PubMed Health⌕ Search

PubMed · 9785825

Weaning from artificial ventilation.

Abstract

Every intubated and mechanically-ventilated patient should be clinically evaluated, at least on a daily basis, by a skilled team in order to speed up the weaning process as much as possible. Again, it should be emphasized that the adoption of an active clinical strategy when faced with "difficult" to wean patients is of paramount importance. In one study, performed in Spain, analysing the prevalence of mechanical ventilation in intensive care units [3], reported the mean number of days that patients spent on mechanical ventilation was 27. In a more recent intervention study, in which a specific protocol was followed each day [2], the mean number of days on mechanical ventilation was only 12. These data have been confirmed by several authors [4, 40], and it has also been reported that a protocol-directed weaning strategy leads not only to a significant reduction in the duration of mechanical ventilation but also to a significant decrease in the number of complications and cost [4]. However, even following a protocol-directed weaning strategy, it is possible that weaning duration can be further reduced. In a prospective study performed in our institution [41] during 32 months, we reported that, following an episode of unplanned extubation, the only independent variables associated with the need for reintubation were the number of days of mechanical ventilation and the type of ventilatory support at the time of autoextubation. Indeed, when patients were in the weaning period only 16% (5 out of 32) needed reintubation, whereas reintubation was needed in 82% (22 out of 27) of patients who had an unplanned extubation during full mechanical ventilatory support. These data suggest that there are still some patients being on mechanical ventilation for a longer than necessary period of time. Finally, very recent advances in technological areas such as artificial intelligence, are proving to be useful in the management of the weaning process. When such systems are applied to modern microprocessor-controlled mechanical ventilators they can significantly help in the process of weaning [42] by automatically reducing the ventilatory assistance and by indicating the optimal time to withdraw the patient from the ventilator and proceed with extubation.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J Mancebo. 1998. Weaning from artificial ventilation.. https://pubmed.ncbi.nlm.nih.gov/9785825/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗