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Critical Care and Resuscitation: Original Clinical Research Report

Culture-Negative and Culture-Positive Sepsis: A Comparison of Characteristics and Outcomes

Sigakis, Matthew J. G. MD*; Jewell, Elizabeth MS*; Maile, Michael D. MD, MS*; Cinti, Sandro K. MD; Bateman, Brian T. MD, MSc; Engoren, Milo MD*

Author Information
doi: 10.1213/ANE.0000000000004072
  • Free

Abstract

KEY POINTS

  • Question: Are there differences in characteristics or outcomes between culture-positive and culture-negative patients, and does sepsis definition used impact the results?
  • Findings: We found that (1) patients with sepsis have similar characteristics regardless of culture status; (2) culture negativity is associated with receipt of antibiotics during the 48 hours preceding presentation; (3) after adjusting for disease severity, culture status itself is not associated with mortality; and (4) results were similar using systemic inflammatory response syndrome, Sequential Organ Failure Assessment, and quick Sequential Organ Failure Assessment sepsis definitions.
  • Meaning: Culture-negative and culture-positive sepsis patients demonstrate largely similar characteristics and mortality, and receipt of antibiotics before presentation is associated with culture-negative sepsis.

Sepsis is one of the most common causes of mortality in hospitalized patients.1 In 1992, sepsis was defined on the basis of having systemic inflammatory response syndrome with an identified (or presumed) infection.2 While the risk of mortality increases with severity of systemic inflammatory response syndrome, a large portion of patients (30%–60%) fail to demonstrate a culture-proven source of infection (culture-negative sepsis).3–10 More recently, a third definition of sepsis (Sepsis-3) required a change in Sequential Organ Failure Assessment score of ≥2 in the setting of suspected infection with the emphasis on identification of patients with higher risk of in-hospital mortality.11,12

A few small studies suggest that mortality is not impacted by identification of an infective pathogen and that many clinical characteristics are similar between patients with or without microbiologically documented infection.4–9 However, these studies were limited by only studying patients with septic shock,6,9 patients with acute respiratory distress syndrome,7 emergency department patients,4 or patient populations >2 decades old that may not reflect current intensive care unit practices.5,8 While most of these studies found few differences in patient characteristics and no difference in survival between culture-positive and culture-negative patients, 2 recent studies reached very different conclusions. A single-center study of 1000 medical intensive care unit patients in Asia found that culture-negative patients had fewer comorbidities and a lower risk of death.6 After controlling for other factors, having a positive culture was not significantly associated with mortality.6 In contrast, a second study utilizing administrative data from the Nationwide Inpatient Sample found that culture-negative patients had a higher burden of comorbidity and higher risk of death.10 Given the contrasting methodology and results, we sought to further evaluate this topic using a large clinical database that contained patient-level data.

The primary objective of this study was to compare the characteristics of culture-positive and culture-negative status in septic patients. The secondary objectives were to determine whether culture status is associated with mortality and to determine whether unique variables are associated with mortality in culture-positive and culture-negative patients separately.

METHODS

Data Source

The institutional review board of the University of Michigan reviewed and approved this retrospective study (HUM00052066) and waived consent. No funding sources were used for this study. All demographic, vital signs, laboratory, and outcomes data were obtained from the University of Michigan Health System’s electronic health record system (Centricity, General Electric, Waukegan, IL).

Study Population

Our study population consisted of all adult patients (≥18 years of age) who presented between January 1, 2007, and May 31, 2014 and developed ≥2 systemic inflammatory response syndrome criteria with suspected source of infection. The original American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference Definition for systemic inflammatory response syndrome was used: temperature <36°C or >38°C, heart rate >90 beats/min, respiratory rate >20 breaths/min or Paco2 <32 mm Hg, or white blood cell count >12,000/mm3, <4000/mm3, or >10% immature (band) forms.3 These data were collected on a broad patient population that included patients from any adult intensive care unit, emergency department, and general care floor.

We defined patients as having a suspected infection if a blood culture was sent, with the onset of infection being the time of culture and sepsis if they met systemic inflammatory response syndrome criteria in the 24-hour window (12 hours before and 12 hours after) surrounding the culture.

To ensure best culture practices, the microbiology laboratory is Clinical Laboratory Improvement Amendments and College of American Pathologists certified. It maintains strict standards for ensuring the correct amount of blood is added to the culture bottles. Bottles with lesser amounts are rejected and redrawn. Blood cultures are ordered when infection is suspected by house officers, nurse practitioners, or physician assistants based on vital signs, physical examination (eg, wound appearance, productive cough), and clinical history (eg, recent surgery, comorbidities placing the patient at risk for infections).

For determining vital signs at onset of infection, we used the vital signs closest to the culture within a 6-hour window (3 before to 3 after) of cultures. Similarly, for determining laboratory values at the time of suspected infection, we used values closest to the time of blood culture, 6 hours before or 6 hours after (12-hour window) presentation.

To identify culture status, we evaluated whether the index blood sample obtained subsequently became positive at any time in the future. We also included all other samples (urine, wound, respiratory, or additional blood) taken during the 24 hours before and after index blood culture and determined culture results. Patients who had any positive culture were referred to as “culture positive.” Patients who did not have a positive index blood culture and had no positive culture from any sample taken within 24 hours before and after the index culture were deemed “culture negative.” We reviewed the medical records of 20 culture-negative patients to confirm that they were actually culture negative.

To examine the liberality of obtaining blood cultures, that is, having a too-low threshold leading to excessive cases of culture-negative sepsis, we conducted a post hoc analysis of a random sample of hospital adult admissions (40% of all admissions) weighted to match the temporal distribution of patients in the study. We used the RAND function (Excel; Microsoft, Redmond, WA) to generate a random sample of 10% of the days between January 1, 2007, and May 31, 2014, with the probability of a date being selected proportional to the number of patients in our database who had sepsis develop on that day. This generated a population of patients hospitalized on that day (40% of all admissions, because most admitted patients were hospitalized for several days). We then determined which patients had systemic inflammatory response syndrome and which of the patients with systemic inflammatory response syndrome had blood cultures obtained while they had systemic inflammatory response syndrome.

Sensitivity Analyses

Because we selected a narrow window of time surrounding index culture, we wished to determine the impact of including prior and subsequent infections in our dataset. Thus, we performed 3 sensitivity analyses by including patients with positive cultures: (1) only before presentation (>24 hours before blood cultures); (2) only subsequent to presentation (>24 hours after cultures until hospital discharge); and (3) those with both. We also performed a subgroup analysis of patients with septic shock, defined as requiring a vasopressor or inotrope at the time of presentation.

Finally, we evaluated whether our results would be impacted by choice of sepsis definition. We, therefore, analyzed separately 2 subset databases of patients: (1) patients who met Sepsis-3 criteria (an increase of ≥2 Sequential Organ Failure Assessment score) in the 48 hours before to 24 hours after blood culture for suspected infection and (2) patients who had a quick Sequential Organ Failure Assessment score ≥2).11,12

Statistical Analysis

To compare characteristics by culture status, we used Pearson χ2 tests to compare categorical variables, Student t tests to compare normally distributed continuous variables, and Mann-Whitney U tests to compare nonparametric continuous variables. Because patients had varying collections of laboratory tests and vital signs and these missing data were missing not at random but were obtained (or not obtained) based on perceived clinical need, we adjusted for missing data by binning these variables. These continuous variables were binned into deciles, and the missing data became an 11th bin and treated as an 11-level categorical variable.13 The first 10 levels maintain the order of the variables. The 11th bin permits inclusion of all patients. The odds ratio for a patient with missing data is calculated using the odds ratio of that particular category representing the missing data. This adjusts for both the presence and absence of a test and the numerical value of the result when obtained. For these variables, the number of patients with available data is listed in parentheses in the relevant tables.

To determine the variables associated with culture status and mortality, we created logistic regression models using Akaike Information Criteria to select the final variables, except culture status and year of culture, which were always included. We used all demographic; Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score scores; vital signs; laboratory values; antibiotic use; transfusions; use of mechanical ventilation, renal replacement therapy, and vasopressors; and culture results (Table 1) as covariates in all regression models. We also used this method to determine variables associated with mortality in culture-negative and culture-positive patients separately.

Table 1.
Table 1.:
Univariate Analysis Comparing Culture-Negative to Culture-Positive Patients

For variable selection in building our logistic regression model, we used stepwise Akaike Information Criteria variable selection to find reduced models as follows. Beginning with the full model, each variable was removed, one at a time, and the Akaike Information Criteria calculated for a model including only the remaining variables. The model with the minimum Akaike Information Criteria was selected and, once again, each variable was removed one at a time, and the model with the minimum Akaike Information Criteria was selected. From here, each remaining variable was removed and the Akaike Information Criteria calculated for the model including the remaining variables, and each already-removed variable was reentered to the model, one at a time, with the Akaike Information Criteria calculated, and the model with the minimum Akaike Information Criteria was selected. This stepwise procedure—removing each remaining variable as well as adding each removed variable and choosing the model with the minimum Akaike Information Criteria—continued until the current model had a lesser Akaike Information Criteria than any of the models removing a remaining variable or reentering a removed variable. Culture status was forced to remain in the model and was not eligible to be removed, no matter what Akaike Information Criteria removing it would produce. We used this model as our reduced model.

Discrimination of the models is presented as C-statistics ± SD. Hosmer–Lemeshow test for goodness of fit and calibration plots were used to assess calibration for each regression.

We used the Bonferroni method to adjust for multiple outcomes. We had 6 analyses for the primary and secondary aims, 5 for the sensitivity analyses, and 3 for septic shock. Hence, the adjusted P values for statistical significance are .008, .010, and .017, respectively. We present both the unadjusted and adjusted P values in a footnote for each table in the results. All analyses were performed using R version 3.2.1 (R Foundation for Statistical Computing, Vienna, Austria).14 This manuscript adheres to the applicable Strengthening The Reporting of Observational Studies in Epidemiology reporting guidelines.

Power Analysis

Recent studies of sepsis have been powered to find a 20% relative reduction in mortality.15,16 For us to have 90% power to detect a 20% difference in mortality of 2.5% (12.5% vs 10.0%) between the culture-positive and culture-negative groups, with α = .05, required 8000 patients (3200 and 4800 in each group). However, after collecting our data, our population was >8000 patients but <3200 in the culture-positive group. We, therefore, performed a post hoc power calculation. Using our actual 16.2% mortality rate, 1105 culture-positive and 9208 culture-negative patients with α = .05, we had 81% power to detect a 20% reduction in mortality.

RESULTS

Of the 10,393 patients who met inclusion criteria (Figure 1), 9288 (89%) were culture negative and 1105 (11%) were culture positive (666 = blood, 432 = urine, 42 = wound, 19 = respiratory; some patients had >1 positive site). By univariate analysis, culture-negative patients were more likely to be younger, male, and to have a lower Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score. Culture-positive patients were more likely to receive transfusion of plasma before presentation. However, the presenting vital signs and laboratory values were fairly similar between culture-negative and culture-positive patients (Table 1).

Figure 1.
Figure 1.:
Study population. A total of 20,522 patients with ≥2 SIRS criteria were identified. Patients with subsequent sepsis episodes during hospitalization (1500) and <18 y of age (3878) were excluded, resulting in 15,144 patients. Then, patients were further excluded if they had grown positive cultures from samples taken 0–48 h before presentation (2888) or beyond 24 h after presentation (1863), resulting in 10,393 patients of whom 9063 were culture negative and 1330 were culture positive. Culture negative = patients who had samples taken during the first 24 h of presentation that did not grow a pathogen. Culture positive = patients who had samples taken during the first 24 h of presentation that did grow a pathogen. SIRS indicates systemic inflammatory response syndrome.

A total of 1333 patients (13%) did not survive to discharge. Patients who survived were more likely to be young, African American, and have a lower Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score (Table 2). Those who died were more likely to be culture positive, have abnormal vital signs and laboratory values, and have received transfusion of plasma and platelets, mechanical ventilation, and renal replacement therapy (Table 2). Patients who died were more likely to have positive cultures (179/1330, 13%) than patients who lived (926/9063, 10%; P < .001).

Table 2.
Table 2.:
Univariate Analysis Comparing In-Hospital Survival to Mortality

After adjustment for other factors using logistic regression, older age, worse vital signs, more abnormal laboratory values, mechanical ventilation, renal replacement therapy, plasma transfusion, and vasopressors at the time of presentation were associated with mortality (Table 3). However, having a positive culture itself was not significantly associated with mortality after adjusting for severity of illness and other factors (odds ratio = 1.01 [95% CI, 0.81–1.26]; P = .945; Bonferroni significance P < .008; Table 3). In addition, the year of culture was included as a covariate in the multivariable analysis but was nonsignificant in the full and Akaike Information Criteria regression models. The model predicting mortality demonstrated very good discrimination (C-statistic, 0.87 ± 0.01) and good calibration with a line close to 45° (Hosmer–Lemeshow P value of <.001; Supplement Digital Content, Figure 1, http://links.lww.com/AA/C743).

Table 3.
Table 3.:
Factors Associated With Mortality by Multivariable Logistic Regression

After adjusting for other factors, we found that older and female patients were more likely to be culture positive, while the use of antibiotics within the preceding 48 hours was associated with culture negativity (Table 4). Higher heart rate and transfusion of plasma before presentation were also significantly associated with culture positivity. Notably, race, Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score, vital signs, and laboratory values were not discriminators between culture-positive and culture-negative sepsis (C-statistic, 0.71 ± 0.01; Hosmer–Lemeshow P value of .924; Supplemental Digital Content 1, Figure 1, http://links.lww.com/AA/C743).

Table 4.
Table 4.:
Factors Associated With Positive Cultures by Multivariable Logistic Regression
Table 5.
Table 5.:
Factors Associated With Mortality by Multivariable Logistic Regression

Culture-positive patients had a longer post-sepsis length of stay (4.2 ± 5.9 vs 3.5 ± 5.1 days; P < .001) and greater mortality (179/1105 [16%] vs 1151/9288 [12%]; P < .001). Vasopressor use, renal replacement therapy, and plasma transfusion within 24 hours before presentation were significantly associated with mortality in culture-negative patients compared to culture-positive patients. Initiation of renal replacement therapy after presentation was significantly associated with mortality in culture-positive patients. Other factors associated with death were similar between culture-negative and culture-positive patients (Table 5). The models predicting mortality in each group showed very good and excellent discrimination (culture-negative C-statistic, 0.87 ± 0.01 and culture-positive C-statistic, 0.92 ± 0.01), respectively, along with good calibration (Supplemental Digital Content 1, Figure 2, http://links.lww.com/AA/C743).

Examination of the Liberality of Obtaining Blood Cultures

Of the 57,415 patients, admitted on average twice in the 7 years, in our 40% random sample of adult hospital patients, 16,156 (28%) had ≥1 systemic inflammatory response syndrome episodes. Of these 16,156 systemic inflammatory response syndrome patients, 6547 (41%) had blood cultures obtained within the 12-hour window of systemic inflammatory response syndrome. Thus, 11% (6547/57,415) of patients had sepsis, or approximately 5.6% of hospital admissions.

Sensitivity Analyses

We performed sensitivity analyses by sequentially reincluding patients who had cultures before or after the initial sepsis episode and found similar results. Culture positivity was not significantly associated with mortality in these sensitivity analyses (adjusted odds ratio = 0.98 [95% CI, 0.81–1.18]; P = .829; 1.01 [95% CI, 0.84–1.21]; P = .913; and 1.05 [95% CI, 0.90–1.22]; P = .562; Bonferroni significance P < .010) for patients with prior infections, subsequent infections, or either, respectively.

Sequential Organ Failure Assessment and Quick Sequential Organ Failure Assessment

Figure 2.
Figure 2.:
SOFA and qSOFA study populations. A total of 10,393 patients with ≥2 SIRS criteria were identified. From this population, patients with SOFA and qSOFA data were identified. We restricted patients to those who had an increase of ≥2 SOFA in the 48 h before to 24 h after blood culture for suspected infection and, separately, qSOFA score ≥2. This resulted in 6572 patients meeting SOFA sepsis criteria and 6770 patients meeting qSOFA sepsis criteria. qSOFA indicates quick Sequential Organ Failure Assessment; SIRS, systemic inflammatory response syndrome; SOFA, Sequential Organ Failure Assessment.

We restricted the database to patients who met Sepsis-3 criteria (an increase of ≥2 Sequential Organ Failure Assessment score) in the 48 hours before to 24 hours after blood culture for suspected infection and, separately, patients with quick Sequential Organ Failure Assessment score ≥2). Of the 6572 patients who met Sequential Organ Failure Assessment criteria (Figure 2), 5875 (89%) were culture negative and 697 (11%) were culture positive. Of the 6770 patients who met quick Sequential Organ Failure Assessment criteria (Figure 2), 6024 (89%) were culture negative and 746 (11%) were culture positive. For in-hospital mortality, 1204 (18.3%) of patients who met Sequential Organ Failure Assessment criteria and 1150 (17.1%) of patients who had >=2 quick Sequential Organ Failure Assessment criteria did not survive to discharge. Similar to the systemic inflammatory response syndrome population, univariate analyses showed that culture-positive patients in both the Sequential Organ Failure Assessment and quick Sequential Organ Failure Assessment populations had greater likelihood of dying, but after multivariable adjustment, culture positivity was not associated with greater risk of death (Supplemental Digital Content 2, Tables 1–10, http://links.lww.com/AA/C744; Supplemental Digital Content 1, Figures 3–8, http://links.lww.com/AA/C743).

Septic Shock

We analyzed the systemic inflammatory response syndrome patient population with septic shock. Of the 1398 patients who presented with septic shock, 1242 (89%) were culture negative and 156 (11%) were culture positive. Culture-positive patients with septic shock had higher Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score (21 ± 8 vs 20 ± 9; P = .035) and mortality rate (46% vs 36%; P = .014) compared to culture-negative patients (Supplemental Digital Content 2, Table 11, http://links.lww.com/AA/C744). After adjusting for other factors, age (adjusted odds ratio = 1.01 [95% CI, 1.002–1.03]; P = .026) and initiation of renal replacement therapy (adjusted odds ratio = 2.04 [95% CI, 1.25–3.34]; P = .004) were associated with culture positivity, while the use of antibiotics within the preceding 48 hours was associated with culture negativity, (C-statistic, 0.56 ± 0.02; Supplemental Digital Content 2, Table 12, http://links.lww.com/AA/C744; Supplemental Digital Content 1, Figure 9, http://links.lww.com/AA/C743).

Eight hundred eighty-one septic shock patients (63%) survived to discharge, and 517 (37%) died. Patients who survived were more likely to be younger and have a lower Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score (Supplemental Digital Content 2, Table 13, http://links.lww.com/AA/C744). Patients who died were more likely to be blood culture positive (72/517 [14%] vs 84/881 [10%]; P = .014), have worse vital signs and laboratory values, and have received transfusion, mechanical ventilation, and renal replacement therapy (Supplemental Digital Content 2, Table 13, http://links.lww.com/AA/C744). After adjustment for other factors using logistic regression, older age, lower oxygen saturation, lower Glasgow Coma Score, more abnormal laboratory values, transfusion of plasma, and renal replacement therapy were associated with mortality. Yet, having a positive culture was not significantly associated with mortality (odds ratio = 1.36 [95% CI, 0.88–2.09]; P = .165; Bonferroni significance P < .017; Supplemental Digital Content 2, Table 14, http://links.lww.com/AA/C744). The model predicting mortality in patients with septic shock demonstrated very good discrimination (C-statistic, 0.84 ± 0.01), along with good calibration (Supplemental Digital Content 1, Figure 9, http://links.lww.com/AA/C743).

We also performed a sensitivity analysis on patients with septic shock restricted to those who also met Sepsis-3 Sequential Organ Failure Assessment and, separately, quick Sequential Organ Failure Assessment criteria. Of the 1396 patients who met Sepsis-3 Sequential Organ Failure Assessment criteria, 1240 (89%) were culture negative and 156 (11%) were culture positive. Of the 1354 patients who met quick Sequential Organ Failure Assessment criteria, 1203 (89%) were culture negative and 151 (11%) were culture positive. Hospital mortality for patients meeting Sepsis-3 Sequential Organ Failure Assessment criteria was 37% (n = 517) and 37% (n = 494) for the patients in septic shock meeting quick Sequential Organ Failure Assessment criteria. Univariate and regression analyses demonstrated largely similar results to our systemic inflammatory response syndrome septic shock patient population (Supplemental Digital Content 2, Tables 15–23, http://links.lww.com/AA/C744; Supplemental Digital Content 1, Figures 10–11, http://links.lww.com/AA/C743).

DISCUSSION

We found that culture-negative and culture-positive patients had similar mortality after correcting for greater severity of illness and other factors. We also found that the clinical picture of laboratory values and vital signs had only fair discrimination between culture-positive and culture-negative patients and that culture-positive and culture-negative patients had mostly similar risk factors for death. The most important predictor of culture negativity was receipt of antibiotics within the preceding 48 hours. These results did not change after restricting patients to an increase in Sequential Organ Failure Assessment score ≥2 and, separately, quick Sequential Organ Failure Assessment score ≥2.

Patients with culture-positive sepsis accounted for 11% of our patient population, a smaller percentage than reported in most previously published studies, which ranged between 40% and 70%.5,7,17–19 This is likely a result of including patients from a broad range of hospital units in our study rather than restricting to the intensive care unit. Furthermore, prior studies included culture results from samples collected before presentation or prospectively beyond 24 hours, and results may be impacted by preexisting or subsequent hospital-acquired infection. A strength of our study is that cultures were restricted to samples taken during the 24-hour window of meeting sepsis criteria, which better isolates the effect of an episode of sepsis. Even when restricting our sepsis population to those who also met Sepsis-3 criteria by Sequential Organ Failure Assessment or quick Sequential Organ Failure Assessment scores, we found a similar rate of positive cultures. This is similar to the rate found in the seminal study by Seymour et al12 establishing Sepsis-3. They found that positive blood cultures occurred in only 4%–8% of the primary cohorts and 5%–19% of encounters in the external datasets. Our blood culture-positive rate of 11% is consistent with these findings.

It is also possible that the higher culture-negative rate in our study represents institutional practices reflecting a more liberal culture strategy or antibiotic administration before obtaining cultures. Furthermore, practice habits may change over the course of the 7 years of this retrospective study. In our analyses, however, year of culture was not a significant covariate in either the culture positive or mortality regression models.

In contrast to one study that demonstrated a step-wise increase in rate of pathogen identification with severity of sepsis—culture-positive rates with sepsis, severe sepsis, and septic shock were 17%, 25%, and 69%, respectively8—we found 11% and 11% for sepsis and septic shock patients, respectively, regardless of the definition of sepsis used. This may be the result of restricting culture analysis to samples obtained during systemic inflammatory response syndrome presentation. Our goal was to analyze sepsis based on what was known to the physician at the time of presentation or within a short time thereafter—similar to the window of time assessed in Symour et al.2 Furthermore, our rate of sepsis, 5.6% of admissions, is similar to a large US study of 409 hospitals by Rhee et al20 that found a 6.0% rate. Given the same rate of sepsis as found by Rhee et al,20 further study is needed to assess the lower culture-positive rate.20

We found that culture-negative patients had a lower Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score compared to culture-positive patients. This may reflect a lower bacterial load or milder biological insult resulting in decreased sensitivity of laboratory culture testing. A negative culture could also be a result of sampling error or testing error (false-negative), but this is rare.21 Negative culture results may also reflect issues unique to the microorganism, viral or fungal origin, noninfectious source of symptoms, or genetic differences. Studies have shown that only about 1% of environmental bacteria are currently culturable,22,23 only half of bacterial species inhabiting the human mouth have been characterized, and the colonic flora is suspected to be mostly unidentified.24,25 Infection by any of these nonculturable organisms would result in culture-negative sepsis. Similar to other studies, as prior antibiotic use was associated with culture-negative sepsis (Tables 1 and 4), antibiotics may have sterilized the cultures.6,26 This suggests that pre-sepsis antibiotics may either sterilize the cultures or select for a nonculturable infection. Another possibility is toxemia with very low grade or intermittent bacteremia. Further study is needed to determine why most septic patients have negative cultures and how best to treat them. Despite these reasons for negative cultures, obtaining cultures are important as, when positive, the sensitivities will affect the class of antibiotic and treatment duration.

Our results demonstrating that culture status was not significant in predicting mortality in both all septic patients and only septic shock patients were similar to many other studies.6,8,9,17–19 In contrast, Gupta et al10 found a higher mortality in culture-negative patients. They used the Nationwide Inpatient Sample and International Classification of Diseases codes to identify hospital-associated infections and deemed patients culture negative when billing records did not include coding for an infectious organism.10 However, the accuracy of International Classification of Diseases coding used to identify sepsis and hospital-associated infection was not evaluated. Other studies have suggested that the use of International Classification of Diseases codes to diagnose severe sepsis has limited accuracy20,27 and low sensitivity for identifying the organism.28,29 In addition, identified infections, comorbidities, and mortality were associated with the entire hospitalization and may be confounded by a previously existing condition or hospital-acquired conditions that occurred after or were not related to sepsis. Unlike our study, actual clinical data and culture results were not used.

Compared to other studies,8,9,17–19 our study demonstrated a much lower rate of hospital mortality—13% overall, 12% for culture-negative, and 16% for culture-positive patients. This may be explained by the lower mean Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score in our study (culture negative 12 ± 8 and culture positive 13 ± 8), inclusion of non–intensive care unit and nonshock patients, and a generalized improvement in sepsis survival since the earlier studies.30 Although culture-negative and culture-positive patients demonstrated similar risk factors for mortality in our study, the mortality that we observed in culture-positive patients is likely attributed to the greater occurrence of risk factors, such as older age and higher Acute Physiology and Chronic Health Evaluation II–Acute Physiology Score. The hospital mortality in our study population was similar to that demonstrated in Seymour et al,12 which reported 4%–17% in the primary cohort and 5%–18% in the external datasets.

While the protective association between survival and pre-sepsis red blood cell transfusion that we found may be a result of increased oxygen-carrying capacity or improvement in intravascular volume, prospective studies showed no improved survival with red blood cell transfusion in intensive care unit and septic shock patients.31–33 Our findings may simply reflect that patients receiving red blood cell transfusion develop systemic inflammatory response syndrome as a result of a transfusion reaction that is not a true infection and therefore are more likely to survive. Further study is needed on this important point.

Our study has several limitations. First, patient and culture data were collected retrospectively; therefore, our findings represent associations only and prospective studies are needed to infer causality. Furthermore, retrospective data collection may be subject to missing data and therefore less accurate than information collected prospectively.34 Second, our study was conducted at a single institution, a large academic medical center, and results may not be generalizable to other settings. However, our study is the largest study using clinical variables comparing the differences between culture-negative and culture-positive septic patients and included patients presenting from a broad clinical setting (intensive care units, emergency department, and general hospital wards). Finally, a systemic inflammatory response syndrome–based definition of sepsis was used to identify the initial patient population, from which further restriction of Sequential Organ Failure Assessment score or quick Sequential Organ Failure Assessment was applied for sensitivity analyses. In doing so, it is possible that we excluded true septic patients who met a Sequential Organ Failure Assessment or quick Sequential Organ Failure Assessment definition but did not meet systemic inflammatory response syndrome criteria definition. However, restricting the data to Sequential Organ Failure Assessment ≥2 or quick Sequential Organ Failure Assessment ≥2 aligns the dataset with the current Sepsis-3 definition. While a new organ dysfunction definition of sepsis has been proposed, it has not been fully accepted by some professional societies,35 and a systemic inflammatory response syndrome–based definition of sepsis is consistent with the Centers for Medicare and Medicaid Services Quality Measure Special Enrollment Period-1: the Early Management Bundle for Severe Sepsis/Septic Shock. Additionally, voluminous literature uses systemic inflammatory response syndrome–based criteria, permitting more generalizability of our results.

As culture-negative sepsis is the most common type of sepsis in both our study and in the case-based study of 409 US hospitals,20 further study is needed to determine the effect of the duration and spectrum (broad versus narrow) of antibiotics in culture-negative patients on outcome.

CONCLUSIONS

While culture status is important for tailoring antibiotics, culture-negative and culture-positive patients with sepsis demonstrate similar characteristics and, after adjusting for severity of illness, similar mortality. The most important factor associated with negative cultures is receipt of antibiotics during the preceding 48 hours. The risk of death in patients suspected of having an infection is most associated with severity of illness. These results did not change when restricting patients to a Sepsis-3 definition.

DISCLOSURES

Name: Matthew J. G. Sigakis, MD.

Contribution: This author helped aggregate and analyze the data and prepare the manuscript.

Name: Elizabeth Jewell, MS.

Contribution: This author helped analyze the data and prepare the manuscript.

Name: Michael D. Maile, MD, MS.

Contribution: This author helped analyze the data and prepare the manuscript.

Name: Sandro K. Cinti, MD.

Contribution: This author helped analyze the data and prepare the manuscript.

Name: Brian T. Bateman, MD, MSc.

Contribution: This author helped analyze the data and prepare the manuscript.

Name: Milo Engoren, MD.

Contribution: This author helped aggregate and analyze the data and prepare the manuscript.

This manuscript was handled by: Avery Tung, MD, FCCM.

REFERENCES

1. Kumar G, Kumar N, Taneja A, et al.; Milwaukee Initiative in Critical Care Outcomes Research (MICCOR) Group of Investigators. Nationwide trends of severe sepsis in the 21st century (2000-2007). Chest. 2011;140:1223–1231.
2. Bone RC, Balk RA, Cerra FB. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest. 1992;101:1644–1655.
3. Kaukonen KM, Bailey M, Pilcher D, Cooper DJ, Bellomo R. Systemic inflammatory response syndrome criteria in defining severe sepsis. N Engl J Med. 2015;372:1629–1638.
4. Armstrong-Briley D, Hozhabri NS, Armstrong K, Puthottile J, Benavides R, Beal S. Comparison of length of stay and outcomes of patients with positive versus negative blood culture results. Proc (Bayl Univ Med Cent). 2015;28:10–13.
5. Peduzzi P, Shatney C, Sheagren J, Sprung C. Predictors of bacteremia and gram-negative bacteremia in patients with sepsis. The Veterans Affairs Systemic Sepsis Cooperative Study Group. Arch Intern Med. 1992;152:529–535.
6. Phua J, Ngerng W, See K, et al. Characteristics and outcomes of culture-negative versus culture-positive severe sepsis. Crit Care. 2013;17:R202.
7. Yang SC, Liao KM, Chen CW, Lin WC. Positive blood culture is not associated with increased mortality in patients with sepsis-induced acute respiratory distress syndrome. Respirology. 2013;18:1210–1216.
8. Rangel-Frausto MS, Pittet D, Costigan M, Hwang T, Davis CS, Wenzel RP. The natural history of the systemic inflammatory response syndrome (SIRS). A prospective study. JAMA. 1995;273:117–123.
9. Brun-Buisson C, Doyon F, Carlet J, et al. Incidence, risk factors, and outcome of severe sepsis and septic shock in adults. A multicenter prospective study in intensive care units. French ICU Group for Severe Sepsis. JAMA. 1995;274:968–974.
10. Gupta S, Sakhuja A, Kumar G, McGrath E, Nanchal RS, Kashani KB. Culture-negative severe sepsis: nationwide trends and outcomes. Chest. 2016;150:1251–1259.
11. Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315:801–810.
12. Seymour CW, Liu VX, Iwashyna TJ, et al. Assessment of clinical criteria for sepsis: for the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315:762–774.
13. Engoren M. Does erythrocyte blood transfusion prevent acute kidney injury? Propensity-matched case control analysis. Anesthesiology. 2010;113:1126–1133.
14. R Development Core Team. R: A Language and Environment for Statistical Computing. 2008Vienna, Austria: R Foundation for Statistical Computing; . Available at: http://www.R-project.org. Accessed October 4, 2016.
15. Mouncey PR, Osborn TM, Power GS, et al.; ProMISe Trial Investigators. Trial of early, goal-directed resuscitation for septic shock. N Engl J Med. 2015;372:1301–1311.
16. Peake SL, Delaney A, Bailey M, et al. Goal-directed resuscitation for patients with early septic shock. N Engl J Med. 2014;371:1496–506.
17. Kumar A, Roberts D, Wood KE, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med. 2006;34:1589–1596.
18. Vincent JL, Sakr Y, Sprung CL, et al.; Sepsis Occurrence in Acutely Ill Patients Investigators. Sepsis in European intensive care units: results of the SOAP study. Crit Care Med. 2006;34:344–353.
19. Kethireddy S, Bilgili B, Sees A, et al.; Cooperative Antimicrobial Therapy of Septic Shock (CATSS) Database Research Group. Culture-negative septic shock compared with culture-positive septic shock: a retrospective cohort study. Crit Care Med. 2018;46:506–512.
20. Rhee C, Dantes R, Epstein L, et al.; CDC Prevention Epicenter Program. Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009-2014. JAMA. 2017;318:1241–1249.
21. Peretz A, Isakovich N, Pastukh N, Koifman A, Glyatman T, Brodsky D. Performance of gram staining on blood cultures flagged negative by an automated blood culture system. Eur J Clin Microbiol Infect Dis. 2015;34:1539–1541.
22. Ward DM, Bateson MM, Weller R, Ruff-Roberts AL. Marshall KC. Ribosomal analysis of microorganisms as they occur in nature. In: Advances in Microbial Ecology. 1992:New York, NY: Plenum Press, 219–286.
23. Amann RI, Ludwig W, Schleifer KH. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev. 1995;59:143–169.
24. Wade W. Unculturable bacteria–the uncharacterized organisms that cause oral infections. J R Soc Med. 2002;95:81–83.
25. Siqueira JF, Rôças IN. As-yet-uncultivated oral bacteria: breadth and association with oral and extra-oral diseases. J Oral Microbiol. 2013;5:21077.
26. de Prost N, Razazi K, Brun-Buisson C. Unrevealing culture-negative severe sepsis. Crit Care. 2013;17:1001.
27. Iwashyna TJ1, Odden A, Rohde J, et al. Identifying patients with severe sepsis using administrative claims: patient-level validation of the angus implementation of the international consensus conference definition of severe sepsis. Med Care. 2014;52:e39–e43.
28. Jones G, Taright N, Boelle PY, et al. Accuracy of ICD-10 codes for surveillance of Clostridium difficile infections, France. Emerg Infect Dis. 2012;18:979–981.
29. Guevara RE, Butler JC, Marston BJ, Plouffe JF, File TM Jr, Breiman RF. Accuracy of ICD-9-CM codes in detecting community-acquired pneumococcal pneumonia for incidence and vaccine efficacy studies. Am J Epidemiol. 1999;149:282–289.
30. Kaukonen KM, Bailey M, Suzuki S, Pilcher D, Bellomo R. Mortality related to severe sepsis and septic shock among critically ill patients in Australia and New Zealand, 2000-2012. JAMA. 2014;311:1308–1316.
31. Sadaka F, Aggu-Sher R, Krause K, O’Brien J, Armbrecht ES, Taylor RW. The effect of red blood cell transfusion on tissue oxygenation and microcirculation in severe septic patients. Ann Intensive Care. 2011;1:46.
32. Hébert PC, Wells G, Blajchman MA, et al. A multicenter, randomized, controlled clinical trial of transfusion requirements in critical care. Transfusion requirements in critical care investigators, Canadian Critical Care Trials Group. N Engl J Med. 1999;340:409–417.
33. Holst LB, Haase N, Wetterslev J, et al.; TRISS Trial Group; Scandinavian Critical Care Trials Group. Lower versus higher hemoglobin threshold for transfusion in septic shock. N Engl J Med. 2014;371:1381–1391.
34. Sedgwick P. Retrospective cohort studies: advantages and disadvantages. BMJ. 2014;348:g1072.
35. Simpson SQ. New sepsis criteria: a change we should not make. Chest. 2016;149:1117–1118.
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