This was a retrospective cohort study of patients included in the sepsis protocol in two Brazilian university hospitals. This study was approved with a waiver of informed consent by the institutional review board of the Pontifícia Universidade Católica do Paraná (CAAE number: 79976517.4.0000.0020).

This study was conducted on adult patients with suspected sepsis. The cohort included patients admitted at two academic public hospitals between January 2016 and December 2021. The first hospital was composed of an emergency room, a 207-bed hospital ward, and a 29-bed mixed intensive care unit (ICU), but reference for trauma, neurosurgery, and general surgery. The second hospital was also composed of an emergency room, 240-bed hospital wards, and a 38-bed ICU, reference for general surgery and cardiovascular surgery.

Both hospitals present the same antimicrobial stewardship team.

The antibiotic therapy decisions were based on local microbial resistance profiles.14 The antibiotic stewardship program (ASP) implemented a restrictive policy for dispensing carbapenems and polymyxin using a hand-filled form.15 In addition, a prospective auditing and feedback process was adopted for all antimicrobial prescriptions. Dose, length of treatment adjustment, de-escalation, route of administration, and side effects were determined under the guidance of a clinical pharmacist and infectious diseases specialist.16

Once sepsis was suspected and judged that antimicrobial therapy was needed in the first hour, the physician fulfilled the protocol. However, only those with Sepsis-3 criteria were included,3 which was defined within 24 hours by the antimicrobial stewardship. The patients were followed up until death or discharge. The hour-1 bundle includes: i) measuring lactate level and remeasuring lactate if initial lactate is elevated (> 2 mmol/L); ii) obtaining blood cultures before administering antibiotics; iii) administration of broad-spectrum antibiotics; iv) rapid administration of 30 mL/kg crystalloid for hypotension or lactate ≥ 4 mmol/L; v) application of vasopressors if the patient was hypotensive during or after fluid resuscitation to maintain a mean arterial pressure ≥65 mmHg.7 The sepsis bundle is shown in Supplementary Figure 1 (Fig. 1).

Figure 1.

Schematic model of sepsis bundle protocol used in the hospital for screening and data analysis.

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Inclusion criteria were (i) a hospital admission, (ii) ≥18 years of age, and (iii) a starting sepsis protocol, (iv) sepsis diagnosis according to Sepsis-3 criteria.3 The only exclusion criterion was a lack of information in the patient’s sepsis protocol file to avoid selection bias. Follow-up was performed using electronic medical records. Patients with more than one episode of sepsis were included as a “new” event. The population of the study included ICU, ward, and emergency room.

The SIRS (2 points) and qSOFA (2 points), as well as other clinical data were considered at the moment of protocol. The SIRS criteria (i.e., temperature > 38 °C, heart rate >90/min, respiratory rate >20/min, and leukocytes >12,000 or <4,000 cell/mm3)17 and qSOFA score (i.e., systolic blood pressure <100 mmHg, respiratory rate >22 rpm, and Glasgow coma scale <15) were used.18 Comorbidities were analyzed according to the Charlson comorbidity index.19 Hospital-acquired infection were defined according with the Centers for Disease Control and Prevention were included.20 Community-acquired infection was defined based on the physician’s classification, using the International Classification of Diseases, Tenth Revision (ICD-10), and diagnosis codes.21

The primary outcome was global mortality. The timing of antibiotic treatment relative to clinical diagnosis was evaluated. The cultures were evaluated, and appropriate antimicrobial therapy was provided to patients with sepsis. The length of hospital stay was also assessed. Outcomes were compared according to SIRS criteria and qSOFA scores, hospital unit (ICU, ward, or emergency room [ER]), and positive cultures.

The continuous variables were expressed was mean or median according with normality test (Kolmogorov–Smirnov test). The descriptive variables were expressed as percentages. The dispersion of variables were standard deviation or 95% confidence interval.

In the bivariate analysis, P-values were calculated using the χ2 or Fisher’s exact test for categorical variables and the Student’s t-test or Mann–Whitney test for continuous variables. The covariates were compared based on the criteria for sepsis and outcomes. Covariates were compared between survivors versus non-survivors. In the forward stepwise regression, variables with P-values ≤ 0.2 were included in the model, while those with P-values ≤ 0.10 were maintained in the model. Multicollinearity was calculated with the variance inflation factor for each independent variable. Variables which included other variables (e.g., SIRS and qSOFA) were not included in the model. All tests were two-tailed. A P significance was set at P < 0.05. A receiver operating characteristic (ROC) curve was constructed based on independent variables associated with mortality and the logistic binary regression model. The score was based on coefficient (beta) of each variable in the multivariable analysis. The area under the curve (AUC) was calculated to determine the internal performance of the score based on multivariable analysis.

A total of 2,232 were screened and 205 were excluded due to lack of data, and 219 patients do not fulfill sepsis-3 criteria. Thus, 1,808 were included in the study. The mean age was 60 years (interquartile range [IQR]: 42–72), and 38% of the patients were men. The SIRS criteria (≥2) and qSOFA (≥2) accounted for 63% (n = 1,278) and 29% (n = 593), respectively. The main sites of infection were the lungs (42% [n = 657]) and abdomen (15% [n = 236]). The median length of hospital stay after sepsis was 10 days (IQR: 4–22), while death occurred in 36.8% of patients (n = 666). The mortality in patients admitted at ICU was 47.7%, at emergency room 26.2%, and those with diagnosis of sepsis in the ward was 26.8%. The main comorbidities were systemic arterial hypertension (SAH) (42% [n = 782]), diabetes mellitus (DM) (16% [n = 303]), previous stroke (14.7% [n = 274]), and cancer (8.3% [n = 155]). Among the patients with microbiological data, 45% (n = 626) presented with positive culture results. Blood cultures were obtained from all patients and other cultures, according to the medical decision.

The data from patients who died or survived are described in the Table 1. The mortality, the outcome variable, was higher in ICU admitted patients (p < 0.001), but similar between emergency room and ward. Twenty variables were found to be related to death after univariate analysis. Major variables were age (64 vs. 52 years, P < 0.001), length of hospital stay before sepsis (10 vs. 5.4 days, P < 0.001), temperature >38 °C (26% vs. 39%, P < 0.001), leukocytes >12,000 or <4,000 cells/mm3 (49% vs. 38%, P = 0.001), qSOFA criteria >2 (35% vs. 25%, P < 0.001), altered level of consciousness (30% vs. 21%, P < 0.001), low blood pressure (i.e., systolic blood pressure [SBP] <90 mmHg) (31% vs. 21%, P < 0.001), minutes to antimicrobial infusion (45 min vs. 35 min, P < 0.001), heart failure (9.5% vs. 4.8%, P < 0.0001), previous stroke (20% vs. 11%, P < 0.0001), SAH (47% vs. 38%, P < 0.001), cancer (13% vs. 5.5%, P < 0.001), previous sepsis (35% vs. 18%, P < 0.0001), and positive culture (50% vs. 39%, P < 0.0001).

Despite these 20 variables, after multivariate analysis, half of them remained independent variables related to death (Table 2). Characteristics such as (i) cirrhosis, (ii) dialysis, and (iii) cancer at least doubled the risk of death: (i) (odds ratio [OR] = 3.97, 95% confidence interval [CI] 1.41–11.16, P = 0.009), (ii) (OR = 2.51, 95% CI 1.54–4.10, P < 0.0001), and (iii) (OR = 2.2, 95% CI 1.49–3.24, P < 0.0001). Other variables were also related to poor prognosis increasing between 42–93% the odds of death: previous sepsis (OR = 1.42, 95% CI 1.08–1.87, P = 0.012), qSOFA criteria ≥2 (OR = 1.43, 95% CI 1.12–1.84, P = 0.04), leukocytes >12,000 or <4,000 cells/mm3 (OR = 1.61, 95% CI 1.27–2.03, P < 0.0001), and previous stroke (OR = 1.88, 95% CI 1.39–2.55, P < 0.0001). A temperature >38 °C was related to survival (OR = 0.65, 95% CI 0.51–0.83, P = 0.0001].

Considering the equation of the binary regression logistic analysis, the weight of each significant variable was calculated using the following equation: mortality score = 2.186 × (chronic renal failure) + 2.51 × (cerebrovascular disease) + 2.629 × (cancer) + 2.992 × (cirrhosis) + 1.842 × (previous sepsis) + 2.040 × (fever) + 1.387 × (leukocytosis or leukopenia). The mortality risk according to the scores is presented in Table 3.

When applying the score, a ROC curve was constructed, as shown in Fig. 2, considering the sensitivity and specificity of the mortality prediction score. The AUC was 0.668 (95% CI 0.623–0.702), suggesting that the mortality score based on the multivariable analysis was weak. We also performed a ROC curve for SIRS and qSOFA, with AUC = 0.522 (95% CI 0.481–0.563) and 0.583 (95% CI 0.535–0.631), respectively (Supplementary material).

Figure 2.

Receiver operating characteristic (ROC) curve from equation model obtained after multivariable analysis of risk factors associated with death in patients included in a sepsis protocol bundle. The AUC of the ROC curve was 0.66.

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