Effect of Statin Therapy on Sepsis-related Mortality in Intensive Care Unit Patients — HGG_UCI1  

Sepsis Clinical Trial

Official title: Preadmission Use of Statin Therapy and Sepsis-related Mortality in ICU Patients: a Population-based Cohort Study.

Status Completed

Clinical Trial Summary

The average age of patients with sepsis has increased in recent years in parallel with the incidence of sepsis. Many of these patients are frail and require various medications for the treatment of their chronic diseases. Common treatments, including e.g. sarcopenic drugs (statins, sulphonylureas, methyglinides), antioxidants that prevent sarcopenia (allopurinol) or immunoregulators (corticosteroids) may influence the survival and functional prognosis of these patients. Knowing which drugs influence sepsis survival and to what degree patients who survive sepsis have functional deterioration and increased comorbidity and which modifiable factors limit this may be essential.

Clinical Trial Description

The hypothesis of the study is that poor baseline health status, defined by frailty, comorbidities and chronic drug use, determines sepsis survival and long-term functional status of surviving patients. In addition, the study aims to analize the relationship between different groups of drugs, especially sarcopenal drugs, and sepsis survival in patients admitted to hospitals and Intensive Care Units in a region of 8 million inhabitants. Preliminary data suggest that patients with prior corticosteroid use have poorer survival to sepsis, while chronic statin use may be a protective factor.

This will be a retrospective population-based observational analysis of a large cohort of patients with sepsis using a population-based database over a 2-year period.

The data will be obtained from the Catalan Health System (CatSalut) Minimum Basic Data Set (CMBD) registers (compulsory admissions register for all public and private acute care hospitals in Catalonia, Spain. The registry is intended for the evaluation and optimisation of the use of resources, provides support and improves healthcare planning and facilitates the management of purchases and payments. A cohort of approximately 25,000 patients per year is available from the aforementioned databases (2). Data from 2018 and 2019 (pre-pandemic) will be initially included.

Sepsis will be defined using the methodology described by Angus et al, which is currently referenced for population-based studies, consisting of coding a diagnosis of infection with acute organ failure, or sepsis or septic shock.Patients requiring Intensive Care Unit (ICU) admission were identified from the coded procedures of mechanical ventilation, continuous renal replacement techniques (CRRT), tracheostomy, or extracorporeal membrane oxygenation (ECMO).

To analyse outpatient prescriptions, a patient will be considered to have prior treatment with a given medication if, during the 8 months prior to admission for sepsis, a minimum of 6 containers of that drug had been dispensed. The Anatomical, Therapeutic, Chemical (ATC) drug classification of the World Health Organization (WHO) will be used.

An analysis of demographics, risk factors, baseline status, comorbidities, and previous dependence on health services of all patients admitted to hospitals in the region will be carried out. Overall patients admitted to hospitals and those admitted to ICU will be analysed separately. Survival data will be compared with previous drug use, trying to find out the relationship between dependence to some groups of these drugs and survival to sepsis. In addition, drug dependence and health services dependence of sepsis survivors will be studied in comparison with their pre-sepsis situation.

A descriptive analysis of the baseline characteristics of the sample will be performed using absolute values and percentages or mean and standard deviation, as appropriate. To establish the relationship between the dependent and independent variables, a bivariate analysis will be performed using the chi-square or t-Student test, as appropriate. A logistic regression model will be applied to determine the risk factors for mortality, analysing the scores for comorbidities, frailty (defined as emergency admissions, being a resident or institutionalised, being previously defined as a complex chronic patient or advanced chronic disease) and chronic consumption of certain families of drugs, for all those variables that had obtained statistical significance in the bivariate analysis. Statistical significance will be established with a p-value of less than 0.001.

The creation of the scale predictive of mortality will be based on the combination of the risk factors detected in the previous logistic regression analyses. The reliability and validity of the scale for subgroups of the sample will be analysed to check that the psychometric characteristics of the instrument were valid for the different types of population. To study sepsis mortality, Cox regression models or competing risk models will be performed, comparing baseline states and different pharmacological treatments.

The impact on health care consumption of patients who do not survive sepsis will be based on data from the Catalan Health System (CatSalut) Minimum Basic Data Set (CMBD) registers, and it will not be an economic study using cost-effectiveness or health-assessment methodologies. ;

Related Conditions & MeSH terms

• Sepsis
• Septic Shock
• Toxemia

• NCT number: NCT06354452
• Study type: Observational [Patient Registry]
• Source: Hospital de Granollers
• Status: Completed
• Start date: January 1, 2018
• Completion date: January 31, 2020