Predictive algoRithm for EValuation and Intervention in SEpsis (PREVISE)
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ClinicalTrials.gov Identifier: NCT03235193 |
Recruitment Status : Unknown
Verified August 2017 by Dascena.
Recruitment status was: Recruiting
First Posted : August 1, 2017
Last Update Posted : August 3, 2017
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Condition or disease | Intervention/treatment | Phase |
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Sepsis Septic Shock Severe Sepsis | Other: Severe Sepsis Prediction Other: Severe Sepsis Detection | Not Applicable |
Study Type : | Interventional (Clinical Trial) |
Estimated Enrollment : | 1241 participants |
Allocation: | Non-Randomized |
Intervention Model: | Factorial Assignment |
Masking: | None (Open Label) |
Primary Purpose: | Diagnostic |
Official Title: | Prediction of Severe Sepsis Using a Machine Learning Algorithm |
Actual Study Start Date : | August 1, 2017 |
Estimated Primary Completion Date : | October 2017 |
Estimated Study Completion Date : | October 2017 |

Arm | Intervention/treatment |
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Experimental: With InSight
Healthcare provider receives an alert from InSight for patients trending towards severe sepsis. Healthcare provider also receives information from the severe sepsis detector in the CHH electronic health record.
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Other: Severe Sepsis Prediction
Upon receiving an InSight alert, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly. Other: Severe Sepsis Detection Upon receiving information from the severe sepsis detector in the CHH electronic health record, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly. |
Active Comparator: Without Insight
Healthcare provider does not receive any alerts from InSight. Healthcare provider receives information from the severe sepsis detector in the CHH electronic health record.
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Other: Severe Sepsis Detection
Upon receiving information from the severe sepsis detector in the CHH electronic health record, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly. |
- In-hospital mortality [ Time Frame: Through study completion, an average of 30 days ]
- Hospital length of stay [ Time Frame: Through study completion, an average of 30 days ]
- Hospital readmission [ Time Frame: Through study completion, an average of 30 days ]
- ICU length of stay [ Time Frame: Through study completion, an average of 30 days ]

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Ages Eligible for Study: | 18 Years and older (Adult, Older Adult) |
Sexes Eligible for Study: | All |
Accepts Healthy Volunteers: | No |
Inclusion Criteria:
- All adult patients visiting the emergency department, or admitted to the participating intensive care unit (ICU) wards of Cabell Huntington Hospital will be eligible.
Exclusion Criteria:
- All patients younger than 18 years of age will be excluded.

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03235193
Contact: Ritankar Das | 8722285332 | ritankar@dascena.com |
United States, West Virginia | |
Cabell Huntington Hospital | Recruiting |
Huntington, West Virginia, United States, 25701 | |
Contact: Hoyt Burdick |
Principal Investigator: | Hoyt Burdick | Cabell Huntington Hospital |
Publications:
Responsible Party: | Dascena |
ClinicalTrials.gov Identifier: | NCT03235193 History of Changes |
Other Study ID Numbers: |
1097090-1 |
First Posted: | August 1, 2017 Key Record Dates |
Last Update Posted: | August 3, 2017 |
Last Verified: | August 2017 |
Studies a U.S. FDA-regulated Drug Product: | No |
Studies a U.S. FDA-regulated Device Product: | No |
Sepsis Toxemia Infection |
Systemic Inflammatory Response Syndrome Inflammation Pathologic Processes |