at least one episode of hypoxemia, and 7.6% of patients had at least one episode of severe hyperoxemia. Both hypoxemia and hyperoxemia were independently associated with 6-month mortality, but not with poor neurological outcome. The best cutoff point associated with 6-month mortality for hypoxemia was 69 mmHg (Risk Ratio, RR = 1.009, 95% CI 0.93–1.09), and for hyperoxemia was 195 mmHg (RR = 1.006, 95% CI 0.95–1.06). The time exposure, i.e., the area under the curve (PaO2-AUC), for hyperoxemia was significantly associated with mortality (p = 0.003). Conclusions In OHCA patients, both hypoxemia and hyperoxemia are associated with 6-months mortality, with an effect mediated by the timing exposure to high values of oxygen. Precise titration of oxygen levels should be considered in this group of patients. Trial registration: clinicaltrials.gov NCT02908308, Registered September 20, 2016.
AimsCOVID‐19 is especially severe for elderly subjects with cardiometabolic and respiratory comorbidities. Neck circumference (NC) has been shown to be strongly related to cardiometabolic and respiratory illnesses even after adjustment for body mass index (BMI). We performed a prospective study to investigate the potential of NC to predict the need for invasive mechanical ventilation (IMV) in adult COVID‐19 inpatients.Materials and MethodsWe prospectively and consecutively enrolled COVID‐19 adult patients admitted to dedicated medical wards of two Italian hospitals from 25 March to 7 April 2020. On admission, clinical, biochemical and anthropometric data, including BMI and NC were collected. As primary outcome measure, the maximum respiratory support received was evaluated. Follow‐up time was 30 days from hospital admission.ResultsWe enrolled 132 subjects (55.0‐75.8 years, 32% female). During the study period, 26 (19.7%) patients underwent IMV. In multivariable logistic regression analyses, after adjusting for age, sex, diabetes, hypertension and COPD, NC resulted independently and significantly associated with IMV risk (adjusted OR 1.260—per 1 cm increase 95% CI:1.120‐1.417; P < .001), with a stronger association in the subgroup with BMI ≤30 Kg/m2 (adjusted OR 1.526; 95% CI:1.243‐1.874; P < .001). NC showed a good discrimination power in predicting patients requiring IMV (AUC 0.783; 95% CI:0.684‐0.882; P < .001). In particular, NC > 40.5 cm (>37.5 for females and >42.5 for males) showed a higher and earlier IMV risk compared to subjects with lower NC (Log‐rank test: P < .001).ConclusionsNC is an easy to measure parameter able to predict the need for IMV in adult COVID‐19 inpatients.
BackgroundElectroencephalography (EEG) is widely used to monitor critically ill patients. However, EEG interpretation requires the presence of an experienced neurophysiologist and is time-consuming. Aim of this study was to evaluate whether parameters derived from an automated pupillometer (AP) might help to assess the degree of cerebral dysfunction in critically ill patients.MethodsProspective study conducted in the Department of Intensive Care of Erasme University Hospital in Brussels, Belgium. Pupillary assessments were performed using the AP in three subgroups of patients, concomitantly monitored with continuous EEG: “anoxic brain injury”, “Non-anoxic brain injury” and “other diseases”. An independent neurologist blinded to patient's history and AP results scored the degree of encephalopathy and reactivity on EEG using a standardized scale. The mean value of Neurologic Pupil Index (NPi), pupillary size, constriction rate, constriction and dilation velocity (CV and DV) and latency for both eyes, obtained using the NPi®-200 (Neuroptics, Laguna Hills, CA, USA), were reported.ResultsWe included 214 patients (mean age 60 years, 55% male). EEG tracings were categorized as: mild (n = 111, 52%), moderate (n = 65, 30%) or severe (n = 16, 8%) encephalopathy; burst-suppression (n = 19, 9%) or suppression background (n = 3, 1%); a total of 38 (18%) EEG were classified as “unreactive”. We found a significant difference in all pupillometry variables among different EEG categories. Moreover, an unreactive EEG was associated with lower NPi, pupil size, pupillary reactivity, CV and DV and a higher latency than reactive recordings. Low DV (Odds ratio 0.020 [95% confidence intervals 0.002–0.163]; p < 0.01) was independently associated with an unreactive EEG, together with the use of analgesic/sedative drugs and high lactate concentrations. In particular, DV values had an area under the curve (AUC) of 0.86 [0.79–0.92; p < 0.01] to predict the presence of unreactive EEG. In subgroups analyses, AUC of DV to predict unreactive EEG was lower (0.72 [0.56–0.87]; p < 0.01) in anoxic brain injury than Non-anoxic brain injury (0.92 [0.85–1.00]; p < 0.01) and other diseases (0.96 [0.90–1.00]; p < 0.01).ConclusionsThis study suggests that low DV measured by the AP might effectively identify an unreactive EEG background, in particular in critically ill patients without anoxic brain injury.
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