Variation in Definition of Prolonged Mechanical Ventilation

Rose, Louise; McGinlay, Michael; Amin, Reshma; Burns, Karen E. A.; Connolly, Bronwen; Hart, Nicholas; Jouvet, Philippe; Katz, Sherri; Leasa, David; Mawdsley, Cathy; McAuley, Daniel F.; Schultz, Marcus J.; Blackwood, Bronagh

doi:10.4187/respcare.05485

Cited by 66 publications

(72 citation statements)

References 33 publications

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“…There is great variability in terminology and definitions [ 17 ]: National Association for Medical Direction of Respiratory Care (NAMDRC) [ 18 ]: “the need for more than 21 consecutive days of MV for more than 6 h/day”. European Respiratory Society (ERS) Task Force [ 19 ]: “the need of more than 7 days of weaning after the first spontaneous breathing trial (SBT)”.…”

Section: Main Textmentioning

confidence: 99%

The patient needing prolonged mechanical ventilation: a narrative review

Ambrosino

Vitacca

2018

Multidiscip Respir Med

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BackgroundProgress in management has improved hospital mortality of patients admitted to the intensive care units, but also the prevalence of those patients needing weaning from prolonged mechanical ventilation, and of ventilator assisted individuals. The result is a number of difficult clinical and organizational problems for patients, caregivers and health services, as well as high human and financial resources consumption, despite poor long-term outcomes. An effort should be made to improve the management of these patients. This narrative review summarizes the main concepts in this field.Main bodyThere is great variability in terminology and definitions of prolonged mechanical ventilation.There have been several recent developments in the field of prolonged weaning: ventilatory strategies, use of protocols, early mobilisation and physiotherapy, specialised weaning units.There are few published data on discharge home rates, need of home mechanical ventilation, or long-term survival of these patients.Whether artificial nutritional support improves the outcome for these chronic critically ill patients, is unclear and controversial how these data are reported on the optimal time of initiation of parenteral vs enteral nutrition.There is no consensus on time of tracheostomy or decannulation. Despite several individualized, non-comparative and non-validated decannulation protocols exist, universally accepted protocols are lacking as well as randomised controlled trials on this critical issue. End of life decisions should result from appropriate communication among professionals, patients and surrogates and national legislations should give clear indications.ConclusionPresent medical training of clinicians and locations like traditional intensive care units do not appear enough to face the dramatic problems posed by these patients. The solutions cannot be reserved to professionals but must involve also families and all other stakeholders. Large multicentric, multinational studies on several aspects of management are needed.

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Section: Main Textmentioning

confidence: 99%

The patient needing prolonged mechanical ventilation: a narrative review

Ambrosino

Vitacca

2018

Multidiscip Respir Med

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“…Race was not included as a potential effect modifier or confounder because ICU literature reports no association between race and delirium [27,28]. Logistic regression analysis was used to assess the relationship of prolonged length of ICU stay (�7 days), receipt of invasive mechanical ventilation (ever/never), invasive mechanical ventilation �96 hours [29,30] and ICU mortality with delirium severity. Box plots were used to show median and quartiles of length of ICU stay and length of mechanical ventilation with respect to CAM-ICU-7 and ICDSC score categories.…”

Section: Plos Onementioning

confidence: 99%

The CAM-ICU-7 and ICDSC as measures of delirium severity in critically ill adult patients

et al. 2020

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Background In clinical practice, a dichotomous approach to delirium identification may no longer be relevant when existing delirium screening tools measure a range of scores. The objective of this study was to compare the Confusion Assessment Method for the Intensive Care Unit 7-item (CAM-ICU-7) and the Intensive Care Delirium Screening Checklist (ICDSC) as measures of the spectrum of delirium severity in critically ill adult patients. Methods In this cross-sectional study, 218 patients underwent 641 paired assessments by bedside nurses (ICDSC, as per usual care) and trained research assistants (CAM-ICU-7). Correlation between the CAM-ICU-7 and ICDSC scores was evaluated. Logistic regression was used to explore associations between CAM-ICU-7 or ICDSC score and length of ICU stay and mechanical ventilation (receipt, ≥96 hours). Results Delirium prevalence evaluated by the CAM-ICU-7 and ICDSC were 46.3% (95% CI:39.7–53.0) and 34.4% (95% CI:28.3–41.0). Prevalence of less than clinical threshold symptoms of delirium evaluated by the CAM-ICU-7 (score: 1–2) and ICDSC (score: 1–3) were 30.3% (95%CI:24.5–36.7) and 50.9% (95%CI:44.3–57.6). The CAM-ICU-7 and ICDSC had significant positive correlation (0.58, p<0.001). Agreement between the tools as measures of delirium was moderate (kappa = 0.51) and as measures of less than clinical threshold symptoms of delirium was fair (kappa = 0.21). Less than clinical threshold symptoms of delirium identified by the ICDSC, not CAM-ICU-7, were associated with prolonged length of ICU stay (≥7 days) in patients <65 years of age [Odds Ratio (OR) 9.2, 95% CI:2.5–34.0] and mechanical ventilation (receipt: OR 2.8, 95% CI:1.3–6.4; ≥96 hours: OR 6.6, 95% CI:1.9–22.9), when compared to patients with no delirium. Conclusions The CAM-ICU-7 and ICDSC are measures of the spectrum of delirium severity that are closely correlated. Less than clinical threshold symptoms of delirium measure by the ICDSC is a better predictor of outcomes, when compared with the CAM-ICU-7.

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“…Furthermore, there is no consensus on the definition of PMV. The PMV period in the published literature ranges from 5 hours to 1 year with > 21 days being the most common definition for PMV [15]. Table 1 shows examples of the previously published literature in predicting PMV highlighting the patients' characteristics, PMV duration, used predictors and the predictive models' performance measures.…”

Section: Introductionmentioning

confidence: 99%

Using trauma registry data to predict prolonged mechanical ventilation in patients with traumatic brain injury: Machine learning approach

et al. 2020

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We aimed to build a machine learning predictive model to predict the risk of prolonged mechanical ventilation (PMV) for patients with Traumatic Brain Injury (TBI). Methods This study included TBI patients who were hospitalized in a level 1 trauma center between January 2014 and February 2019. Data were analyzed for all adult patients who received mechanical ventilation following TBI with abbreviated injury severity (AIS) score for the head region of � 3. This study designed three sets of machine learning models: set A defined PMV to be greater than 7 days, set B (PMV > 10 days) and set C (PMV >14 days) to determine the optimal model for deployment. Patients' demographics, injury characteristics and CT findings were used as predictors. Logistic regression (LR), Artificial neural networks (ANN) Support vector machines (SVM), Random Forest (RF) and C.5 Decision Tree (C.5 DT) were used to predict the PMV. Results The number of eligible patients that were included in the study were 674, 643 and 622 patients in sets A, B and C respectively. In set A, LR achieved the optimal performance with accuracy 0.75 and Area under the curve (AUC) 0.83. SVM achieved the optimal performance among other models in sets B with accuracy/AUC of 0.79/0.84 respectively. ANNs achieved the optimal performance in set C with accuracy/AUC of 0.76/0.72 respectively. Machine learning models in set B demonstrated more stable performance with higher prediction success and discrimination power.

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Variation in Definition of Prolonged Mechanical Ventilation

Cited by 66 publications

References 33 publications

The patient needing prolonged mechanical ventilation: a narrative review

The patient needing prolonged mechanical ventilation: a narrative review

The CAM-ICU-7 and ICDSC as measures of delirium severity in critically ill adult patients

Using trauma registry data to predict prolonged mechanical ventilation in patients with traumatic brain injury: Machine learning approach

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