Higher Mortality in Bacteremic Sepsis - A Propensity Score Matched Study

Sepsis is a highly heterogenous disease which needs to be thoroughly mapped. The aim of this study was to describe characteristics and outcome for critically ill patients with sepsis-3 with either culture-positive or -negative sepsis. Patients with severe sepsis or septic shock were retrospectively identied in the local quality registry from a general mixed Intensive Care Unit (ICU) at a University Hospital in 2007-2014. Data were collected through manual review of medical charts. Patients were included if they fullled sepsis-3 criteria and at least one blood culture was sampled ±48h from ICU admission. In a propensity score analysis bacteremic and non-bacteremic patients were matched 1:1 with regard to age, comorbidities, site of infection and antimicrobial therapy prior to blood cultures. A Latent Class Analysis (LCA) was performed to identify unmeasured class membership. 784 patients were identied as treated in the ICU with a sepsis diagnosis. Blood cultures were missing in 140 excluded patients and additionally 95 patients did not fulll a sepsis diagnosis and were also excluded. In total 549 patients were included, 295 (54%) with bacteremia, 90 (16%) were non-bacteremic but had relevant pathogens detected from another body location and in 164 (30%) no relevant pathogen was detected in microbial samples. After the propensity score analysis (n=172 in each group) 90-day mortality was higher in bacteremic patients, 47%, than in non-bacteremic patients, 36%, p =0.04. (n=124), p LCA identied 8 classes, with different mortality rates, where pathogen detection in microbial sampleswere important factors for class distinction andoutcome. The primary outcome is whether there are differences in mortality between bacteremic sepsis and non-bacteremic sepsis. Secondary outcomes are differences between the groups with regard to severity of disease, site of infection, comorbidities, preceding antibiotic therapy and other immunomodulatory medications and if there are subphenotypes with clinically distinction on prognosis.


Patient characteristics
A ow chart of patients is presented in Fig. 1. Over the eight study years, 784 patients were treated in the ICU and received a sepsis or septic shock diagnosis. Microbiological samples were not obtained within the prede ned time interval in 88 excluded patients. Additionally 52, lacked blood cultures and were excluded. Ninety-ve patients were excluded at the medical chart review due to absence of sepsis-3 diagnosis and 549 patients were nally included in the study. Blood cultures were positive in 286 of the patients, 83 had negative blood cultures but a positive culture from another body location classi ed as the focus of infection. One hundred and eighty patients were sterile without positive cultures. Four sterile patients were positive in polymerase chain reaction assay (PCR); 2 were positive for legionella and 1 for in uenza in respiratory tract samples and 1 for meningococci in cerebrospinal uid and were reclassi ed as pathogen-detected but nonbacteremic sepsis. Additionally, nine patients with positive blood culture and 3 patients where pathogens were detected from the site of infection, outside the 96-hour time frame surrounding ICU admission, were reclassi ed as bacteremic and pathogen-detected but nonbacteremic, respectively. This resulted in 54% (n = 295) bacteremic sepsis, 16% (n = 90) pathogen-detected but non-bacteremic sepsis and 30% (n = 164) sterile sepsis, see Fig. 1.
There were no missing data in the primary analyses. There were no differences in mortality between the groups of different microbiological status, Fig. 2a. For differences in demography and clinical characteristics between bacteremic and non-bacteremic patients see Table 1and  Table 2. 90-day mortality was compared by the log rank test.
Analyses were performed using SPSS software system version 24.0 (IBM, Armonk, NY), with the FUZZY extension except for LCA analyses, which were conducted using Mplus (version 8.14; Muthén & Muthén, Los Angeles, CA), with data preparation in R version 3.4.0 (The R Foundation for Statistical Computing).  Patients without preceding antibiotic therapy In 352 patients not treated with antibiotics prior to culture sampling, 63% (n = 223) were bacteremic, 14% (n = 50) were non-bacteremic but with positive microbial samples from foci of infection, and 22% (n = 79) were sterile sepsis.
These patients had similar characteristics except for renal disease being more common among bacteremic patients than non-bacteremic patients, 20 versus 4 patients, respectively, p = 0.04. Chronic obstructive pulmonary disease (COPD) was, however, less common among bacteremic patients, 20 patients versus 21 patients, p = 0.04, and likewise immunomodulatory medication in 6 bacteremic patients versus 10 non-bacteremic patients, p = 0.03.

Microbial samples
Escherichia coli was the most common pathogen detected from blood, and non-pneumococcal streptococci were the most common pathogens from other non-blood sites.
Patients from the bacteremic sepsis, pathogen-detected but non-bacteremic sepsis or sterile sepsis groups were compared for proportion of patients with microbial samples from presumed infectious foci. Generally, more microbial samples were sampled from patients with pathogens detected. When compared for proportion of patients with microbial samples from presumed infection foci, the differences between pathogen-detected and sterile sepsis did not remain for respiratory tract, urinary tract, central nervous system, bone and joints and drainage or wound for postoperative infections. A higher number of blood culture pairs were drawn in bacteremic patients, (mean 2.2, 95% CI 2.1-2.2) compared to non-bacteremic patients (mean 1.9, 95% CI 1.8-2.0) p < 0.01. All patients had at least one pair of blood culture drawn. Bacteremic patients had a higher proportion of a second pair of blood cultures drawn. The additional rate of positivity in the second pair of blood culture was 7.4% for the bacteremic patients. The addition of a second pair of blood culture in the non-bacteremic patients with only one pair of blood culture drawn, with an equal rate of positivity as in the bacteremic sepsis, would be equivalent to 4 more patients becoming bacteremic (Table 2).

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As comparisons of mortality between groups of patients with positive respectively negative in microbiological samples are most likely vulnerable to confounders, a propensity score analysis was performed. There were no missing data on the variables in the propensity score analysis.
In the entire cohort 172 matched pairs were retrieved, for clinical characteristics in the matched groups, see Table 3. Mortalities were signi cantly higher among bacteremic patients as were the total SOFA score, the SOFA scores for renal function, liver function, coagulation and lactate, Fig. 2b. Since the matching affected the mortality, the mortality was also compared for patients who had received antibiotic therapy prior to blood cultures. Non-bacteremic patients had signi cantly higher mortality if they received antibiotic therapy prior to blood cultures than if they had not received antibiotic therapy, Fig. 2c.

Latent Class Analysis
The following baseline variables were categorized and entered into a LCA-model: gender, bacteremia, pathogen-detected but non-bacteremic or sterile sepsis, sepsis-causing pathogen, foci of infection, prior antibiotic treatment, immunomodulatory medications, nosocomial infection, fever (> 38 °C), hypothermia (< 36 °C), acidosis (pH < 7.35), p-lactate (divided in quartiles; 0-1.8, > 1.8-3,>3-5.1,>5.1), and CNS-, respiratory-, cardiovascular-, renal-, liver-or coagulatory organ dysfunction. 469 patients without any missing data on the baseline variables were entered into the LCA. An eight-class model or a nine-class model were the best t for the cohort, ABIC continued to decrease until 9classes model, Table 4. We inspected the 8-and 9-class models and the 8-class model did yield more clinically meaningful classes and hence was chosen. The representation of class membership for baseline variables are presented in Table 5. The eight classes are characterized by:  bacteremic. In addition, this group had the highest frequency of organ dysfunction at admission to the ICU.
3. Community-acquired, sterile sepsis, these patients often suffered from a respiratory tract infection or an abdominal infection.
4. Abdominal sepsis with pathogen detected, the infection was community-acquired.
6. Sepsis with gram-positive bacteria, the infections were community-acquired, often in the respiratory tract or skin and soft tissue infections.
7. Imunosuppressed sepsis, these patients had antibiotic therapy prior to microbial sampling and were yet bacteremic.
90-day mortality for the different classes was compared in a Kaplan-Meier model, Fig. 3.
There was a difference in 90-days mortality between classes (p < 0.01) with the lowest mortality in class 8, Urinary tract infection sepsis and the highest in class 2, Sepsis with lactic acidosis.

Discussion
The main ndings in this study are that rstly, bacteremia is associated with poor outcome, and secondly that a higher percentage than previously reported of ICU patients with sepsis had positive blood cultures and other microbiological samples when analyzed with clinical chart reviewed sepsis diagnosis. Thirdly, blood culture positivity is affected by prior antibiotic treatment.
The high proportion of bacteremic patients, 54% in this study compared to 7-37% in other studies, may at least partially be explained by the manual chart review in the present study (2,3,6,8,(11)(12)(13). Two prior studies classify patients as bacteremic depending on ICD-code, which might lead to a proportion of patients being misclassi ed as culture-negative (9,11). Others de ne sepsis as blood cultures drawn in combination with, for example two Systemic In ammatory Response Syndrome (SIRS) criteria or ICU care, which includes other diagnoses than sepsis as well (11)(12)(13).
We applied strict inclusion criteria of patients with at least blood cultures drawn and ful lling an infection diagnosis and a corresponding sepsis-3 diagnosis. If we would have relied on administrative data like ICD-codes or electronic health record algorithms based on blood cultures for diagnosis, 95 (15%) patients not ful lling infection or sepsis-3 de nitions would have been included. Further, ICD-based strategies would even risk to include the 140 (18%) patients without blood cultures taken. As a poor accuracy of ICD-coding for sepsis is well documented, clinical chart reviews should be considered "gold standard" in sepsis epidemiology studies (20)(21)(22)(23). Results from studies based on automated electronic health record data, should be interpreted with caution even if based on large amounts of data.
Another explanation for the high proportion of bacteremic sepsis might be the high morbidity in this cohort, since bacteremic patients had even higher severity of illness and higher mortality than their non-bacteremic counterparts. The sterile sepsis proportion is similar to the numbers described in a previous prospective study on patients with septic shock where 2651 patients (31%) had sterile sepsis (10). We also included other microbiological samples than culture, although they constituted only a small proportion of the pathogen-detected nonbacteremic sepsis group.
Sepsis is a highly heterogenous condition and different foci of infection have both different mortalities as well as different diagnostic yield of cultures and other microbiological analyses. In the present study propensity score match was used to reduce baseline differences between the groups and to estimate differences in morbidity and mortality with minimal bias.
Bacteremic patients demonstrated higher mortality rate than controls in the present study.
Previous studies have resulted in evidence both for and against bacteremia being associated with higher mortality (6,(24)(25)(26)(27)(28). In a large, prospective study by Phua et al mortality was not higher among culture-positive patients in a multivariate analysis and Gupta et al found higher mortality in culture-negatives, however antibiotic therapy preceding culture sampling was not included in the models (2,9). Nannan Panday et al took prior antibiotic therapy into account when retrospectively analyzing a prospectively gathered cohort, and found higher mortality among bacteremic patients (6). We demonstrate that preceding antibiotic therapy is a confounder affecting mortality in nonbacteremic patients. Possibly, a proportion of non-bacteremic sepsis might be bacteremic but without growth in the blood cultures due to antibiotic therapy preceding culture sampling.
Higher mortality in bacteremic sepsis and in non-bacteremic sepsis with prior antibiotic treatment can also be indicative of bacterial load in blood being associated with sepsis severity, which previously has been demonstrated for isolated pathogens (29)(30)(31)(32).
Still, 30% of the patients had sterile sepsis, i.e. negative in all microbiology samples, with a mortality of 44%. With the high incidence of sepsis and the emerging antimicrobial resistance, sterile sepsis is a substantial cause of morbidity which needs to be examined further.
Sterile sepsis has been speculated to depend on misdiagnosis of other conditions, preceding antibiotic therapy, insu cient culture sampling, handling or culture techniques (6). Our results suggest sterile and non-bacteremic sepsis to partially depend on prior antibiotic therapy. The proportion of sterile sepsis patients decreased from 43% with prior antibiotic therapy to 22% sterile sepsis patients without prior antibiotic therapy, and there was a similar decrease from 63% bacteremic patients without prior antibiotic therapy to 37% bacteremic sepsis patients with prior antibiotic therapy. Thus, antibiotic therapy seems to be a predictor for culture-negative sepsis. This is in contrast to Previsdomini et al, although they also noticed this trend but was possibly limited by a smaller sample size (13).
The LCA offers clinical subphenotypes in a classi cation, that might not be identi ed and its impact might not be tested assuming accepted standards. Neither the site nor the microbiology alone distinguished the classes, yet the combinations together with where the infection was acquired, immunosuppression and lactic acidosis were important for class distinction but also for outcome. This nding is in accordance with the propensity score analysis. When de ning subphenotypes in sepsis, pathogen detection in microbial samples seems to have a high impact on probability of belonging to a class. This has previously been demonstrated for septic shock, while it was not a variable in a LCA used for ARDS and might have an impact in staging models like the PIRO system (predisposition, insult, response, organ dysfunction) (14,15,33).
The strengths of this study are the considering of the effect of antibiotic therapy prior to collection of microbiological samples, the inclusion of other microbial samples than cultures (e.g. PCR) and the data on and the high number of microbial samples collected. Further, the results do not solely rely on administrative or microbial data. All infection diagnoses and all data from microbial analysis have been reviewed by an infectious disease specialist. The proportion sterile sepsis might be underestimated since patients without an identi ed pathogen are less likely to obtain an infection diagnosis.
The major weakness of this study is the retrospective design. As microbiological samples were ordered as part of clinical workup, insu cient culture sampling might contribute to the microbiology negative cohorts. Fewer samples were drawn from blood, urine and wounds for microbiology-negative patients and fewer respiratory tract samples were withdrawn from bacteremic patients, although when cultures were compared to presumed infectious foci, there were no signi cant differences in ratio. Also, the handling of microbiological samples and laboratory techniques were part of clinical practice and out of study control. Other weaknesses of the study are the relatively small size and the single center conduct. The classes created by the LCA were created out of, and limited to observable characteristics of the variables entered.

Conclusions
In summary, bacteremia as well as preceding antibiotic treatment in non-bacteremic patients are related to poor outcome. Bacteremia is more common than previously described in sepsis, when a clinical chart review is used as gold-standard. A substantial portion of sepsis patients that remain microbiology-negative cannot be attributed to misdiagnosis or preceding antibiotic treatment. For reducing population heterogeneity and improve the outcome of trials and treatment for sepsis, microbiological-negativity is an important factor of a subphenotype. The study was approved by the Regional Ethical Review Boar, decision number 2015/285. The Regional Ethics Review Board waived the requirement for informed consent.