31 research outputs found
Regional anesthesia with noninvasive ventilation for shoulder surgery in a patient with severe chronic obstructive pulmonary disease: a case report
Interscalene block (ISB) impairs ipsilateral lung function and generally is not used for patients with respiratory insufficiency. We present a 49-year-old man with chronic obstructive pulmonary disease scheduled for shoulder surgery. He was given a regional technique with an ISB (short-acting local anesthetic to minimize duration of diaphragmatic dysfunction) and suprascapular and axillary nerves blocks (long-acting local anesthetic). He was supported with noninvasive ventilation during the time of hemidiaphragmatic paralysis as documented by serial ultrasound examination. A discussion about ISB and its alternatives (general anesthesia versus brachial plexus block versus selective peripheral nerve blocks) always should occur for patients at risk for pulmonary complications
Simulation as a New Tool to Establish Benchmark Outcome Measures in Obstetrics
Background
There are not enough clinical data from rare critical events to calculate statistics to decide if the management of actual events might be below what could reasonably be expected (i.e. was an outlier).
Objectives
In this project we used simulation to describe the distribution of management times as an approach to decide if the management of a simulated obstetrical crisis scenario could be considered an outlier.
Design
Twelve obstetrical teams managed 4 scenarios that were previously developed. Relevant outcome variables were defined by expert consensus. The distribution of the response times from the teams who performed the respective intervention was graphically displayed and median and quartiles calculated using rank order statistics.
Results
Only 7 of the 12 teams performed chest compressions during the arrest following the 'cannot intubate/cannot ventilate' scenario. All other outcome measures were performed by at least 11 of the 12 teams. Calculation of medians and quartiles with 95% CI was possible for all outcomes. Confidence intervals, given the small sample size, were large.
Conclusion
We demonstrated the use of simulation to calculate quantiles for management times of critical event. This approach could assist in deciding if a given performance could be considered normal and also point to aspects of care that seem to pose particular challenges as evidenced by a large number of teams not performing the expected maneuver. However sufficiently large sample sizes (i.e. from a national data base) will be required to calculate acceptable confidence intervals and to establish actual tolerance limits
Assessment of brain midline shift using sonography in neurosurgical ICU patients
Abstract
Introduction
Brain midline shift (MLS) is a life-threatening condition that requires urgent diagnosis and treatment. We aimed to validate bedside assessment of MLS with Transcranial Sonography (TCS) in neurosurgical ICU patients by comparing it to CT.
Methods
In this prospective single centre study, patients who underwent a head CT were included and a concomitant TCS performed. TCS MLS was determined by measuring the difference between the distance from skull to the third ventricle on both sides, using a 2 to 4 MHz probe through the temporal window. CT MLS was measured as the difference between the ideal midline and the septum pellucidum. A significant MLS was defined on head CT as >0.5 cm.
Results
A total of 52 neurosurgical ICU patients were included. The MLS (mean ± SD) was 0.32 ± 0.36 cm using TCS and 0.47 ± 0.67 cm using CT. The Pearson’s correlation coefficient (r2) between TCS and CT scan was 0.65 (P <0.001). The bias was 0.09 cm and the limits of agreements were 1.10 and -0.92 cm. The area under the ROC curve for detecting a significant MLS with TCS was 0.86 (95% CI =0.74 to 0.94), and, using 0.35 cm as a cut-off, the sensitivity was 84.2%, the specificity 84.8% and the positive likelihood ratio was 5.56.
Conclusions
This study suggests that TCS could detect MLS with reasonable accuracy in neurosurgical ICU patients and that it could serve as a bedside tool to facilitate early diagnosis and treatment for patients with a significant intracranial mass effect
Predicting preload responsiveness using simultaneous recordings of inferior and superior vena cavae diameters
Abstract
Introduction
Echocardiographic indices based on respiratory variations of superior and inferior vena cavae diameters (ΔSVC and ΔIVC, respectively) have been proposed as predictors of fluid responsiveness in mechanically ventilated patients, but they have never been compared simultaneously in the same patient sample. The aim of this study was to compare the predictive value of these echocardiographic indices when concomitantly recorded in mechanically ventilated septic patients.
Methods
Septic shock patients requiring hemodynamic monitoring were prospectively enrolled over a 1-year period in a mixed medical surgical ICU of a university teaching hospital (Toulouse, France). All patients were mechanically ventilated. Predictive indices were obtained by transesophageal and transthoracic echocardiography and were calculated as follows: (Dmax - Dmin)/Dmax for ΔSVC and (Dmax - Dmin)/Dmin for ΔIVC, where Dmax and Dmin are the maximal and minimal diameters of SVC and IVC. Measurements were performed at baseline and after a 7-ml/kg volume expansion using a plasma expander. Patients were separated into responders (increase in cardiac index ≥15%) and nonresponders (increase in cardiac index <15%).
Results
Among 44 included patients, 26 (59%) patients were responders (R). ΔSVC was significantly more accurate than ΔIVC in predicting fluid responsiveness. The areas under the receiver operating characteristic curves for ΔSVC and ΔIVC regarding assessment of fluid responsiveness were significantly different (0.74 (95% confidence interval (CI): 0.59 to 0.88) and 0.43 (95% CI: 0.25 to 0.61), respectively (P = 0.012)). No significant correlation between ΔSVC and ΔIVC was found (r = 0.005, P = 0.98). The best threshold values for discriminating R from NR was 29% for ΔSVC, with 54% sensitivity and 89% specificity, and 21% for ΔIVC, with 38% sensitivity and 61% specificity.
Conclusions
ΔSVC was better than ΔIVC in predicting fluid responsiveness in our cohort. It is worth noting that the sensitivity and specificity values of ΔSVC and ΔIVC for predicting fluid responsiveness were lower than those reported in the literature, highlighting the limits of using these indices in a heterogeneous sample of medical and surgical septic patients
Perineural dexamethasone attenuates liposomal bupivacaine-induced delayed neural inflammation in mice in vivo
Perioperative Risk Assessment of Patients Using the MyRISK Digital Score Completed Before the Preanesthetic Consultation: Prospective Observational Study
BackgroundThe ongoing COVID-19 pandemic has highlighted the potential of digital health solutions to adapt the organization of care in a crisis context.
ObjectiveOur aim was to describe the relationship between the MyRISK score, derived from self-reported data collected by a chatbot before the preanesthetic consultation, and the occurrence of postoperative complications.
MethodsThis was a single-center prospective observational study that included 401 patients. The 16 items composing the MyRISK score were selected using the Delphi method. An algorithm was used to stratify patients with low (green), intermediate (orange), and high (red) risk. The primary end point concerned postoperative complications occurring in the first 6 months after surgery (composite criterion), collected by telephone and by consulting the electronic medical database. A logistic regression analysis was carried out to identify the explanatory variables associated with the complications. A machine learning model was trained to predict the MyRISK score using a larger data set of 1823 patients classified as green or red to reclassify individuals classified as orange as either modified green or modified red. User satisfaction and usability were assessed.
ResultsOf the 389 patients analyzed for the primary end point, 16 (4.1%) experienced a postoperative complication. A red score was independently associated with postoperative complications (odds ratio 5.9, 95% CI 1.5-22.3; P=.009). A modified red score was strongly correlated with postoperative complications (odds ratio 21.8, 95% CI 2.8-171.5; P=.003) and predicted postoperative complications with high sensitivity (94%) and high negative predictive value (99%) but with low specificity (49%) and very low positive predictive value (7%; area under the receiver operating characteristic curve=0.71). Patient satisfaction numeric rating scale and system usability scale median scores were 8.0 (IQR 7.0-9.0) out of 10 and 90.0 (IQR 82.5-95.0) out of 100, respectively.
ConclusionsThe MyRISK digital perioperative risk score established before the preanesthetic consultation was independently associated with the occurrence of postoperative complications. Its negative predictive strength was increased using a machine learning model to reclassify patients identified as being at intermediate risk. This reliable numerical categorization could be used to objectively refer patients with low risk to teleconsultation