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1.
Trials ; 23(1): 105, 2022 Feb 02.
Article in English | MEDLINE | ID: covidwho-2098423

ABSTRACT

BACKGROUND: Noninvasive respiratory support is frequently needed for patients with acute hypoxemic respiratory failure due to coronavirus disease 19 (COVID-19). Helmet noninvasive ventilation has multiple advantages over other oxygen support modalities but data about effectiveness are limited. METHODS: In this multicenter randomized trial of helmet noninvasive ventilation for COVID-19 patients, 320 adult ICU patients (aged ≥14 years or as per local standards) with suspected or confirmed COVID-19 and acute hypoxemic respiratory failure (ratio of arterial oxygen partial pressure to fraction of inspired oxygen < 200 despite supplemental oxygen with a partial/non-rebreathing mask at a flow rate of 10 L/min or higher) will be randomized to helmet noninvasive ventilation with usual care or usual care alone, which may include mask noninvasive ventilation, high-flow nasal oxygen, or standard oxygen therapy. The primary outcome is death from any cause within 28 days after randomization. The trial has 80% power to detect a 15% absolute risk reduction in 28-day mortality from 40 to 25%. The primary outcome will be compared between the helmet and usual care group in the intention-to-treat using the chi-square test. Results will be reported as relative risk  and 95% confidence interval. The first patient was enrolled on February 8, 2021. As of August 1, 2021, 252 patients have been enrolled from 7 centers in Saudi Arabia and Kuwait. DISCUSSION: We developed a detailed statistical analysis plan to guide the analysis of the Helmet-COVID trial, which is expected to conclude enrollment in November 2021. TRIAL REGISTRATION: ClinicalTrials.gov NCT04477668 . Registered on July 20, 2020.


Subject(s)
COVID-19 , Noninvasive Ventilation , Respiratory Insufficiency , Adult , Head Protective Devices , Humans , Noninvasive Ventilation/adverse effects , Respiratory Insufficiency/diagnosis , Respiratory Insufficiency/therapy , SARS-CoV-2
2.
JAMA ; 328(11): 1063-1072, 2022 09 20.
Article in English | MEDLINE | ID: covidwho-2047353

ABSTRACT

Importance: Helmet noninvasive ventilation has been used in patients with COVID-19 with the premise that helmet interface is more effective than mask interface in delivering prolonged treatments with high positive airway pressure, but data about its effectiveness are limited. Objective: To evaluate whether helmet noninvasive ventilation compared with usual respiratory support reduces mortality in patients with acute hypoxemic respiratory failure due to COVID-19 pneumonia. Design, Setting, and Participants: This was a multicenter, pragmatic, randomized clinical trial that was conducted in 8 sites in Saudi Arabia and Kuwait between February 8, 2021, and November 16, 2021. Adult patients with acute hypoxemic respiratory failure (n = 320) due to suspected or confirmed COVID-19 were included. The final follow-up date for the primary outcome was December 14, 2021. Interventions: Patients were randomized to receive helmet noninvasive ventilation (n = 159) or usual respiratory support (n = 161), which included mask noninvasive ventilation, high-flow nasal oxygen, and standard oxygen. Main Outcomes and Measures: The primary outcome was 28-day all-cause mortality. There were 12 prespecified secondary outcomes, including endotracheal intubation, barotrauma, skin pressure injury, and serious adverse events. Results: Among 322 patients who were randomized, 320 were included in the primary analysis, all of whom completed the trial. Median age was 58 years, and 187 were men (58.4%). Within 28 days, 43 of 159 patients (27.0%) died in the helmet noninvasive ventilation group compared with 42 of 161 (26.1%) in the usual respiratory support group (risk difference, 1.0% [95% CI, -8.7% to 10.6%]; relative risk, 1.04 [95% CI, 0.72-1.49]; P = .85). Within 28 days, 75 of 159 patients (47.2%) required endotracheal intubation in the helmet noninvasive ventilation group compared with 81 of 161 (50.3%) in the usual respiratory support group (risk difference, -3.1% [95% CI, -14.1% to 7.8%]; relative risk, 0.94 [95% CI, 0.75-1.17]). There were no significant differences between the 2 groups in any of the prespecified secondary end points. Barotrauma occurred in 30 of 159 patients (18.9%) in the helmet noninvasive ventilation group and 25 of 161 (15.5%) in the usual respiratory support group. Skin pressure injury occurred in 5 of 159 patients (3.1%) in the helmet noninvasive ventilation group and 10 of 161 (6.2%) in the usual respiratory support group. There were 2 serious adverse events in the helmet noninvasive ventilation group and 1 in the usual respiratory support group. Conclusions and Relevance: Results of this study suggest that helmet noninvasive ventilation did not significantly reduce 28-day mortality compared with usual respiratory support among patients with acute hypoxemic respiratory failure due to COVID-19 pneumonia. However, interpretation of the findings is limited by imprecision in the effect estimate, which does not exclude potentially clinically important benefit or harm. Trial Registration: ClinicalTrials.gov Identifier: NCT04477668.


Subject(s)
COVID-19 , Noninvasive Ventilation , Oxygen Inhalation Therapy , Respiratory Insufficiency , Acute Disease , Barotrauma/etiology , COVID-19/complications , COVID-19/mortality , COVID-19/therapy , Female , Humans , Hypoxia/etiology , Hypoxia/mortality , Hypoxia/therapy , Male , Middle Aged , Noninvasive Ventilation/adverse effects , Noninvasive Ventilation/methods , Oxygen/administration & dosage , Oxygen/adverse effects , Oxygen Inhalation Therapy/adverse effects , Oxygen Inhalation Therapy/methods , Respiratory Insufficiency/etiology , Respiratory Insufficiency/mortality , Respiratory Insufficiency/therapy
3.
J Infect Public Health ; 15(7): 826-834, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1895224

ABSTRACT

BACKGROUND: Coronavirus disease-19 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is currently a major cause of intensive care unit (ICU) admissions globally. The role of machine learning in the ICU is evolving but currently limited to diagnostic and prognostic values. A decision tree (DT) algorithm is a simple and intuitive machine learning method that provides sequential nonlinear analysis of variables. It is simple and might be a valuable tool for bedside physicians during COVID-19 to predict ICU outcomes and help in critical decision-making like end-of-life decisions and bed allocation in the event of limited ICU bed capacities. Herein, we utilized a machine learning DT algorithm to describe the association of a predefined set of variables and 28-day ICU outcome in adult COVID-19 patients admitted to the ICU. We highlight the value of utilizing a machine learning DT algorithm in the ICU at the time of a COVID-19 pandemic. METHODS: This was a prospective and multicenter cohort study involving 14 hospitals in Saudi Arabia. We included critically ill COVID-19 patients admitted to the ICU between March 1, 2020, and October 31, 2020. The predictors of 28-day ICU mortality were identified using two predictive models: conventional logistic regression and DT analyses. RESULTS: There were 1468 critically ill COVID-19 patients included in the study. The 28-day ICU mortality was 540 (36.8 %), and the 90-day mortality was 600 (40.9 %). The DT algorithm identified five variables that were integrated into the algorithm to predict 28-day ICU outcomes: need for intubation, need for vasopressors, age, gender, and PaO2/FiO2 ratio. CONCLUSION: DT is a simple tool that might be utilized in the ICU to identify critically ill COVID-19 patients who are at high risk of 28-day ICU mortality. However, further studies and external validation are still required.


Subject(s)
COVID-19 , Adult , Algorithms , Cohort Studies , Critical Illness , Decision Trees , Humans , Intensive Care Units , Machine Learning , Pandemics , Prospective Studies , Retrospective Studies , SARS-CoV-2
4.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-292258

ABSTRACT

Background: The Coronavirus Disease-19 (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a major cause of intensive care unit (ICU) admissions globally. Robust data of epidemiology, characteristics, and disease outcomes from different regions and populations showed considerable variations. However, limited number of reports addressed predictors of mortality utilizing machine learning methods. Herein, we aimed to describe the association and relationship of a predefined set of variables found to be predictive of 28–day ICU outcome among adults COVID-19 patients admitted to the ICU using a machine learning decision tree (DT) algorithm. Methods: This was a prospective/retrospective, multicenter cohort study from 14 hospitals in Saudi Arabia. We included critically ill COVID-19 patients admitted to the ICU between March 1, 2020, and October 31, 2020. The primary outcome was 28-day ICU mortality . Secondary outcomes were 90-day mortality and ICU length of stay. The predictors of mortality were identified using two predictive models, the conventional logistic regression and DT analysis. Results: : A total of 1468 critically ill COVID-19 patients were included. The mean age was 55.9 (SD±15.1) years, with 74% of the patients were males. The 28-day ICU mortality was 540 (36.8%), while 90-day mortality was 600 (40.9%). The multivariable logistic regression model demonstrated that the PaO 2 /FiO 2 ratio on ICU admission and the need for intubation or vasopressors could strongly predict 28-day ICU mortality. The DT algorithm identified five variables [need for intubation, need for vasopressors, age, gender, and PaO 2 /FiO 2 ratio] provided in an algorithmic fashion to predict 28-day ICU outcome. Conclusion: Five clinical predictors of 28-day ICU outcome were identified using DT algorithmic analysis of COVID-19 patients admitted to ICU. The findings of this DT analysis may be used in ICU for early identification of critically ill COVID-19 patients who are at high risk of 28-day mortality.

5.
BMJ Open ; 11(8): e052169, 2021 08 26.
Article in English | MEDLINE | ID: covidwho-1376510

ABSTRACT

INTRODUCTION: Non-invasive ventilation (NIV) delivered by helmet has been used for respiratory support of patients with acute hypoxaemic respiratory failure due to COVID-19 pneumonia. The aim of this study was to compare helmet NIV with usual care versus usual care alone to reduce mortality. METHODS AND ANALYSIS: This is a multicentre, pragmatic, parallel randomised controlled trial that compares helmet NIV with usual care to usual care alone in a 1:1 ratio. A total of 320 patients will be enrolled in this study. The primary outcome is 28-day all-cause mortality. The primary outcome will be compared between the two study groups in the intention-to-treat and per-protocol cohorts. An interim analysis will be conducted for both safety and effectiveness. ETHICS AND DISSEMINATION: Approvals are obtained from the institutional review boards of each participating institution. Our findings will be published in peer-reviewed journals and presented at relevant conferences and meetings. TRIAL REGISTRATION NUMBER: NCT04477668.


Subject(s)
COVID-19 , Noninvasive Ventilation , Respiratory Insufficiency , Head Protective Devices , Humans , Multicenter Studies as Topic , Randomized Controlled Trials as Topic , Respiratory Insufficiency/therapy , SARS-CoV-2
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