Objectives: We sought to assess the incidence of acetaminophen-induced hypotension. Our secondary objectives were to describe systemic hemodynamic changes and factors associated with this complication. Design: Prospective observational study. Setting: Three ICUs. Patients: Adult patients requiring IV acetaminophen infusion. Arterial pressure was monitored via an arterial catheter for 3 hours. Hypotension was defined as a decrease in the mean arterial pressure of greater than or equal to 15% compared with the baseline. Results: Overall, 160 patients were included in this study. Eighty-three patients (51.9%) experienced acetaminophen-induced hypotension according to our definition. In patients with acetaminophen-induced hypotension, the nadir mean arterial pressure was 64 mm Hg (95% CI, 54–74). Hypotension was observed 30 minutes (95% CI, 15–71) after acetaminophen infusion. Changes in mean arterial pressure were closely correlated with decreases in the diastolic arterial pressure (r ² = 0.92) and to a lesser extent with changes in the pulse pressure (r ² = 0.18) and heart rate (r ² = 0.09). Changes in the body temperature were not correlated with changes in mean arterial pressure (r ² = 0.0002; p = 0.85). None of the patients’ baseline characteristics (shock, use of angiotensin-converting enzyme inhibitor/angiotensin II receptor blockers, lactates, renal replacement therapy, chronic heart disease, and indication for acetaminophen infusion) or clinically relevant characteristics (baseline severity according to Logistic Organ Dysfunction score, need for vasopressors, use of antihypertensive agents, need for mechanical ventilation, or changes in the body temperature) were independently associated with acetaminophen-induced hypotension. Among patients with acetaminophen-induced hypotension, 29 (34.9%) required therapeutic intervention. Conclusions: Half of the patients who received IV injections of acetaminophen developed hypotension, and up to one third of the observed episodes necessitated therapeutic intervention. Adequately powered randomized studies are needed to confirm our findings, provide an accurate estimation of the consequences of acetaminophen-induced hypotension, and assess the pathophysiologic mechanisms involved.

The interpretation of lung auscultation is highly subjective and relies on non-specific nomenclature. Computer-aided analysis has the potential to better standardize and automate evaluation. We used 35.9 hours of auscultation audio from 572 pediatric outpatients to developDeepBreath: a deep learning model identifying the audible signatures of acute respiratory illness in children. It comprises a convolutional neural network followed by a logistic regression classifier, aggregating estimates on recordings from eight thoracic sites into a single prediction at the patient-level. Patients were either healthy controls (29%) or had one of three acute respiratory illnesses (71%) including pneumonia, wheezing disorders (bronchitis/asthma), and bronchiolitis). To ensure objective estimates on model generalisability,DeepBreathis trained on patients from two countries (Switzerland, Brazil), and results are reported on an internal 5-fold cross-validation as well as externally validated (extval) on three other countries (Senegal, Cameroon, Morocco).DeepBreathdifferentiated healthy and pathological breathing with an Area Under the Receiver-Operator Characteristic (AUROC) of 0.93 (standard deviation [SD] ± 0.01 on internal validation). Similarly promising results were obtained for pneumonia (AUROC 0.75 ± 0.10), wheezing disorders (AUROC 0.91 ± 0.03), and bronchiolitis (AUROC 0.94 ± 0.02). Extval AUROCs were 0.89, 0.74, 0.74 and 0.87 respectively. All either matched or were significant improvements on a clinical baseline model using age and respiratory rate. Temporal attention showed clear alignment between model prediction and independently annotated respiratory cycles, providing evidence thatDeepBreathextracts physiologically meaningful representations.DeepBreathprovides a framework for interpretable deep learning to identify the objective audio signatures of respiratory pathology.

Background: Evidence-based best practices are the cornerstone to guide optimal cardiopulmonary arrest resuscitation care. Adherence to the American Heart Association (AHA) guidelines for cardiopulmonary resuscitation (CPR) optimizes the management of critically ill patients and increases their chances of survival after cardiac arrest. Despite advances in resuscitation science and survival improvement over the last decades, only approximately 38% of children survive to hospital discharge after in-hospital cardiac arrest and only 6%-20% after out-of-hospital cardiac arrest. Objective: We investigated whether a mobile app developed as a guide to support and drive CPR providers in real time through interactive pediatric advanced life support (PALS) algorithms would increase adherence to AHA guidelines and reduce the time to initiation of critical life-saving maneuvers compared to the use of PALS pocket reference cards. Methods: This study was a randomized controlled trial conducted during a simulation-based pediatric cardiac arrest scenario caused by pulseless ventricular tachycardia (pVT). A total of 26 pediatric residents were randomized into two groups. The primary outcome was the elapsed time in seconds in each allocation group from the onset of pVT to the first defibrillation attempt. Secondary outcomes were time elapsed to (1) initiation of chest compression, (2) subsequent defibrillation attempts, and (3) administration of drugs, including the time intervals between defibrillation attempts and drug doses, shock doses, and the number of shocks. All outcomes were assessed for deviation from AHA guidelines. Results: Mean time to the first defibrillation attempt (121.4 sec, 95% CI 105.3-137.5) was significantly reduced among residents using the app compared to those using PALS pocket cards (211.5 sec, 95% CI 162.5-260.6, P<.001). With the app, 11 out of 13 (85%) residents initiated chest compressions within 60 seconds from the onset of pVT and 12 out of 13 (92%) successfully defibrillated within 180 seconds. Time to all other defibrillation attempts was reduced with the app. Adherence to the 2018 AHA pVT algorithm improved by approximately 70% (P=.001) when using the app following all CPR sequences of action in a stepwise fashion until return of spontaneous circulation. The pVT rhythm was recognized correctly in 51 out of 52 (98%) opportunities among residents using the app compared to only 19 out of 52 (37%) among those using PALS cards (P<.001). Time to epinephrine injection was similar. Among a total of 78 opportunities, incorrect shock or drug doses occurred in 14% (11/78) of cases among those using the cards. These errors were reduced to 1% (1/78, P=.005) when using the app. Conclusions: Use of the mobile app was associated with a shorter time to first and subsequent defibrillation attempts, fewer medication and defibrillation dose errors, and improved adherence to AHA recommendations compared with the use of PALS pocket cards.

Mobile phones (MPs) of healthcare workers (HCWs) may represent an important source of transmission of infectious agents. This longitudinal study documents the contamination of these tools. Ten MPs handled by senior pediatricians were sampled once a week during 23 weeks in three pediatric wards of the University Hospital of Saint-Etienne, France. Cultures were performed for bacteria and multiplex PCR assays for a panel of respiratory and enteric viruses. A questionnaire on hygiene habits regarding phoning and care was filled-in by pediatricians before and after the study. From a total of 230 samples, 145 (63%) were contaminated by at least one pathogen. The MPs from emergency departments were the most impacted. Viruses were detected in 179 samples; bacteria were isolated in 59 samples. Contamination increased during the winter epidemic peak. A cross-contamination by Paracoccus yeei between hands and MPs of different HCWs was demonstrated. The communication of the study results influenced the hygiene behaviors. This study highlights the contamination of MPs by pathogens that are resistant in the environment, and its sustainability along the winter season. The role of MPs as vectors of nosocomial infection needs to be better investigated.