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To determine the accuracy and generalizability of VA-LRTI algorithm to detect and predict three high-incidence and high-impact VAEs from electronic health records data: 1) ventilator-associated event, 2) ventilator-associated pneumonia, and 3) ventilator-associated tracheobronchitis.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Dataset for development and testing |
| ||
| Dataset for external validation |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Diagnostic and prognostic models for VA-LRTIs | Other | Diagnostic and prognostic models for VA-LRTIs |
|
| Measure | Description | Time Frame |
|---|---|---|
| Number of participants with VA-LRTI as assessed by risk-calculator | Prediction model to be used at the moment of diagnosis and algorithms to be used prior IMV to predict the risk of VA-LRTI. | 1.6.-31.12.2021 |
| Measure | Description | Time Frame |
|---|---|---|
| Rate of in-hospital mortality | Prediction model to be used at the moment of diagnosis to predict the risk of mortality in VA-LRTIs. | 1.6.-31.12.2021 |
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All invasively ventilated ICU patient (aged 18 or over)
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Adult mixed medical-surgical ICU patients
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Miia Jansson, PhD | Contact | +358 50 470 12 62 | miia.jansson@oulu.fi |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Univeristy of Oulu | Oulu | Finland |
|
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