Obstetric difficult airway guidelines - decision-making in critical situations

Anesthesia decision analysis using a cloud-based big data platform

Big data technologies have proliferated since the dawn of the cloud-computing era. Traditional data storage, extraction, transformation, and analysis technologies have thus become unsuitable for the large volume, diversity, high processing speed, and low value density of big data in medical strategies, which require the development of novel big data application technologies. In this regard, we investigated the most recent big data platform breakthroughs in anesthesiology and designed an anesthesia decision model based on a cloud system for storing and analyzing massive amounts of data from anesthetic records. The presented Anesthesia Decision Analysis Platform performs distributed computing on medical records via several programming tools, and provides services such as keyword search, data filtering, and basic statistics to reduce inaccurate and subjective judgments by decision-makers. Importantly, it can potentially to improve anesthetic strategy and create individualized anesthesia decisions, lowering the likelihood of perioperative complications.

Difficult airway management algorithms: a directed review

The primary aim of this study was to identify, describe and compare the content of existing difficult airway management algorithms. Secondly, we aimed to describe the literature reporting the implementation of these algorithms. A directed search across three databases (MEDLINE, Embase and Scopus) was performed. All articles were screened for relevance to the research aims and according to pre-determined exclusion criteria. We identified 38 published airway management algorithms. Our results show that most facemask employ a four-step process as represented by a flow chart, with progression from tracheal intubation, facemask ventilation and supraglottic airway device use, to a rescue emergency surgical airway. The identified algorithms are overwhelmingly similar, yet many use differing terminology. The frequency of algorithm publication has increased recently, yet adherence and implementation outcome data remain limited. Our results highlight the lack of a single algorithm that is universally endorsed, recognised and applicable to all difficult airway management situations.