Lung Injury Prediction Score Is Useful in Predicting Acute Respiratory Distress Syndrome and Mortality in Surgical Critical Care Patients

Bauman, Zachary M.; Gassner, Marika; Coughlin, Megan A.; Mahan, Meredith; Watras, Jill

doi:10.1155/2015/157408

“…68 Interpretation of the LIPS score has also been shown to be highly dependent on the diagnosing clinician, and overall demonstrates suboptimal sensitivity and specificity. 30 In response to these limitations, alternative systems have been proposed to promote early ARDS recognition and improve patient outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…The most recent Berlin definition 28 of ARDS was developed in 2012 in response to issues regarding the reliability and validity of the 1994 American-European Consensus Conference (AECC) definition. 29 Although the Berlin definition has addressed many of the limitations of the AECC definition, [28][29][30] defining ARDS in diverse clinical settings remains dependent on some subjectivity of the diagnosing clinician. 31 It has been suggested that clinicians' ability to separate ARDS from other heterogeneous causes of respiratory failure is limited, 30,32,33 and that it can often be difficult to diagnose ARDS in patients who have underlying medical problems with similar symptoms.…”

Section: Introductionmentioning

confidence: 99%

“…29 Although the Berlin definition has addressed many of the limitations of the AECC definition, [28][29][30] defining ARDS in diverse clinical settings remains dependent on some subjectivity of the diagnosing clinician. 31 It has been suggested that clinicians' ability to separate ARDS from other heterogeneous causes of respiratory failure is limited, 30,32,33 and that it can often be difficult to diagnose ARDS in patients who have underlying medical problems with similar symptoms. 34 Because ARDS treatment options have limited efficacy, there is an interest in identifying patients most at risk of developing ARDS for early prevention strategies, such as antiplatelet therapy, 7,[35][36][37] as well as early clinical trial enrollment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Supervised Machine Learning for the Early Prediction of Acute Respiratory Distress Syndrome (ARDS)

Le

¹

,

Pellegrini

²

,

Green‐Saxena

³

et al. 2020

Preprint

View full text Add to dashboard Cite

Purpose: Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with high mortality and associated morbidity. The objective of this study is to develop and evaluate a novel application of gradient boosted tree models trained on patient health record data for the early prediction of ARDS.Materials and Methods: 9919 patient encounters were retrospectively analyzed from the Medical Information Mart for Intensive Care III (MIMIC-III) data base. XGBoost gradient boosted tree models for early ARDS prediction were created using routinely collected clinical variables and numerical representations of radiology reports as inputs. XGBoost models were iteratively trained and validated using 10-fold cross validation. Results:On a hold-out test set, algorithm classifiers attained area under the receiver operating characteristic curve (AUROC) values of 0.905, 0.827, 0.810, and 0.790 when tested for the prediction of ARDS at 0-, 12-, 24-, and 48-hour windows prior to onset, respectively. Conclusion: Supervised machine learning predictions may help predict patients with ARDS up to 48 hours prior to onset.

show abstract

“…Scores have been specifically developed to identify patients at risk of ARDS or severe PPCs [8], including the surgical lung injury prediction 2 model (SLIP-2) [20] and the lung injury prediction score 4 (LIPS) [21]. Other scores were generically developed for predicting all-types PPCs [8,10,[22][23][24].…”

Section: Patient and Surgical-related Risk Identificationmentioning

confidence: 99%

Perioperative anaesthetic management of patients with or at risk of acute distress respiratory syndrome undergoing emergency surgery

Battaglini

¹

,

Robba

²

,

Rocco

³

et al. 2019

Preprint

View full text Add to dashboard Cite

Patients undergoing emergency surgery may present with the acute respiratory distress syndrome (ARDS) or develop this syndrome postoperatively. The incidence of ARDS in the postoperative period is relatively low, but the impact of ARDS on patient outcomes and healthcare costs is relevant [1]. The development of ARDS as a postoperative pulmonary complication (PPC) is associated with prolonged hospitalisation, longer duration of mechanical ventilation, increased intensive care unit length of stay and high morbidity and mortality [2]. In order to mitigate the risk of ARDS after surgery, the anaesthetic management and protective mechanical ventilation strategies play an important role. In particular, a careful integration of general anaesthesia with neuraxial or locoregional techniques might promote faster recovery and reduce opioid consumption. In addition, the use of low tidal volume, minimising plateau pressure and titrating a low-moderate PEEP level based on the patient’s need can improve outcome and reduce intraoperative adverse events. Moreover, perioperative management of ARDS patients includes specific anaesthesia and ventilator settings, hemodynamic monitoring, moderately restrictive fluid administration and pain control. The aim of this review is to provide an overview and evidence- and opinion-based recommendations concerning the management of patients at risk of and with ARDS who undergo emergency surgical procedures.

show abstract

“…Scores have been specifically developed to identify patients at risk of ARDS or severe PPCs [8], including the surgical lung injury prediction 2 model (SLIP-2) [20] and the lung injury prediction score (LIPS) [21]. Other scores were generically developed for predicting all-types PPCs [8,10,[22][23][24].…”

Section: Patient and Surgical-related Risk Identificationmentioning

confidence: 99%

Perioperative anaesthetic management of patients with or at risk of acute distress respiratory syndrome undergoing emergency surgery

Battaglini

¹

,

Robba

²

,

Rocco

³

et al. 2019

Preprint

0

View full text Add to dashboard Cite

Patients undergoing emergency surgery may present with the acute respiratory distress syndrome (ARDS) or develop this syndrome postoperatively. The incidence of ARDS in the postoperative period is relatively low, but the impact of ARDS on patient outcomes and healthcare costs is relevant [1]. The development of ARDS as a postoperative pulmonary complication (PPC) is associated with prolonged hospitalisation, longer duration of mechanical ventilation, increased intensive care unit length of stay and high morbidity and mortality [2]. In order to mitigate the risk of ARDS after surgery, the anaesthetic management and protective mechanical ventilation strategies play an important role. In particular, a careful integration of general anaesthesia with neuraxial or locoregional techniques might promote faster recovery and reduce opioid consumption. In addition, the use of low tidal volume, minimising plateau pressure and titrating a low-moderate PEEP level based on the patient’s need can improve outcome and reduce intraoperative adverse events. Moreover, perioperative management of ARDS patients includes specific anaesthesia and ventilator settings, hemodynamic monitoring, moderately restrictive fluid administration and pain control. The aim of this review is to provide an overview and evidence- and opinion-based recommendations concerning the management of patients at risk of and with ARDS who undergo emergency surgical procedures.

show abstract

Lung Injury Prediction Score Is Useful in Predicting Acute Respiratory Distress Syndrome and Mortality in Surgical Critical Care Patients

Cited by 19 publications

References 44 publications

Supervised Machine Learning for the Early Prediction of Acute Respiratory Distress Syndrome (ARDS)

Supervised Machine Learning for the Early Prediction of Acute Respiratory Distress Syndrome (ARDS)

Perioperative anaesthetic management of patients with or at risk of acute distress respiratory syndrome undergoing emergency surgery

Perioperative anaesthetic management of patients with or at risk of acute distress respiratory syndrome undergoing emergency surgery

Contact Info

Product

Resources

About