Complications and Pharmacologic Interventions of Invasive Positive Pressure Ventilation During Critical Illness

Newsome, Andrea Sikora; Chastain, Daniel B; Watkins, Paige Marie; Hawkins, W. Anthony

doi:10.1177/8755122518766594

Cited by 3 publications

(3 citation statements)

References 256 publications

(245 reference statements)

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“…(44)(45)(46) Ventilator settings and medication therapy do not occur in silos but are highly intertwined: liberalizing ventilator settings can reduce the need for sedation (which is known to prolong mechanical ventilation and reduce extubation success). (2,47,48) As opposed to "settling in" for an intubation that is expected to last for an extended period, such a model may guard against clinical inertia towards more active interventions to get the patient successfully extubated (e.g., early mobility, avoidance of benzodiazepines). (49,50) Despite knowing the importance of light sedation and early mobility, translating this knowledge into action has remained a challenge, but quantitative risk prediction data indicating a short intubation period may guard against this inertia.…”

Section: Discussionmentioning

confidence: 99%

Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data

Sikora,

Zhao,

Kong

et al. 2023

Preprint

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Rationale: Duration of mechanical ventilation is associated with adverse outcomes in critically ill patients and increased use of resources. The increasing complexity of medication regimens has been associated with increased mortality, length of stay, and fluid overload but has never been studied specifically in the setting of mechanical ventilation. Objective: The purpose of this analysis was to develop prediction models for mechanical ventilation duration to test the hypothesis that incorporating medication data may improve model performance. Methods: This was a retrospective cohort study of adults admitted to the ICU and undergoing mechanical ventilation for longer than 24 hours from October 2015 to October 2020. Patients were excluded if it was not their index ICU admission or if the patient was placed on comfort care in the first 24 hours of admission. Relevant patient characteristics including age, sex, body mass index, admission diagnosis, morbidities, vital signs measurements, severity of illness, medication regimen complexity as measured by the MRC-ICU, and medical treatments before intubation were collected. The primary outcome was area under the receiver operating characteristic (AUROC) of prediction models for prolonged mechanical ventilation (defined as greater than 5 days). Both logistic regression and supervised learning techniques including XGBoost, Random Forest, and Support Vector Machine were used to develop prediction models. Results: The 318 patients [age 59.9 (SD 16.9), female 39.3%, medical 28.6%] had mean 24-hour MRC-ICU score of 21.3 (10.5), mean APACHE II score of 21.0 (5.4), mean SOFA score of 9.9 (3.3), and ICU mortality rate of 22.6% (n=72). The strongest performing logistic model was the base model with MRC-ICU added, with AUROC of 0.72, positive predictive value (PPV) of 0.83, and negative prediction value (NPV) of 0.92. The strongest overall model was Random Forest with an AUROC of 0.78, a PPV of 0.53, and NPV of 0.90. Feature importance analysis using support vector machine and Random Forest revealed severity of illness scores and medication related data were the most important predictors. Conclusions: Medication regimen complexity is significantly associated with prolonged duration of mechanical ventilation in critically ill patients, and prediction models incorporating medication information showed modest improvement in this prediction.

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Section: Discussionmentioning

confidence: 99%

Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data

Sikora,

Zhao,

Kong

et al. 2023

Preprint

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“…These machines offer various features and modes for Noninvasive PPV (NIPPV), using facial or nasal masks, or Invasive PPV (IPPV), employing Endotracheal Tubes (ETT) or Tracheostomy Tubes (TT). However, PPVs, especially IPPVs, can impose serious health complications due to factors related to intubation, sedation, and PPV management [17].…”

Section: Introductionmentioning

confidence: 99%

ExoventQ: A Novel Low-Cost Portable Negative Pressure Ventilator Design and Implementation

Gaben,

Abughanam,

Ibtehaz

et al. 2024

IEEE Access

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The onset of Coronavirus Disease 2019 (COVID-19) led to significant shortages in mechanical ventilators worldwide. This situation prompted investigations to discover new methods for producing lowcost, safe ventilators. Among the popular types of ventilators are positive pressure ventilators (PPVs), conventional negative pressure ventilators (NPVs), and biphasic cuirass ventilators (BCVs). Unfortunately, PPVs were found to cause serious health complications for patients, not to mention their high manufacturing costs. Therefore, in this study, we introduce ExoventQ, an innovative, cost-effective respiratory support device derived from historical NPV designs. The system was meticulously designed, simulated, implemented, and tested in two modes: continuous negative extrathoracic pressure (CNEP) and cyclic negative pressure ventilation (CNPV). ExoventQ comprises a pressure vessel, a pumping system, and a control panel. Each of these three major subsystems was designed with considerations of pressure distribution, material, safety, cost, and portability. The ANSYS stress analysis of the polycarbonate pressure vessels indicates that a semicylindrical vessel can withstand more pressure than a prismatic vessel without experiencing permanent deformations or fractures. Subsequently, the structure was modified to adopt a squircle-shaped vessel to prevent the airway from tilting when assembled on the side, providing the patient with more space to lie comfortably. The pressure inside the vessel is regulated via a bypass butterfly valve actuated by a servo motor. The user interface was implemented on a Raspberry Pi touchscreen, allowing inputs to be entered by rotating the knobs on the screen, with the output displayed for monitoring. To ensure patient safety, a range of safety measures were implemented, including audio and visual alarms and a power switch that halts ventilation if the vacuum in the vessel drops below 40 mbar. The successful design and implementation of this system have the potential to pave the way for the mass production of safe and affordable NPVs to address pulmonary complications.

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“…1 In severe COVID-19 disease with patients were put on NIV therapy but the risk of aerosol dispersion associated with NIV therapy and consequent contraction of COVID-19 disease was a constant fear amongst health care workers. Complications of invasive mechanical ventilation in Severe COVID-19 diseases like high rate of mortality, difficult weaning, barotrauma, and Ventilator-associated pneumonia(VAP) have led to renewed interest in the utility of NIV 3 . In patients with ARDS, HFNC, NIV, and severe cases invasive ventilation is the last resort for the management.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness and safety of non invasive pressure ventilation in severe COVID-19 disease: A retrospective analysis

Gupta¹,

Dalal

Das³

2021

PJMS

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Noninvasive ventilation (NIV) has a controversial role in treating acute hypoxemic respiratory failure in Severe COVID-19 disease. Noninvasive ventilation has been known to avoid intubation and prevent complications associated with mechanical ventilation, but the risk of aerosolization and consequent contraction of disease deterred clinicians from using it.: The medical records of 18 patients having severe COVID -19 disease with Acute respiratory distress syndrome (ARDS), who received NIV therapy in a tertiary care hospital were scrutinized from a period of 15 June 2020 to 28 June 2020. The parameters like respiratory rate (RR)and PaO2/FiO2(PF ratio) and SOFA score were collected from the day of admission to 5th day of ICU stay. Other parameters like outcomes of NIV therapy, complications and time taken from weaning from NIV were recorded. Forty-five health care workers, involved in the treatment were educated about use of PPE and NIV and were tested for COVID -19 by RT-PCR post-ICU rotation.: The statistical analysis was done by statistical package for social science version(SPSS) 22.0. The parameters were compared by using repeated measure analysis of variance.The mean age group of the patient in the study was 47.44 years. The respiratory rate and PaO2/FIO2 at the time of ICU admission were 29.28±3.74 per minute and 121.06±29.05 respectively. There was significant improvement in PF ratio throughout the observation (p=0.021) and the respiratory rate decreased after NIV therapy from the day of admission to the subsequent days (p=0.001). The major proportion (i.e. 88.8%) of patients with ARDS but SOFA score <5, had a favorable outcome with NIV therapy. 45 HCWs tested negative for SARS-CoV-2. Non-invasive ventilation can be safely used as an effective therapy for moderate to severe ARDS due to COVID-19 disease.

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Complications and Pharmacologic Interventions of Invasive Positive Pressure Ventilation During Critical Illness

Cited by 3 publications

References 256 publications

Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data

Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data

ExoventQ: A Novel Low-Cost Portable Negative Pressure Ventilator Design and Implementation

Effectiveness and safety of non invasive pressure ventilation in severe COVID-19 disease: A retrospective analysis

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