Prone Positioning for Acute Hypoxemic Respiratory Failure and ARDS

Rampon, Garrett; Simpson, Steven Q.; Agrawal, Ritwick

doi:10.1016/j.chest.2022.09.020

Cited by 20 publications

(10 citation statements)

References 50 publications

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“…The median age of the patients was 64 [55-73] years and 67.6% of them were male. The APACHE II and SOFA scores on ICU admission were 14 [11][12][13][14][15][16] and 3 [3][4], respectively. Patients were admitted to the hospital within 5 [2][3][4][5][6][7] days and to the ICU within 10 [7-12] days after the onset of symptoms.…”

Section: Resultsmentioning

confidence: 99%

“…The APACHE II and SOFA scores on ICU admission were 14 [11][12][13][14][15][16] and 3 [3][4], respectively. Patients were admitted to the hospital within 5 [2][3][4][5][6][7] days and to the ICU within 10 [7-12] days after the onset of symptoms. Estimated PaO 2 from SpO 2 was used at 38 patients before PP, 48 patients during PP and 58 patients after PP.…”

Section: Resultsmentioning

confidence: 99%

“…2,3 Prone positioning has been shown to improve oxygenation and respiratory mechanics by promoting lung homogeneity and to reduce lung injury and mortality in the intubated patients with moderate to severe ARDS. 4,5 Notably, after the COVID-19 pandemic, interest has been raised for awake PP to reduce the need for IMV. [6][7][8][9] The utilization of PP in spontaneously breathing, non-intubated patients treated with oxygen therapy or non-invasive ventilation (NIV) have been reported to improve oxygenation and to decrease respiratory effort.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Awake Prone Positioning on ROX Index in Critically-ill Patients With Respiratory Failure due to COVID-19

Ortac Ersoy,

Erdemir,

Halacli

et al. 2023

J Intensive Care Med

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COVID-19 pneumonia causes acute respiratory distress syndrome (ARDS). Prone positioning (PP) is beneficial to pulmonary physiology and improves oxygenation in patients with ARDS. We aimed to investigate the effect of the PP on oxygenation, respiratory rate (RR) and ROX index in non-intubated patients with COVID-19 associated respiratory failure and to determine whether ROX index predicts intubation. Awake critically-ill patients with confirmed diagnosis of COVID-19 who underwent PP were enrolled in the retrospective, single-center study. Oxygenation parameters were recorded 1 h before PP, during PP and 1 h after return to supine position (after PP). Intubation was defined as the endpoint. Seventy-one patients with a median age of 64 [55-73] years were enrolled in the study. PaO2/FiO2 and SpO2/FiO2 improved during PP, this improvement did not persist after PP. RR improved during and after PP in both intubated and non-intubated patients (for all P < .001). ROX index improved only in non-intubated patients ( P < .001) but not in intubated patients ( P = .07). Area under the curve (AUC) of ROX index for intubation before PP, during PP and after PP were 0.74 [0.61-0.88] ( P = .002), 0.76 [0.62-0.91] ( P = .001), and 0.76 [0.64-0.89] ( P = .001), respectively. ROX index >6.83 before PP had a negative predictive value (NPV) of 0.85; ROX index >8.28 during PP had a NPV of 0.88 and ROX index >7.48 after PP had a NPV of 0.85. In logistic regression adjusted for APACHE II score, ROX index ≤6.83 before PP had an odds ratio (OR) 4.47 [1.39-14.38], ROX index ≤8.28 during PP had an OR 7.96 [2.29-27.64] and ROX index ≤7.48 had an OR 3.98 [1.25-12.61] for prediction of intubation. In conclusion, awake PP improves oxygenation and decreases RR. ROX index improved only in non- intubated patients and a higher ROX index predicts lower risk of progressing to mechanical ventilation with intubation.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effect of Awake Prone Positioning on ROX Index in Critically-ill Patients With Respiratory Failure due to COVID-19

Ortac Ersoy,

Erdemir,

Halacli

et al. 2023

J Intensive Care Med

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“…uid restriction[18], and prone ventilation [19,20], consequently leading to increased mortality [21]. Despite ongoing research, there remains a lack of a widely accepted predictive model to identify individuals at risk of ARDS.…”

Section: Discussionmentioning

confidence: 99%

Establishment and Validation of Predictive Model of ARDS in critically ill patients

wei,

Zhang,

et al. 2024

Preprint

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Background: Acute respiratory distress syndrome (ARDS) is a prevalent complication among critically ill patients, constituting around 10% of intensive care unit (ICU) admissions and mortality rates ranging from 35% to 46%. Hence, early recognition and prediction of ARDS are crucial for the timely administration of targeted treatment. However, ARDS is frequently underdiagnosed or delayed, and its heterogeneity diminishes the clinical utility of ARDS biomarkers. This study aimed to observe the incidence of ARDS among high-risk patients and develop and validate an ARDS prediction model using machine learning (ML) techniques based on clinical parameters. Methods: This prospective cohort study in China was conducted on critically ill patients to derivate and validate the prediction model. The derivation cohort, consisting of 400 patients admitted to the ICU of the Peking University Third Hospital(PUTH) between December 2020 and August 2023, was separated for training and internal validation, and an external data set of 160 patients at the FU YANG People's Hospital from August 2022 to August 2023 was employed for external validation. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to screen predictor variables. Multiple ML classification models were integrated to analyze and identify the best models. Several evaluation indexes were used to compare the predictive performance, including the area under the receiver-operating-characteristic curve (AUC) and decision curve analysis (DCA). S Hapley Additive ex Planations (SHAP) is used to interpret ML models. Results:400 critically ill patients were included in the analysis, with 117 developing ARDS during follow-up. The final model included gender, Lung Injury Prediction Score (LIPS), HepaticDisease, Shock, and combined Lung Contusion. Based on the AUC and DCA in the validation group, the logistic model demonstrated excellent performance, achieving an AUC of 0.836 (95% CI: 0.762-0.910). For external validation, comprising 160 patients, 44 of whom developed ARDS, the AUC was 0.799 (95% CI: 0.723-0.875). conclusion: Logistic regression models were constructed and interpreted using the SHAP method to provide a basis for screening high-risk groups for ARDS and to guide individualized treatment for different patients.

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“…The landmark 2013 Proning Severe ARDS Patients (PROSEVA) trial demonstrating improved 28-day mortality in patients with severe ARDS [3] , along with subsequent meta-analyses [4,5] also showing improved mortality in prone positioning, led to the American Thoracic Society/European Society of Intensive Care Medicine/Society of Critical Care Medicine clinical practice guidelines to strongly recommend prone positioning in severe ARDS [6,7] . Prone positioning improves mortality effectively by improving oxygenation and respiratory mechanics through a more homogenous distribution of ventilation and perfusion [7] .…”

Section: Introductionmentioning

confidence: 99%

Outcomes of Prone Positioning in Mechanically Ventilated COVID-19 patients: A Prospective Observational Study

Chandler

Jandali

Joyce

et al. 2023

Preprint

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Introduction Prone positioning in mechanically ventilated patients with severe acute respiratory distress syndrome (ARDS) is associated with improved mortality. More data is needed to fully understand its utility in those with ARDS due to COVID-19. Methods We conducted a single center prospective observational study inclusive of 100 consecutive patients intubated for ARDS from COVID-19 admitted to the ICU from September 2020 to December 2020. Data was collected daily from time of intubation for 7 days along with 30-day outcomes. Results The study included a total of 53 patients proned and 47 non-proned during their hospitalization. Proned patients were 61.8 years old, and 56.6% men compared to 66.3 years old and 57.4% male in the non-proned group. Other baseline characteristics and treatments were similar between both groups other than proned patients having a higher BMI than non-proned patients (34.1 ± 7.5 vs 30.5 ± 7.4, p = 0.02), and lower initial P/F ratios (119.1 ± 54.5 vs 154.0 ± 92.7, p = 0.047). Proned patients required more neuromuscular blockade (OR 6.63, 95% CI 3.25–13.12, p < 0.0001) and higher sedation levels (2 sedatives: OR = 3.00, 95% CI = 1.77,5.08; ≥3 sedatives: OR = 7.13, 95% CI = 3.96,12.81) with similar ICU length of stays, ventilator days, newly initiated renal replacement therapy, and 30-day outcomes when compared to non-proned patients. Proned patients were re-intubated substantially less than the non-proned group (1.9% vs 19.1%, p = 0.006). Conclusion Proning mechanically ventilated COVID-19 patients was associated with more frequent use of neuromuscular blockade and sedation, and required significantly lower rates of re-intubation for respiratory failure when compared to non-proned patients.

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Prone Positioning for Acute Hypoxemic Respiratory Failure and ARDS

Cited by 20 publications

References 50 publications

Effect of Awake Prone Positioning on ROX Index in Critically-ill Patients With Respiratory Failure due to COVID-19

Effect of Awake Prone Positioning on ROX Index in Critically-ill Patients With Respiratory Failure due to COVID-19

Establishment and Validation of Predictive Model of ARDS in critically ill patients

Outcomes of Prone Positioning in Mechanically Ventilated COVID-19 patients: A Prospective Observational Study

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