Ignite Creation Date:
2024-05-06 @ 7:02 PM
Last Modification Date:
2024-10-26 @ 2:59 PM
Study NCT ID:
NCT05875220
Status:
RECRUITING
Last Update Posted:
2023-11-30
First Post:
2023-04-26
Brief Title:
Organic Compounds and Postoperative Delirum
Sponsor:
University of Virginia
Organization:
University of Virginia
Study Overview
Official Title:
Exhaled Volatile Organic Compounds Phospho-tau and Postoperative
Status:
RECRUITING
Status Verified Date:
2023-11
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
This study involves collecting exhaled breath containing hundreds of volatile organic compounds VOCs that are present in very low quantity parts per billion VOCs in the exhaled gase carry information to indicate individuals risk for Postoperative Delirium and its severity Our long-term objectives are to identify breathomic patterns for prediction early detection and stratification of POD during pre- and post-operative phases
Detailed Description:
Post-operative delirium POD is a serious clinical syndrome associated with increased mortality and morbidity Old age and Alzheimers disease are at an increased risk for developing post-operative delirium POD occurs in 60 of patients after surgery ref and is associated with a poor outcome including longer hospitalization and higher rate of mortality ref Although the investigators have methods like AD biomarker blood tests they are expensive and time-consuming
This study involves collecting exhaled breath containing hundreds of volatile organic compounds VOCs that are present in very low quantity parts per billion These VOCs are by-products of metabolic activities in healthy and disease states VOCs in the exhaled gases which can be extracted in a noninvasive fashion carry information to indicate individuals risk for POD and its severity Real-time monitoring of VOCs could potentially produce point-of-care POC breathomic signatures capable of rapid prediction during pre-operative phase as well as early diagnosis and stratification of POD during post-operative phase However there is no study on analyzing exhaled gases of patients with surgery to improve their outcome In this initial project the investigators propose to determine whether a portable and fully automated gas chromatography GC device which can be attached to an anesthesia machine circuit is capable of rapidly detecting exhaled VOCs for POD prediction Our long-term objectives are to identify breathomic patterns for prediction early detection and stratification of POD during pre- and post-operative phases Such POC monitoring has a great potential not only to be transformative in perioperative managing patients with surgery and allowing for precision treatment but also to elicit the pathophysiological understanding of POD and accelerate drug development for reducing POD
The investigators hypothesize that patients with POD have a unique pattern of exhaled VOCs and that this pattern is associated with AD-related biomarkers in the blood
Aim 1 To determine whether patients with POD have a pattern of exhaled VOCs that is different from patients without POD The exhaled gases of patients with a major spine surgery will be analyzed by a portable GC with an automated GC data processing pipeline for chromatogram peak feature extractions including baseline removal denoising normalization peak detection peak modeling and chromatogram alignment The VOC pattern of patients with POD will be compared with that of patients without POD
Aim 2 To determine whether the exhaled gas pattern is associated with AD-related biomarkers in the blood AD-related biomarkers in the blood will be measured by ELISA Correlations between the levels of VOCs that contribute to the pattern changes between patients with POD and patients without POD and the levels of AD related biomarkers will be performed Dysfunction of possible metabolic pathways in patients with POD may be indicated by VOCs that have changes in those patients
This study involves collecting exhaled breath containing hundreds of volatile organic compounds VOCs that are present in very low quantity parts per billion These VOCs are by-products of metabolic activities in healthy and disease states VOCs in the exhaled gases which can be extracted in a noninvasive fashion carry information to indicate individuals risk for POD and its severity Real-time monitoring of VOCs could potentially produce point-of-care POC breathomic signatures capable of rapid prediction during pre-operative phase as well as early diagnosis and stratification of POD during post-operative phase However there is no study on analyzing exhaled gases of patients with surgery to improve their outcome In this initial project the investigators propose to determine whether a portable and fully automated gas chromatography GC device which can be attached to an anesthesia machine circuit is capable of rapidly detecting exhaled VOCs for POD prediction Our long-term objectives are to identify breathomic patterns for prediction early detection and stratification of POD during pre- and post-operative phases Such POC monitoring has a great potential not only to be transformative in perioperative managing patients with surgery and allowing for precision treatment but also to elicit the pathophysiological understanding of POD and accelerate drug development for reducing POD
The investigators hypothesize that patients with POD have a unique pattern of exhaled VOCs and that this pattern is associated with AD-related biomarkers in the blood
Aim 1 To determine whether patients with POD have a pattern of exhaled VOCs that is different from patients without POD The exhaled gases of patients with a major spine surgery will be analyzed by a portable GC with an automated GC data processing pipeline for chromatogram peak feature extractions including baseline removal denoising normalization peak detection peak modeling and chromatogram alignment The VOC pattern of patients with POD will be compared with that of patients without POD
Aim 2 To determine whether the exhaled gas pattern is associated with AD-related biomarkers in the blood AD-related biomarkers in the blood will be measured by ELISA Correlations between the levels of VOCs that contribute to the pattern changes between patients with POD and patients without POD and the levels of AD related biomarkers will be performed Dysfunction of possible metabolic pathways in patients with POD may be indicated by VOCs that have changes in those patients
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None
Secondary IDs
| Secondary ID | Type | Domain | Link |
|---|---|---|---|
| R21AG083656 | NIH | None | httpsreporternihgovquickSearchR21AG083656 |