Carbon Monoxide-induced Coma: Prognostic Factors

Coma Clinical Trial

— Coma-CO  

Official title:

Prognostic Factors of Carbon Monoxide-induced Coma Treated by Hyperbaric Oxygen: a Retrospective Study

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03926494
• Other study ID #: 18PMG-COMA-CO
• Status: Completed
• Start date: May 1, 2019
• Est. completion date: June 30, 2019

Study information

• Verified date: November 2019
• Source: Assistance Publique - Hôpitaux de Paris
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The primary objective of the study is to determine prognostic factors for hospital-mortality following carbon monoxide (CO)-induced coma. The secondary objective is to determine prognostic factors of CO related cognitive sequelae, at the time of hospital discharge.

Description:

Carbon monoxide is a leading cause of poison related lethality in France. Moreover, survivors may develop severe neuro-cognitive sequelae. Few studies sought to determine prognostic factors related to CO induced coma.

Coma is defined as a Glasgow coma score of < 8. Neurological sequels will be considered persistent when present at hospital discharge.

This is a retrospective observational study. All comatose patients with Glasgow coma score < 8 due to carbon monoxide poisoning, treated by hyperbaric oxygen therapy in a tertiary hospital in the Île de France area, will be included in the study. Clinical, biological, iconographic and electrophysiological data collected from patient's medical files between January 2000 to December 2018 will be analysed retrospectively.

Statistics

Base-line characteristics will be summarized using tabulated Statistics, namely median [interquartile range, IQR] or percentages (*"Statistics") unless specified.

Exact Fisher tests will be used to compare distribution of binary outcomes, while nonparametric Wilcoxon rank sum tests will be used for comparison of continuous variables.

Logistic regression models will be used to measure the strength of association of the variables with the outcomes, by odds ratio (OR), either unadjusted or adjusted in multivariable models.

Multivariate imputation by chained equations (MICE) will be used as the method of dealing with missing data in covariates. It operates under the assumption that given the variables used in the imputation procedure, the missing data are Missing At Random (MAR), which means that the probability that a value is missing depends only on observed values and not on unobserved values. A total of m = 30 imputed datasets will be generated, with Rubin's rules applied thereafter to provide mean estimates of the ORs. The package mice implemented the MICE procedure within R.

All tests are 2-sided with p-values of 0.05 or less denoting statistical significance. Statistical analysis will be performed on R 3.5.1

Recruitment information / eligibility

• Status: Completed
• Enrollment: 212
• Est. completion date: June 30, 2019
• Est. primary completion date: June 30, 2019
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• All comatose patients (Glasgow coma score <8) due to carbon monoxide poisoning, treated by hyperbaric oxygen therapy in a tertiary hospital in Île de France area;

• Aged = 18 years;

• Hospitalized in hyperbaric medicine unity of Raymond Poincaré hospital in Garches.

Exclusion Criteria:

• Pregnant woman;

• Patient present clinical signes of stroke and without CO detection.

In case of unusable data, patient will be excluded from study.

Related Conditions & MeSH terms

• Carbon Monoxide Poisoning
• Coma
• Poisoning

Locations

Country	Name	City	State
France	Intensive Care Unit, Raymond Poincaré hospital	Garches

Sponsors (1)

Lead Sponsor	Collaborator
Assistance Publique - Hôpitaux de Paris

Country where clinical trial is conducted

France, 

References & Publications (1)

Resche-Rigon M, White IR. Multiple imputation by chained equations for systematically and sporadically missing multilevel data. Stat Methods Med Res. 2018 Jun;27(6):1634-1649. doi: 10.1177/0962280216666564. Epub 2016 Sep 19. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Mortality rate	Mortality rate during the stay in hospital: patient alive or not at discharge or death	28-day
Secondary	Cognitive sequelae at hospital discharge	Assessment of neurological sequelae at hospital discharge: epilepsia or abnormal movements recorded in files	28-day
Secondary	Cognitive sequelae at hospital discharge	Assessment of neurological sequelae at hospital discharge: motor deficit recorded in files	28-day
Secondary	Cognitive sequelae at hospital discharge	Assessment of neurological sequelae at hospital discharge: disorders of consciousness recorded in files	28-day
Secondary	Cognitive sequelae at hospital discharge	Assessment of neurological sequelae at hospital discharge: cognitive and psychological disorders recorded in files	28-day

External Links

•   Mice : Multivariate Imputation by Chained Equations in R.
•   R Development Core Team (2008)
•   R Development Core Team (2008). R: A language and environment for statistical computing. R Foundation for Statistical Computing