Introduction: Endotracheal intubation is an uncommon procedure for children in the emergency department but can be technically difficult and cause significant adverse effects. Videolaryngoscopy (VL) offers improved first-pass success rates over direct laryngoscopy (DL) for both adults and children undergoing elective surgery. This systematic review was designed to evaluate current evidence regarding how the effectiveness and safety of VL compares to DL for intubation of children in emergency departments.
Methods: Four databases (MEDLINE, Embase, CENTRAL and Web of Science) were searched on 11 May 2023 for studies comparing first-pass success of VL and DL for children undergoing intubation in the emergency department. Studies including adult patients or where intubation occurred outside of the emergency department were excluded. Quality assessment of included studies was carried out using the Risk Of Bias In Non-randomised Studies of Interventions (ROBINS-I) tool. Meta-analysis was undertaken for first-pass success and adverse event rate.
Results: Ten studies met the inclusion criteria representing 5,586 intubations. All included studies were observational. Significantly greater first-pass success rate was demonstrated with VL compared to DL (OR 1.64, 95% CI [1.21-2.21], = 0.001). There was no significant difference in risk of adverse events between VL and DL (OR 0.79, 95% CI [0.52-1.20], = 0.27). The overall risk of bias was moderate to serious for all included studies.
Conclusion: VL can offer improved first-pass success rates over DL for children intubated in the emergency department. However, the quality of current evidence is low and further randomised studies are required to clarify which patient groups may benefit most from use of VL.
Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=415039, Identifier CRD42023415039.
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http://dx.doi.org/10.3389/fmed.2024.1373460 | DOI Listing |
Int J Surg
January 2025
Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital, Linkou; Chang Gung University, Taoyuan, Taiwan.
Background: Detecting kidney trauma on CT scans can be challenging and is sometimes overlooked. While deep learning (DL) has shown promise in medical imaging, its application to kidney injuries remains underexplored. This study aims to develop and validate a DL algorithm for detecting kidney trauma, using institutional trauma data and the Radiological Society of North America (RSNA) dataset for external validation.
View Article and Find Full Text PDFJAMA
January 2025
Division of Hematology, Brigham and Women's Hospital, Boston, Massachusetts.
JAMA Intern Med
January 2025
Harvard Medical School, Boston, Massachusetts.
JAMA Intern Med
January 2025
Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Importance: There are no validated decision rules for terminating resuscitation during in-hospital cardiac arrest. Decision rules may guide termination and prevent inappropriate early termination of resuscitation.
Objective: To develop and validate termination of resuscitation rules for in-hospital cardiac arrest.
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