scholarly journals Acute Brain Dysfunction, Host Inflammation, and Gut Dysbiosis During Critical Illness: A Prospective Cohort Study in Mechanically Ventilated Adults

Author(s):  
C. Franz ◽  
G. Kitsios ◽  
S. Alexander ◽  
K. Fair ◽  
A.M. Morris ◽  
...  
2017 ◽  
Vol 42 ◽  
pp. 405-406
Author(s):  
Paola Tonin Carpeggiani ◽  
Júlia Bertholdo Bossardi ◽  
Fabricio Piccoli Fortuna ◽  
Vanessa Piccoli ◽  
Nicole Elen Lira ◽  
...  

2018 ◽  
Vol 6 (3) ◽  
pp. 213-222 ◽  
Author(s):  
Timothy D Girard ◽  
Jennifer L Thompson ◽  
Pratik P Pandharipande ◽  
Nathan E Brummel ◽  
James C Jackson ◽  
...  

2008 ◽  
Vol 126 (6) ◽  
pp. 319-322 ◽  
Author(s):  
Bruno Franco Mazza ◽  
José Luiz Gomes do Amaral ◽  
Heloisa Rosseti ◽  
Rosana Borges Carvalho ◽  
Ana Paula Resque Senna ◽  
...  

CONTEXT AND OBJECTIVE: Intrahospital transportation of mechanically ventilated patients is a high-risk situation. We aimed to determine whether transfers could be safely performed by using a transportation routine. DESIGN AND SETTING: Prospective cohort study with "before and after" evaluation. METHODS: Mechanically ventilated patients who needed transportation were included. Hemodynamic and respiratory parameters were measured before and after transportation. Statistical analysis consisted of variance analysis and paired Student's t test. Results were considered significant if P < 0.05. RESULTS: We studied 37 transfers of 26 patients (12 female) of mean age 46.6 ± 15.7. Patients with pulmonary diseases, positive end expiratory pressure > 5, FiO2 > 0.4 and vasoactive drug use comprised 42.4%, 24.3%, 21.6% and 33.0% of cases, respectively. Mean duration of transportation was 43.4 ± 18.9 minutes. Complications occurred in 32.4%. There was a significant increase in CO2 (before transportation, 29.6 ± 7.3 and after transportation, 34.9 ± 7.0; P = 0.000); a trend towards improved PO2/FiO2 ratio (before transportation, 318.0 ± 137.0 and after transportation, 356.8 ± 119.9; P = 0.053); increased heart rate (before transportation, 80.9 ± 18.7 and after transportation, 85.5 ± 17.6; P = 0.08); and no significant change in mean arterial blood pressure (P = 0.93). CONCLUSION: These results suggest that intrahospital transportation can be safely performed. Our low incidence of complications was possibly related to both the presence of a multidisciplinary transportation team and proper equipment.


Author(s):  
Christopher G. Hughes ◽  
Christina J. Hayhurst ◽  
Pratik P. Pandharipande ◽  
Matthew S. Shotwell ◽  
Xiaoke Feng ◽  
...  

Critical Care ◽  
2016 ◽  
Vol 20 (1) ◽  
Author(s):  
Jason E. Tomichek ◽  
Joanna L. Stollings ◽  
Pratik P. Pandharipande ◽  
Rameela Chandrasekhar ◽  
E. Wesley Ely ◽  
...  

2020 ◽  
Author(s):  
Li Zhao ◽  
Wen-Kui Xu ◽  
Ying Wang ◽  
Wei-Yan Lu ◽  
Yong Wu ◽  
...  

Abstract Background A vast number of patients with chronic critical illness (CCI) have died of delayed organ failure in the intensive care unit (ICU). The weak organ function of patients needed appropriate tool to evaluate, which could provide reference for clinical decisions and communication with family members. The objective of this study was to develope and validate a prediction model for accurate, timely, simple, and objective identification of the critical degree of the patients' condition. Methods This study used a retrospective case–control and a prospective cohort study, with no interventions. Patients identified as CCI from a comprehensive ICU of a large metropolitan public hospital were selected. A total of 344 (case 172; control 172) patients were included to develop the Prognosis Prediction Model of Chronic Critical Illness (PPCCI Model) in this case-control study; 88 (case, 44; control 44) patients were included for the validation cohort in a prospective cohort study. The discrimination of the model was assessed by the area under the curve (AUC) of the receiver operating characteristic (ROC). Results The model comprised 9 predictors: age, prolonged mechanical ventilation (PMV), sepsis/other serious infections, Glasgow Coma Scale (GCS), mean artery pressure (MAP), heart rate (HR), respiratory rate (RR), oxygenation index (OI), and active bleeding.In both cohorts, the PPCCI Model could better identify the dead CCI patients (development cohort: AUC, 0.934; 95% CI, 0.908–0.960; validation cohort: AUC, 0.965; 95% CI, 0.931–0.999), and showed better discrimination than the Acute Physiology And Chronic Health Evaluation II (APACHE II), Modified Early Warning Score (MEWS), and Sequential Organ Failure Assessment (SOFA). Conclusions The PPCCI Model can provide a standardized measurement tool for ICU medical staff to evaluate the condition of CCI patients, to facilitate rational allocation of ward-monitoring resources or communicate with family members.


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