Adverse effects of delayed antimicrobial treatment and surgical source control in adults with sepsis: results of a planned secondary analysis of a cluster-randomized controlled trial

Abstract

Background: Timely antimicrobial treatment and source control are strongly recommended by sepsis guidelines, however, their impact on clinical outcomes is uncertain.

Methods: We performed a planned secondary analysis of a cluster-randomized trial conducted from July 2011 to May 2015 including forty German hospitals. All adult patients with sepsis treated in the participating ICUs were included. Primary exposures were timing of antimicrobial therapy and delay of surgical source control during the first 48 h after sepsis onset. Primary endpoint was 28-day mortality. Mixed models were used to investigate the effects of timing while adjusting for confounders. The linearity of the effect was investigated by fractional polynomials and by categorizing of timing.

Results: Analyses were based on 4792 patients receiving antimicrobial treatment and 1595 patients undergoing surgical source control. Fractional polynomial analysis identified a linear effect of timing of antimicrobials on 28-day mortality, which increased by 0.42% per hour delay (OR with 95% CI 1.019 [1.01, 1.028], p ≤ 0.001). This effect was significant in patients with and without shock (OR = 1.018 [1.008, 1.029] and 1.026 [1.01, 1.043], respectively). Using a categorized timing variable, there were no significant differences comparing treatment within 1 h versus 1-3 h, or 1 h versus 3-6 h. Delays of more than 6 h significantly increased mortality (OR = 1.41 [1.17, 1.69]). Delay in antimicrobials also increased risk of progression from severe sepsis to septic shock (OR per hour: 1.051 [1.022, 1.081], p ≤ 0.001). Time to surgical source control was significantly associated with decreased odds of successful source control (OR = 0.982 [0.971, 0.994], p = 0.003) and increased odds of death (OR = 1.011 [1.001, 1.021]; p = 0.03) in unadjusted analysis, but not when adjusted for confounders (OR = 0.991 [0.978, 1.005] and OR = 1.008 [0.997, 1.02], respectively). Only, among patients with septic shock delay of source control was significantly related to risk-of death (adjusted OR = 1.013 [1.001, 1.026], p = 0.04).

Conclusions: Our findings suggest that management of sepsis is time critical both for antimicrobial therapy and source control. Also patients, who are not yet in septic shock, profit from early anti-infective treatment since it can prevent further deterioration. Trial registration ClinicalTrials.gov ( NCT01187134 ). Registered 23 August 2010, NCT01187134.

Keywords: Anti-biotic agents; Infection control; Patient care bundles; Sepsis; Surgical source control; Time-to-treatment.

Conflict of interest statement

Dr. Rüddel has nothing to disclose. Dr. Bloos reports grants from German Federal Ministry of Education and Research to his institution, during and outside the conduct of the study; personal fees from Baxter, outside the submitted work, and receipt of kits for a clinical trial from Assoc. of CapeCods, outside the submitted work. Dr. Thomas-Rüddel reports grants from BMBF to his institution, outside the submitted work..Dr. Reinhart is shareholder with less of 0.5% of InflaRx NV a Jena /Germany based Biotech Company that evaluates a immunmodulatory approach for the adjunctive treatment of COVID-19. Dr. Bach has nothing to disclose. Dr. Gerlach has nothing to disclose. Dr. Lindner has nothing to disclose. Dr. Marshall reports consulting fees from Gilead Pharma, support for traveling to the WHO Covid-19 meeting by Bill and Melinda Gates Foundation, personal fees from AM Pharma for participation on a data safety monitoring board, being chair of the International Forum for Acute Care Trialists (unpaid), and being co-chair of the WHO Working Group on Clinical Characterization and Management of Covid-19 (unpaid), all outside the submitted work. Dr. Simon has nothing to disclose. Dr. Weiss has nothing to disclose. Dr. Schwarzkopf reports grants from German Federal Ministry of Education and Research to his institution, during the conduct of the study.

© 2022. The Author(s).

Figures

Fig. 1

Crude outcomes and predicted outcomes depending on time to treatment. Presented are the risk (bars) and predicted risk (lines) across a range of time after onset of sepsis. Bold lines present the predicted risk with 95% confidence interval for a typical patient from a model adjusting for covariates, dotted lines present the predicted risk with 95% confidence interval from a model without adjusting for covariates. The effect of timing was tested for linearity by fractional polynomials at significance level 0.05; in panels a to c timing is treated as linear, since no significant deviation from linearity was found. Models adjusted for the following covariates: age and gender, origin of infection, location of the patient at the onset of sepsis, focus of infection, microbiological confirmation of infection, study phase (trial vs. surveillance phase), and group the hospital was randomized to (intervention vs. control). a Effect of time to antimicrobial therapy within the first 48 h on 28-day mortality. N = 4792 cases were treated with antimicrobials within 48 h after sepsis onset, of which 4659 (97%) cases had complete data on outcome and covariates for analysis. b Effect of timing of surgical source control within the first 48 h on 28-day mortality. N = 1595 cases had surgical source control within 48 h after onset of sepsis, of which 1563 (98%) cases had complete data on outcome and covariates for analysis. c Effect of time to antimicrobial therapy on the risk of progression to septic shock between 12 and 24 h after onset of sepsis. N = 1129 received their first antimicrobial treatment within 24 h after sepsis onset and were at risk of developing shock between 12 and 24 h, of these 1125 (99%) cases had complete data on outcome and covariates for analysis. d Effect of time to surgical source control on the risk of progression to septic shock between 12 and 24 h after onset of sepsis. Effect fitted by the fractional polynomial x+0.1/102+x+0.1/103 , where x is the timing of surgical source control. N = 193 cases did undergo a surgical source control within 24 h after sepsis onset and were at risk of developing shock between 12 and 24 h, of which 193 cases had complete data on outcome and covariates for analysis

Fig. 2

Effects of antimicrobial therapy and of surgical source control on 28-day mortality. Effects were tested in a logistic hierarchical linear model with a random intercept adjusting for covariates. Risk-adjusted mortality estimates were obtained as predictive margins that were calculated for the average of continuous variables and for the most common category of categorical variables. No. of patients gives the number of cases with complete data compared to the total number of patients suitable for the respective analysis. * marks the p-value of the overall test of significance for the categorical variables on timing conducted by a likelihood-ratio test, while the other p-values give the results of tests of single categories against the reference category. Models adjusted for the following covariates: age and gender, origin of infection, location of the patient at the onset of sepsis, focus of infection, microbiological confirmation of infection, study phase (trial vs. surveillance phase), and group the hospital was randomized to (intervention vs. control)

Fig. 3

Test of effect moderation of timing of treatment in prespecified subgroups for time from onset of sepsis to start of antimicrobial therapy (panel a) and conduction of surgical source control (panel b) on 28-day mortality. OR: odds ratio per hour delay of treatment. Only cases with times between 0 and 48 h were considered. Effect moderation was tested by introducing individual interaction terms between respective effect moderator and the effect of timing of antimicrobial therapy or timing of surgical source control, respectively, in the logistic regression models. Regression models were calculated by logistic hierarchical linear models with a random intercept. No. of patients gives the number of cases with complete data compared to the total number of patients within the respective subgroup. Models adjusted for the following covariates: age and gender, origin of infection, location of the patient at the onset of sepsis, focus of infection, microbiological confirmation of infection, study phase (trial vs. surveillance phase), and group the hospital was randomized to (intervention vs. control). ICU: intensive care unit; IMC: intermediate care unit