Failure of Empirical Systemic Antifungal Therapy in Mechanically Ventilated Critically Ill Patients

2015 ◽  
Vol 191 (10) ◽  
pp. 1139-1146 ◽  
Author(s):  
Sébastien Bailly ◽  
Lila Bouadma ◽  
Elie Azoulay ◽  
Maité Garrouste Orgeas ◽  
Christophe Adrie ◽  
...  
Keyword(s):  
Critically Ill ◽  
Antifungal Therapy ◽  
Critically Ill Patients ◽  
Mechanically Ventilated ◽  
Systemic Antifungal Therapy

Systemic antifungal therapy in critically ill patients without invasive fungal infection*

2012 ◽  
Vol 40 (3) ◽  
pp. 813-822 ◽  
Author(s):  
Elie Azoulay ◽  
Hervé Dupont ◽  
Alexis Tabah ◽  
Olivier Lortholary ◽  
Jean-Paul Stahl ◽  
...  
Keyword(s):  
Fungal Infection ◽  
Critically Ill ◽  
Antifungal Therapy ◽  
Invasive Fungal Infection ◽  
Critically Ill Patients ◽  
Systemic Antifungal Therapy

Candidemia in non-neutropenic critically ill patients: analysis of prognostic factors and assessment of systemic antifungal therapy

1997 ◽  
Vol 23 (1) ◽  
pp. 23-30 ◽  
Author(s):  
J. Nolla-Salas ◽  
A. Sitges-Serra ◽  
C. León-Gil ◽  
J. Martínez-González ◽  
M. A. León-Regidor ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Critically Ill ◽  
Antifungal Therapy ◽  
Critically Ill Patients ◽  
Systemic Antifungal Therapy

Outcomes associated with routine systemic antifungal therapy in critically ill patients with Candida colonization

2015 ◽  
Vol 41 (6) ◽  
pp. 1077-1088 ◽  
Author(s):  
David Ferreira ◽  
Frederic Grenouillet ◽  
Gilles Blasco ◽  
Emmanuel Samain ◽  
Thierry Hénon ◽  
...  
Keyword(s):  
Critically Ill ◽  
Antifungal Therapy ◽  
Critically Ill Patients ◽  
Candida Colonization ◽  
Systemic Antifungal Therapy

scholarly journals Etiology, incidence, and outcomes of patient–ventilator asynchrony in critically-ill patients undergoing invasive mechanical ventilation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yongfang Zhou ◽  
Steven R. Holets ◽  
Man Li ◽  
Gustavo A. Cortes-Puentes ◽  
Todd J. Meyer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mechanical Ventilation ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Invasive Mechanical Ventilation ◽  
Surgical Intensive Care ◽  
Mechanically Ventilated ◽  
History Of ◽  
Training Background ◽  
The Relationship

AbstractPatient–ventilator asynchrony (PVA) is commonly encountered during mechanical ventilation of critically ill patients. Estimates of PVA incidence vary widely. Type, risk factors, and consequences of PVA remain unclear. We aimed to measure the incidence and identify types of PVA, characterize risk factors for development, and explore the relationship between PVA and outcome among critically ill, mechanically ventilated adult patients admitted to medical, surgical, and medical-surgical intensive care units in a large academic institution staffed with varying provider training background. A single center, retrospective cohort study of all adult critically ill patients undergoing invasive mechanical ventilation for ≥ 12 h. A total of 676 patients who underwent 696 episodes of mechanical ventilation were included. Overall PVA occurred in 170 (24%) episodes. Double triggering 92(13%) was most common, followed by flow starvation 73(10%). A history of smoking, and pneumonia, sepsis, or ARDS were risk factors for overall PVA and double triggering (all P < 0.05). Compared with volume targeted ventilation, pressure targeted ventilation decreased the occurrence of events (all P < 0.01). During volume controlled synchronized intermittent mandatory ventilation and pressure targeted ventilation, ventilator settings were associated with the incidence of overall PVA. The number of overall PVA, as well as double triggering and flow starvation specifically, were associated with worse outcomes and fewer hospital-free days (all P < 0.01). Double triggering and flow starvation are the most common PVA among critically ill, mechanically ventilated patients. Overall incidence as well as double triggering and flow starvation PVA specifically, portend worse outcome.

scholarly journals Selection strategy for sedation depth in critically ill patients on mechanical ventilation

2021 ◽  
Vol 21 (S2) ◽  
Author(s):  
Longxiang Su ◽  
Chun Liu ◽  
Fengxiang Chang ◽  
Bo Tang ◽  
Lin Han ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Dimensionality Reduction ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Mechanically Ventilated ◽  
Mechanically Ventilated Patients ◽  
Sedation And Analgesia ◽  
Ventilated Patients

Abstract Background Analgesia and sedation therapy are commonly used for critically ill patients, especially mechanically ventilated patients. From the initial nonsedation programs to deep sedation and then to on-demand sedation, the understanding of sedation therapy continues to deepen. However, according to different patient’s condition, understanding the individual patient’s depth of sedation needs remains unclear. Methods The public open source critical illness database Medical Information Mart for Intensive Care III was used in this study. Latent profile analysis was used as a clustering method to classify mechanically ventilated patients based on 36 variables. Principal component analysis dimensionality reduction was used to select the most influential variables. The ROC curve was used to evaluate the classification accuracy of the model. Results Based on 36 characteristic variables, we divided patients undergoing mechanical ventilation and sedation and analgesia into two categories with different mortality rates, then further reduced the dimensionality of the data and obtained the 9 variables that had the greatest impact on classification, most of which were ventilator parameters. According to the Richmond-ASS scores, the two phenotypes of patients had different degrees of sedation and analgesia, and the corresponding ventilator parameters were also significantly different. We divided the validation cohort into three different levels of sedation, revealing that patients with high ventilator conditions needed a deeper level of sedation, while patients with low ventilator conditions required reduction in the depth of sedation as soon as possible to promote recovery and avoid reinjury. Conclusion Through latent profile analysis and dimensionality reduction, we divided patients treated with mechanical ventilation and sedation and analgesia into two categories with different mortalities and obtained 9 variables that had the greatest impact on classification, which revealed that the depth of sedation was limited by the condition of the respiratory system.

Retrospective Evaluation of Commonly Used Equations to Predict Energy Expenditure in Mechanically Ventilated, Critically Ill Patients

2004 ◽  
Vol 24 (12) ◽  
pp. 1659-1667 ◽  
Author(s):  
Earnest Alexander ◽  
Gregory M. Susla ◽  
Aaron H. Burstein ◽  
Dennis T. Brown ◽  
Frederick P. Ognibene
Keyword(s):  
Energy Expenditure ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Retrospective Evaluation ◽  
Mechanically Ventilated
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