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Today, the electronic medical record, microprocessor mechanical ventilators, and physiologic monitoring are under-utilized when translating research into decision support. Current medical informatic capabilities can be leveraged to calculate trends in measured parameters to initiate a paradigm shift in critical care from reaction-based treatment to proactive and plausibly preventative care. Therefore, the purpose of this study is to develop baseline understanding of our practice and how data collection utilizing a newly implemented system called T3. We would like to retrospectively review mechanically ventilated patients in which we have collected continuous data to test a newly developed analytic platform. Additionally we would like to compare these results to our standards of practice established by clinical practice guidelines.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Device utlization following extubation | |||
| Pulmonary mechanics |
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| Measure | Description | Time Frame |
|---|---|---|
| Successful Extubation | Successful extubation without the use of noninvasive ventilation or requiring reintubation | Within 24 hours of extubation |
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Inclusion Criteria:
Exclusion Criteria:
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All mechanically ventilated patients in our medical surgical ICU.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Boston Children's Hospital | Boston | Massachusetts | 02115 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32879034 | Derived | Castineira D, Schlosser KR, Geva A, Rahmani AR, Fiore G, Walsh BK, Smallwood CD, Arnold JH, Santillana M. Adding Continuous Vital Sign Information to Static Clinical Data Improves the Prediction of Length of Stay After Intubation: A Data-Driven Machine Learning Approach. Respir Care. 2020 Sep;65(9):1367-1377. doi: 10.4187/respcare.07561. | |
| 28073993 |
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| ID | Title | Description |
|---|---|---|
| FG000 | Patient Categorization | We retrospectively categorized the ventilation and oxygenation statuses of patients within our PICU utilizing 15 rules based algorithms. Targets were predetermined based on generally accepted practices. All patient categories were calculated and presented as a percent score (0-100%) of acceptable ventilation, acceptable oxygenation, barotrauma free and volutrauma free states. |
| Title | Milestones | Reasons Not Completed | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
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| ID | Title | Description |
|---|---|---|
| BG000 | Patient Categorization | We retrospectively categorized the ventilation and oxygenation statuses of patients within our PICU utilizing 15 rules based algorithms. Targets were predetermined based on generally accepted practices. All patient categories were calculated and presented as a percent score (0-100%) of acceptable ventilation, acceptable oxygenation, barotrauma free and volutrauma free states. |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Median |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Successful Extubation | Successful extubation without the use of noninvasive ventilation or requiring reintubation | Posted | Count of Participants | Participants | Within 24 hours of extubation |
|
Duration of ICU stay.
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Device Utlization Following Extubation | Patients who were extubated were evaluated. |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Brian Kendall Walsh | Boston Children's Hospital | 617-919-3692 | brian.walsh@childrens.harvard.edu |
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| ID | Term |
|---|---|
| D012128 | Respiratory Distress Syndrome |
| ID | Term |
|---|---|
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D012120 | Respiration Disorders |
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| Walsh BK, Smallwood C, Rettig J, Kacmarek RM, Thompson J, Arnold JH. Daily Goals Formulation and Enhanced Visualization of Mechanical Ventilation Variance Improves Mechanical Ventilation Score. Respir Care. 2017 Mar;62(3):268-278. doi: 10.4187/respcare.04873. Epub 2017 Jan 10. |
| 27303050 | Derived | Walsh BK, Smallwood CD, Rettig JS, Thompson JE, Kacmarek RM, Arnold JH. Categorization in Mechanically Ventilated Pediatric Subjects: A Proposed Method to Improve Quality. Respir Care. 2016 Sep;61(9):1168-78. doi: 10.4187/respcare.04723. Epub 2016 Jun 14. |
| years |
|
| Sex: Female, Male | Count of Participants | Participants |
|
| Race (NIH/OMB) | Count of Participants | Participants |
|
| Region of Enrollment | Number | participants |
|
| Units |
|---|
| Counts |
|---|
| Participants |
|
|
| 9 |
| 104 |
| 0 |
| 104 |
| 0 |
| 104 |
| EG001 | Pulmonary Mechanics | All patients on mechanical ventilation were evaluated. | 20 | 222 | 0 | 222 | 0 | 222 |
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