Clinical trial NCT03926494: Carbon Monoxide-induced Coma: Prognostic Factors
Official title: Prognostic Factors of Carbon Monoxide-induced Coma Treated by Hyperbaric Oxygen: a Retrospective Study
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Coma
Carbon Monoxide Poisoning
Keywords: Carbon monoxide poisoning
Oxygen
Coma
Hyperbaric oxygen
Lead sponsor: Assistance Publique - Hôpitaux de Paris
Sponsor class: OTHER
First posted: 2019-04-24
Enrollment: 212
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: All comatose patients (Glasgow coma score \<8) due to carbon monoxide poisoning, treated by hyperbaric oxygen therapy in a tertiary hospital in the greater Paris area were included in the current study

Brief 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.

Detailed 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

Eligibility criteria: 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.

Primary outcomes:
measure: Mortality rate
timeFrame: 28-day
Secondary outcomes:
measure: Cognitive sequelae at hospital discharge
timeFrame: 28-day
measure: Cognitive sequelae at hospital discharge
timeFrame: 28-day
measure: Cognitive sequelae at hospital discharge
timeFrame: 28-day
measure: Cognitive sequelae at hospital discharge
timeFrame: 28-day
Other outcomes:
Locations:
city: Garches
country: France
facility: Intensive Care Unit, Raymond Poincaré hospital
Study officials:
affiliation: Intensive Care Unit, Raymond Poincaré hospital
name: Paris Meng, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: Intensive Care Unit, Raymond Poincaré hospital
name: Djillali ANNANE, MD, PhD
role: STUDY_DIRECTOR
References:
citation: 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.