关键点 español English 问题
在社区发作性脓血病中,抗生素耐药性的发生率如何?接受经验性广谱抗生素是否会带来风险?
结果
这项队列研究涉及美国 104 所医院收治的 17,430 例血培养阳性脓毒病成人患者。研究发现,67.0% 的患者接受了经验性广谱抗生素,但只有 13.6% 的患者分离出了耐药的革兰氏阳性菌,只有 13.2% 的患者分离出了耐药的革兰氏阴性菌。经过详细的风险调整后,治疗不足(未覆盖菌群)和治疗过度(已确定但未分离耐药箘)均与较高的死亡率相关。
意义
在这项研究中,广谱抗生素经常用于没有耐药菌的社区发作性脓毒病患者,而这些疗法与不良结局存在相关性。
Importance
Broad-spectrum antibiotics are recommended for all patients with suspected sepsis to minimize the risk of undertreatment. However, little is known regarding the net prevalence of antibiotic-resistant pathogens across all patients with community-onset sepsis or the outcomes associated with unnecessarily broad empiric treatment.
Objective
To elucidate the epidemiology of antibiotic-resistant pathogens and the outcomes associated with both undertreatment and overtreatment in patients with culture-positive community-onset sepsis.
Design, Setting, and Participants
This cohort study included 17 430 adults admitted to 104 US hospitals between January 2009 and December 2015 with sepsis and positive clinical cultures within 2 days of admission. Data analysis took place from January 2018 to December 2019.
Exposures
Inadequate empiric antibiotic therapy (ie, ≥1 pathogen nonsusceptible to all antibiotics administered on the first or second day of treatment) and unnecessarily broad empiric therapy (ie, active against methicillin-resistant Staphylococcus aureus [MRSA]; vancomycin-resistant Enterococcus [VRE]; ceftriaxone-resistant gram-negative [CTX-RO] organisms, including Pseudomonas aeruginosa; or extended-spectrum β-lactamase [ESBL] gram-negative organisms when none of these were isolated).
Main Outcomes and Measures
Prevalence and empiric treatment rates for antibiotic-resistant organisms and associations of inadequate and unnecessarily broad empiric therapy with in-hospital mortality were assessed, adjusting for baseline characteristics and severity of illness.
Results
Of 17 430 patients with culture-positive community-onset sepsis (median [interquartile range] age, 69 [57-81] years; 9737 [55.9%] women), 2865 (16.4%) died in the hospital. The most common culture-positive sites were urine (9077 [52.1%]), blood (6968 [40.0%]), and the respiratory tract (2912 [16.7%]). The most common pathogens were Escherichia coli (5873 [33.7%]), S aureus (3706 [21.3%]), and Streptococcus species (2361 [13.5%]). Among 15 183 cases in which all antibiotic-pathogen susceptibility combinations could be calculated, most (12 398 [81.6%]) received adequate empiric antibiotics. Empiric therapy targeted resistant organisms in 11 683 of 17 430 cases (67.0%; primarily vancomycin and anti-Pseudomonal β-lactams), but resistant organisms were uncommon (MRSA, 2045 [11.7%]; CTX-RO, 2278 [13.1%]; VRE, 360 [2.1%]; ESBLs, 133 [0.8%]). The net prevalence for at least 1 resistant gram-positive organism (ie, MRSA or VRE) was 13.6% (2376 patients), and for at least 1 resistant gram-negative organism (ie, CTX-RO, ESBL, or CRE), it was 13.2% (2297 patients). Both inadequate and unnecessarily broad empiric antibiotics were associated with higher mortality after detailed risk adjustment (inadequate empiric antibiotics: odds ratio, 1.19; 95% CI, 1.03-1.37; P = .02; unnecessarily broad empiric antibiotics: odds ratio, 1.22; 95% CI, 1.06-1.40; P = .007).
Conclusions and Relevance
In this study, most patients with community-onset sepsis did not have resistant pathogens, yet broad-spectrum antibiotics were frequently administered. Both inadequate and unnecessarily broad empiric antibiotics were associated with higher mortality. These findings underscore the need for better tests to rapidly identify patients with resistant pathogens and for more judicious use of broad-spectrum antibiotics for empiric sepsis treatment.
Sepsis, the syndrome of life-threatening organ dysfunction complicating severe infection, is a leading cause of death in hospitalized patients.1 Early active antibiotic therapy is associated with better outcomes.2-5 Therefore, national quality measures and international guidelines recommend immediate empiric broad-spectrum antibiotics for all patients with suspected sepsis.6,7
However, it is unclear how many patients presenting with sepsis require coverage for methicillin-resistant Staphylococcus aureus (MRSA), Pseudomonas aeruginosa, and other potentially resistant pathogens. Most existing epidemiologic studies present rates of resistance to selected antimicrobials per pathogen rather than quantifying overall resistance rates across all patients and syndromes associated with sepsis. These data are needed to inform the rational use of antibiotics, given that overuse of broad-spectrum therapy may also confer harm by selecting for antibiotic-resistant bacteria, increasing the risk of adverse events, such as Clostridioides difficile infections, and raising costs.8-12 Overtreatment has also been associated with higher mortality rates in some populations.13-15 Therefore, we sought to elucidate the epidemiology of antibiotic-resistant pathogens in patients with culture-positive community-onset sepsis and the risks of both inadequate and unnecessarily broad antibiotic treatments in US hospitals.
Study Design, Data Source, and Population
We conducted a retrospective cohort study using Cerner HealthFacts, a deidentified data set that includes detailed electronic clinical data from diverse US hospitals.16-20 We included all patients aged at least 20 years who were admitted between January 2009 and September 2015, excluding those with missing discharge dispositions or International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) rather than ICD-9-CM codes.16 Data analysis took place between January 2018 and December 2019 and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.21 This study was approved by the institutional review board at Harvard Pilgrim Health Care Institute with a waiver of informed consent given that the patients in this study had high mortality rates, making collection of consent infeasible.
Identifying Patients With Culture-Positive Sepsis
We identified sepsis hospitalizations using the US Centers for Disease Control and Prevention Adult Sepsis Event surveillance criteria, which defines sepsis as concurrent evidence of presumed serious infection (ie, blood culture order and ≥4 consecutive days of new antibiotics) and organ dysfunction (ie, initiation of vasopressors or mechanical ventilation, lactate level ≥2.0 mmol/L [to convert to milligram per deciliter, divide by 0.111], doubling in baseline creatinine level or ≥50% decrease in estimated glomerular filtration rate, doubling in total bilirubin level to ≥2.0 mg/dL [to convert to micromoles per liter, multiply by 17.104], or ≥50% decrease in platelet count to <100 × 103/μL [to convert to × 109/L, multiply by 1.0]).22 We focused on culture-positive community-onset sepsis, as defined by a blood culture draw, first antibiotic administration, organ dysfunction, and clinical cultures obtained and subsequently testing positive for potentially pathogenic organisms, all on hospital day 2 or earlier. We excluded culture-negative patients because of the difficulty determining antibiotic appropriateness in this population using electronic data alone. We further excluded patients transferred from hospitals, rehabilitation or long-term facilities, and hospice as well as patients with hospital-onset sepsis because the epidemiology, antibiotic resistance patterns, and recommended treatments differ substantially in health care–acquired vs community-acquired infections.23-25 Infectious syndromes were classified using ICD-9-CM discharge codes (eAppendix 1 in the Supplement).26
Culture Sites and Pathogens of Interest
We included clinical cultures from the following anatomic sites: blood, respiratory, urine, deep tissue, central nervous system fluid, body fluid, and superficial tissue. We focused on pathogens commonly encountered in routine practice. Gram-negative organisms included Acinetobacter species, Citrobacter species, Enterobacter species, Escherichia coli, Klebsiella species, Proteus species, P aeruginosa, and Serratia species. Gram-positive organisms included S aureus, Streptococcus species, and Enterococcus species. Surveillance cultures and cultures positive for other organisms within the first 2 days of hospitalization were excluded, including coagulase-negative Staphylococcus species (because it can be difficult to distinguish contaminants vs true infections) and Enterococcus species isolated from respiratory samples.
We assessed the prevalence of the following resistant organisms: MRSA, vancomycin-resistant Enterococcus (VRE), extended spectrum β-lactamase (ESBL) gram-negative organisms (ie, resistant to all β-lactams except carbapenems), carbapenem-resistant Enterobacteriaceae (CRE; defined as resistant to imipenem, meropenem, doripenem, or ertapenem), and ceftriaxone-resistant gram negatives (CTX-RO; including P aeruginosa and ESBLs). We grouped P aeruginosa with other CTX-RO organisms because they share the need for treatment with β-lactams with anti-Pseudomonal coverage, which are an important class of broad-spectrum antibiotics.
Antibiotic Susceptibilities and Adequacy of Therapy
We assessed each potential antibiotic-pathogen combination using antibiotic susceptibilities derived from in vitro reports generated by each institution. Intermediate susceptibilities were treated as nonsusceptible. In some cases, susceptibilities to specific antibiotics administered were not explicitly listed but could be assumed using knowledge of the spectrum of activity for each antibiotic-pathogen combination. For example, many antibiotics are intrinsically inactive against certain species (eg, ceftriaxone vs P aeruginosa) and are therefore not included in susceptibility reports. Alternatively, a gram-negative organism susceptible to ceftriaxone may not have susceptibilities reported to all higher-generation cephalosporins (ie, cefepime), but these agents can be safely used. We created rules to impute susceptibilities for each antibiotic-pathogen combination (eAppendix 2 in the Supplement).
We considered patients to have received inadequate empiric therapy if at least 1 pathogen isolated from any clinical culture site was not susceptible to all antibiotics administered on the first and second day of treatment. We considered patients to have received unnecessarily broad empiric therapy if they received adequate empiric therapy and anti-MRSA antibiotics (ie, vancomycin, linezolid, or daptomycin), anti-VRE antibiotics (ie, linezolid or daptomycin), anti-Pseudomonal β-lactams (ie, ceftazidime, cefepime, piperacillin-tazobactam, aztreonam, imipenem, meropenem, or doripenem), or carbapenems (ie, imipenem, meropenem, doripenem, or ertapenem), but none of the organisms targeted by these antibiotics (ie, MRSA, VRE, CTX-RO, or ESBL) were recovered. We did not consider CRE in the analysis of unnecessarily broad therapy given the infrequency of empiric CRE treatment.27
We examined associations of both inadequate and unnecessarily broad empiric regimens with in-hospital mortality. The analysis of unnecessarily broad antibiotics was limited to patients who received adequate antibiotics because an empiric regimen would generally not be considered unnecessarily broad if the spectrum was inadequate. Secondary outcomes included hospital-onset acute kidney injury, defined as an increase in creatinine level by at least 0.5 mg/dL (to convert to micrograms per liter, multiply by 1) at any point during hospitalization relative to the initial value on presentation and C difficile infections, which we identified using the ICD-9-CM code 008.45 because C difficile test results were unavailable in our data set.
We fit logistic regression models using generalized estimating equations to account for clustering within hospitals. Model covariates included admission year, hospital characteristics (bed size, region, teaching status), patient demographic characteristics (age, sex, race), total burden of comorbidities (Agency for Healthcare Research and Quality [AHRQ] Elixhauser Comorbidity Index28), microbiologic characteristics (site of positive clinical culture, pathogen, and presence of antibiotic resistance [MRSA, VRE, CTX-RO, ESBL, or CRE]), infectious syndrome (by ICD-9-CM codes), intensive care unit (ICU) care on admission, and physiological markers of severity of illness on admission (number of vasopressors, need for mechanical ventilation, and worst values for temperature, systolic blood pressure, respiratory rate, Glasgow Coma Scale score, serum lactate level, creatinine level, anion gap, total bilirubin level, aspartate aminotransferase level, white blood cell count, hematocrit level, platelet count, and serum albumin level). We used univariate logistic regression to assess associations of covariates with each outcome. Covariates with univariate P < .10 were included in the multivariable models. The 2247 cases (12.9%) in which susceptibility or resistance to all administered antibiotics could not be reliably imputed were excluded from this multivariable analysis (eAppendix 3 in the Supplement).
Multiple imputation was used in our primary analysis to assign values for missing severity-of-illness physiological variables (eAppendix 3 in the Supplement). Several sensitivity analyses were conducted to handle missing data in different ways. First, we imputed all missing severity-of-illness covariates with median values. Second, we limited analyses to patients with nonmissing vital signs (ie, temperature, blood pressure, and respiratory rate) and used multiple imputation to account for other missing covariates. Third, we limited analyses to patients with complete data for all covariates.
For our assessment of inadequate antibiotic therapy and mortality, we conducted an additional sensitivity analysis restricted to positive blood cultures because these organisms unequivocally represent true pathogens, whereas organisms isolated from most other sites can sometimes be colonizers rather than pathogens. We also conducted subgroup analyses restricted to patients with septic shock, as defined by the need for vasopressors on admission.
All tests of significance used a 2-sided P < .05. Analyses were conducted using SAS version 9.4 (SAS Institute).
Patient Characteristics and Pathogen Epidemiology
The cohort included 17 430 patients with culture-positive community-onset sepsis (median [interquartile range {IQR}] age, 69 [57-81] years; 9737 [55.9%] women) (Figure 1). Of these, 5609 (32.2%) had septic shock requiring vasopressors, 8001 (45.9%) were admitted to the ICU, and 2865 (16.4%) died in the hospital (Table 1). Patients with septic shock had higher mortality than those without shock (1733 of 5345 [32.4%] vs 1137 of 12 098 [9.4%]; P < .001).
Urinary tract infection was the most common infectious diagnosis (8515 [48.9%]), followed by pulmonary (5728 [32.9%]), intra-abdominal (2373 [13.6%]), and skin or soft tissue (1787 [10.3%]) infections. The most common positive culture sites were urine (9077 [52.1%]), blood (6968 [40.0%]), and the respiratory tract (2912, [16.7%]). The top pathogens were E coli (5873 [33.7%]), S aureus (3706 [21.3%]), Streptococcus species (2361 [13.5%]), Klebsiella (2254 [12.9%]), and Enterococcus (1928 [11.1%]) (Figure 2). Empiric therapy targeted resistant organisms in 11 683 of 17 430 cases (67.0%). Drug-resistant pathogens were relatively uncommon (MRSA, 2045 [11.7%]; CTX-RO, 2278 [13.1%], of whom 1510 patients [66.3%] had P aeruginosa; VRE, 360 [2.1%]; ESBLs, 133 [0.8%]; and CRE, 83 [0.5%]). The net prevalence of at least 1 resistant gram-positive organism (ie MRSA or VRE) was 13.6% (2376 patients); at least 1 resistant gram negative organism (ie, CTX-RO, ESBL, CRE), 13.2% (2297 patients); and any of these organisms, 25.7% (4474 patients). The prevalence of pathogens across blood, respiratory, and urine cultures is shown in eFigure 1 in the Supplement.
The characteristics of patients with vs without resistant organisms (4474 [25.7%] vs 12 956 [74.3%]) are shown in Table 1. Patients with resistant organisms were more likely to have more comorbidities (median [IQR] AHRQ Elixhauser Comorbidity Index score, 12 [4-20] vs 11 [3-19]; P < .001), to have a pulmonary infection (1851 [41.4%] vs 3877 [29.9%]; P < .001), to have positive respiratory cultures (1339 [29.9%] vs 1573 [12.1%]; P < .001), to require vasopressors (1612 [36.0%] vs 3997 [30.9%]; P < .001) or mechanical ventilation (1264 [28.3%] vs 2489 [19.2%]; P < .001), to require ICU admission (2243 [50.1%] vs 5758 [44.4%]; P < .001), and to die in the hospital (888 [19.9%] vs 1977 [15.3%]; crude odds ratio [OR], 1.38; 95% CI, 1.26-1.50).
The prevalence of resistant organisms was higher in the 5609 patients with septic shock vs 11 821 patients without shock (1612 [28.7%] vs 2862 [24.2%]; P < .001), including higher rates of MRSA (785 [14.0%] vs 1260 [10.7%]; P < .001) and CTX-RO (801 [14.3%] vs 1477 [12.5%]; P = .001) but not ESBL (49 [0.9%] vs 84 [0.7%]; P = .25), VRE (117 [2.1%] vs 243 [2.1%]; P = .90), or CRE (52 [0.9%] vs 31 [0.3%]; P = .31) (eFigure 2 in the Supplement).
Empiric Antibiotics and Rates of Overtreatment for Resistant Pathogens
Vancomycin was the most commonly prescribed empiric antibiotic (7262 [41.7%]), followed by an anti-Pseudomonal fluoroquinolone (ciprofloxacin or levofloxacin, 6997 [40.1%]), piperacillin-tazobactam (5911 [33.9%]), ceftriaxone (5187 [29.8%]), and third- or fourth-generation cephalosporins (ceftazidime or cefepime, 2300 [13.2%]) (eFigure 3 in the Supplement). Anti-MRSA treatment (ie, vancomycin, linezolid, or daptomycin) was given to 7936 of 17 430 patients (45.5%), of whom 1310 (16.5%) had positive cultures for MRSA. Anti-Pseudomonal β-lactams were given to 9031 patients (51.8%), of whom 1367 (15.1%) had positive cultures for CTX-ROs. Anti-VRE treatment was given to 1040 patients (6.0%), of whom 58 (5.6%) had positive cultures for VRE. Carbapenems were given to 1408 patients (8.1%), of whom 19 (1.4%) had positive cultures for ESBL. Overall, 11 797 patients (67.7%) received anti-MRSA, anti-Pseudomonal, anti-VRE, and/or anti-ESBL treatment, of whom 3447 (29.2%) had at least 1 of these organisms isolated (Figure 3). In addition, 4090 patients (23.5%) received double coverage for gram-negative organisms; 3260 patients (8.7%) received anti-Pseudomonal β-lactams with ciprofloxacin or levofloxacin, and 830 patients (4.8%) received anti-Pseudomonal β-lactams with amikacin, gentamicin, or tobramycin.
Associations Between Empiric Therapy, Antibiotic Resistance, and Outcomes
The crude and adjusted associations between empiric therapy patterns and outcomes are summarized in Table 2. Empiric antibiotics were active against all isolated pathogens in 12 398 of 15 183 (81.6%) sepsis cases in which all antibiotic-pathogen susceptibility combinations could be calculated. Compared with 12 398 patients who received adequate therapy, 2785 patients who received inadequate empiric antibiotic therapy were older (median [IQR] age, 71 [60-83] years vs 68 [56-80] years; P < .001) and had a higher burden of comorbidities (median [IQR] AHRQ Elixhauser Comorbidity Index score, 13 [5-21] vs 11 [2-19]; P < .001), but the groups had similar rates of organ dysfunction (eg, renal dysfunction: 1480 [53.1%] vs 6465 [52.2%]; P = .34), ICU admission (1248 [44.8%] vs 5710 [46.1%]; P = .23), and in-hospital mortality (488 [17.5%] vs 2011 [16.3%]; P = .09) (eTable 1 in the Supplement). However, on multivariable analysis, inadequate therapy was significantly associated with higher mortality (adjusted OR, 1.19; 95% CI, 1.03-1.37; P = .02).
Inadequate therapy was much more likely in patients with resistant pathogens (MRSA, VRE, CTX-RO, ESBL, or CRE) vs nonresistant pathogens (1544 of 3811 [40.5%] vs 1241 of 11 372 [10.9%]; P < .001). Although patients with antibiotic-resistant organisms had higher crude hospital mortality rates, there was no difference after adjusting for baseline characteristics, severity of illness, and adequacy of therapy (adjusted OR, 1.04; 95% CI, 0.83-1.30; P = .75). There was also no association between antibiotic-resistant organisms and mortality when only considering positive blood cultures (adjusted OR, 1.10; 95% CI, 0.82-1.46; P = .54).
Inadequate antibiotic therapy was not significantly associated with hospital death in the subgroup of patients with septic shock (OR, 1.10; 95% CI, 0.87-1.38; P = .44), but there was an association between inadequate antibiotics and hospital death when considering patients with sepsis who had positive blood cultures alone (adjusted OR, 1.40; 95% CI, 1.07-1.84; P = .02). The risk of C difficile was similar in patients who received inadequate vs adequate therapy (adjusted OR 1.19; 95% CI, 0.98-1.45; P = .09) as was the risk of hospital-onset acute kidney injury (adjusted OR, 1.02; 95% CI, 0.90-1.16; P = .72).
Patients who received adequate but unnecessarily broad empiric antibiotics were younger and had a similar burden of comorbidities compared with those who did not receive unnecessarily broad therapy (median [IQR] age, 67 [55-79] years vs 71 [58-82] years; P < .001; median [IQR] AHRQ Elixhauser Comorbidity Index score, 11 [2-19] vs 11 [3-18]; P = .11) but were more severely ill on admission, with higher rates of vasopressor use (3310 [39.4%] vs 858 [21.5%]; P < .001), mechanical ventilation (1987 [23.6%] vs 601 [15.1%]; P < .001), ICU care (4276 [50.9%] vs 1434 [35.9%]; P < .001), and crude mortality (1575 [18.7%] vs 436 [10.9%]; P < .001) (eTable 2 in the Supplement). The association between unnecessarily broad empiric antibiotics and higher mortality persisted after risk adjustment (adjusted OR, 1.22; 95% CI, 1.06-1.49; P = .007). On subgroup analysis, the association between unnecessarily broad therapy and higher mortality was only seen in patients with sepsis and without shock (adjusted OR, 1.33; 95% CI, 1.09-1.60; P = .005) but not in patients with septic shock (adjusted OR, 1.12; 95% CI, 0.90-1.40; P = .32). The risk of C difficile among patients with sepsis was higher with unnecessarily broad therapy (adjusted OR, 1.26; 95% CI, 1.01-1.57; P = .04), but there was no association between unnecessarily broad therapy and hospital-onset acute kidney injury (adjusted OR, 1.12; 95% CI, 1.00-1.26; P = .05). The median (IQR) duration of treatment in the unnecessarily broad group was 3 (1-5) days for vancomycin, 4 (2-6) days for anti-Pseudomonal β-lactams, and 4 (2-6) days for carbapenems.
The full univariate and multivariable models for mortality are shown in eTable 3 in the Supplement. The distribution of severity-of-illness covariates is shown in eTable 4 in the Supplement. The frequencies of missing data within the first 2 days of hospitalization are shown in eFigure 4 in the Supplement and were highest among laboratory data for lactate levels (7123 of 17 430 [40.9%]) but low for general chemistry (140 [0.8%]) and complete blood cell count variables (376 [2.2%]); vital sign data was missing in as many of 8309 cases (47.8%), and Glasgow Coma Scale scores were missing in 8872 cases (50.9%). Sensitivity analyses handling missing data in different ways, including limiting to patients with nonmissing data, yielded similar point estimates as the primary analysis (eTable 5 in the Supplement).
Prior studies have estimated the national and global burden of antimicrobial resistance,29,30 but our study is among the first to estimate the net prevalence of antibiotic resistance across all culture sites in patients with culture-positive community-onset sepsis. We found that approximately 1 in 8 patients had resistant gram-positive organisms (primarily MRSA and rarely VRE) and 1 in 8 had resistant gram-negative organisms (primarily ceftriaxone-resistant gram-negative organisms and rarely ESBL or CRE). More than two-thirds of patients received broad-spectrum therapy directed at resistant organisms, but MRSA was only isolated in 1 in 6 patients treated with vancomycin or linezolid, P aeruginosa or other ceftriaxone-resistant gram-negative organisms in 1 in 6 patients treated with anti-Pseudomonal agents, VRE in 1 in 16 patients treated with linezolid or daptomycin, and ESBLs in 1 in 70 patients treated with carbapenems. Both inadequate and unnecessarily broad empiric therapy were associated with higher mortality after detailed risk adjustment.
Our findings almost certainly overestimate the prevalence of resistant pathogens across the entire spectrum of patients treated for possible sepsis given the following: (1) we limited our analysis to bacterial, culture-positive sepsis, and between 30% and 50% of all patients with sepsis are culture negative31,32; (2) viruses are often implicated in severe pneumonia (the most common cause of sepsis), and (3) there are many noninfectious mimickers of sepsis that are treated as sepsis.33,34 All told, the net fraction of patients with sepsis who would benefit from broad-spectrum therapy, including agents active against both MRSA and Pseudomonas, is small. This may be an acceptable trade-off given the increased risk of death associated with inadequate therapy, but it underscores the need for rapid tests to more efficiently identify the small fraction of patients who truly need broad spectrum therapy.35 Alternatively, predictive models may soon allow clinicians to effectively select and tailor antibiotic regimens at the point of care.36-39
In our cohort, inadequate therapy was associated with a 20% to 40% higher odds of death depending on whether all cultures or only blood cultures were analyzed. Our estimates are in the range of the results of a meta-analysis of 48 studies that reported a pooled odds ratio of 1.6 for death associated with inadequate therapy in patients with sepsis.40 We also found that patients with antibiotic-resistant pathogens received inadequate empiric therapy 4 times as often compared with patients with nonresistant organisms; patients with resistant pathogens who received inadequate therapy had higher mortality rates. However, we did not find an association between antibiotic-resistant organisms and mortality after adjusting for baseline and clinical characteristics as well as adequacy of empiric antibiotics. This suggests that the higher crude mortality rates in patients with resistant organisms could be mediated by their higher comorbidity burden, greater severity of illness, and inadequate antibiotic therapy rather than intrinsic virulence of resistant organisms.41-43
While clinicians, guidelines, and policies understandably emphasize broad-spectrum antibiotics to ensure adequate empiric treatment,44 our findings suggest that the risk of inadequate therapy needs to be weighed against the risks of unnecessarily broad empiric antibiotics. Among patients who received adequate therapy, overtreatment was associated with a 20% increase in the odds of death. Other studies have also reported that more aggressive antibiotic regimens may be associated with higher mortality rates in critically ill patients.13-15 In our cohort, we found an association between overtreatment and mortality only among patients without shock. This may be because the morbidity of acute severe illness in patients with septic shock outweighs the possible morbidity of excessively broad antibiotic therapy, whereas in less critically ill patients, the morbidity of excessively broad antibiotics may be more significant. Another possibility is residual confounding among patients without shock because of the wide array of infections and organ dysfunction in this group that may make it more difficult to adequately adjust for all gradations in illness. The possibility of residual confounding is supported by the observation that more severely ill patients were more likely to receive broad-spectrum antibiotics.
There are several other potential explanations for the association between overtreatment and higher mortality. As many as 20% of hospitalized patients who receive antibiotics experience adverse effects.45 Even a single dose of antibiotics can increase the risk of C difficile; this risk is higher with broad- vs narrow-spectrum antibiotics.46,47 We found unnecessarily broad empiric therapy was associated with a 26% increased risk of C difficile infection in our study. Unnecessary antibiotics may also increase the risk of acute kidney injury.48 We observed a trend toward more acute kidney injury in patients treated with unnecessarily broad antibiotics. In particular, the combination of vancomycin and piperacillin-tazobactam, a common regimen during the study period, is associated with renal toxicity.49 Broad-spectrum antibiotics also disrupt the gut microbiome, an increasingly recognized modulator of the immune system and outcomes in sepsis.50,51 Lastly, broad-spectrum antibiotics may increase the risk of resistant hospital-acquired infections.
Our study has important limitations. First, we used a convenience sample of hospitals, which may limit generalizability. Antibiotic resistance rates vary substantially by region, hospital, and even within a facility. Second, our data did not allow us to calculate the time to antibiotics on the scale of hours, an important predictor of patient outcomes in some studies.2,4 Third, our primary analysis included pathogens isolated from all clinical cultures, but not all of these may be pathogenic. However, an analysis using only organisms isolated from blood demonstrated similar results with respect to the association between inadequate antibiotics and mortality. Fourth, we excluded patients with atypical pathogens owing to the complexity of determining adequate vs excessive treatment in this population. Fifth, C difficile assay results were unavailable in our data sets, so we had to use ICD-9-CM codes for this outcome; this prevented us from knowing whether C difficile infections developed while in the hospital or were present on admission and to what degree there was misclassification of true infections vs colonization.52 Sixth, we excluded patients transferred from other hospitals or health care facilities to focus on community-onset infections, but our data did not allow us to identify patients who might have been recently hospitalized. Seventh, our data sets did not allow us to examine the full array of potential complications of antibiotics, such as hepatitis, cytopenias, and drug eruptions. Data on patients’ allergies were also unavailable to us; therefore, we could not account for broad-spectrum antibiotics administered because patients were allergic to narrower agents (such as vancomycin or carbapenems for patients with β-lactam allergies). Furthermore, we only included patients with culture-positive sepsis, but a substantial fraction of patients with sepsis are culture negative.31,32 Determining the consequences of unnecessarily broad antibiotic therapy in the culture-negative population is an important topic for future research.
In this study of a large US cohort, we found that most patients with culture-positive community-onset sepsis did not have resistant organisms; however, empiric, broad-spectrum antibiotics targeting these organisms were frequently prescribed. Both inadequate and unnecessarily broad empiric therapy were associated with higher mortality. These findings underscore the need for better diagnostic tests to rapidly identify resistant pathogens and an increased focus on judicious use of broad-spectrum antibiotics for the empiric treatment of sepsis.
Accepted for Publication: February 19, 2020.
Published: April 16, 2020. doi:10.1001/jamanetworkopen.2020.2899
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Rhee C et al. JAMA Network Open.
Corresponding Author: Chanu Rhee, MD, MPH, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, 401 Park Dr, Ste 401, Boston, MA 02215 (crhee@bwh.harvard.edu).
Author Contributions: Dr Rhee had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Rhee, Dekker, Danner, Klompas.
Acquisition, analysis, or interpretation of data: Rhee, Kadri, Dekker, Chen, Fram, Zhang, Wang, Klompas.
Drafting of the manuscript: Rhee, Wang, Klompas.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Rhee, Zhang, Wang.
Obtained funding: Rhee, Kadri, Klompas.
Administrative, technical, or material support: Chen, Fram.
Supervision: Klompas.
Conflict of Interest Disclosures: Dr Rhee reported receiving personal fees from UpToDate outside the submitted work. Dr Chen reported having a consulting service contract with Harvard Pilgrim Health Care Institute during the conduct of the study. Mr Fram reported having a consulting service contract with Harvard Pilgrim Healthcare Institute during the conduct of the study. Dr Klompas reported receiving personal fees from UpToDate outside the submitted work. No other disclosures were reported.
Funding/Support: This work was funded by grant U54CK000484 from the Centers for Disease Control and Prevention, grant K08HS025008 from the Agency for Healthcare Research and Quality to Dr Rhee, and intramural funds from the National Institutes of Health Clinical Center and National Institute of Allergy and Infectious Diseases to Drs Kadri, Dekker, and Danner.
Role of the Funder/Sponsor: Members of the National Institutes of Health Clinical Center who are coauthors on this study contributed to the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The Centers for Disease Control and Prevention and Agency for Healthcare Research and Quality had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
1.Rhee
C, Jones
TM, Hamad
Y,
et al; Centers for Disease Control and Prevention (CDC) Prevention Epicenters Program. Prevalence, underlying causes, and preventability of sepsis-associated mortality in US acute care hospitals.
JAMA Netw Open. 2019;2(2):e187571. doi:
10.1001/jamanetworkopen.2018.7571PubMedGoogle Scholar 5.Vazquez-Guillamet
C, Scolari
M, Zilberberg
MD, Shorr
AF, Micek
ST, Kollef
M. Using the number needed to treat to assess appropriate antimicrobial therapy as a determinant of outcome in severe sepsis and septic shock.
Crit Care Med. 2014;42(11):2342-2349. doi:
10.1097/CCM.0000000000000516PubMedGoogle ScholarCrossref 9.Hiensch
R, Poeran
J, Saunders-Hao
P,
et al. Impact of an electronic sepsis initiative on antibiotic use and health care facility-onset
Clostridium difficile infection rates.
Am J Infect Control. 2017;45(10):1091-1100. doi:
10.1016/j.ajic.2017.04.005PubMedGoogle ScholarCrossref 10.Polgreen
PM, Chen
YY, Cavanaugh
JE,
et al. An outbreak of severe
Clostridium difficile-associated disease possibly related to inappropriate antimicrobial therapy for community-acquired pneumonia.
Infect Control Hosp Epidemiol. 2007;28(2):212-214. doi:
10.1086/512174PubMedGoogle ScholarCrossref 12.Teshome
BF, Vouri
SM, Hampton
N, Kollef
MH, Micek
ST. Duration of exposure to antipseudomonal β-lactam antibiotics in the critically ill and development of new resistance.
Pharmacotherapy. 2019;39(3):261-270. doi:
10.1002/phar.2201PubMedGoogle ScholarCrossref 13.Hranjec
T, Rosenberger
LH, Swenson
B,
et al. Aggressive versus conservative initiation of antimicrobial treatment in critically ill surgical patients with suspected intensive-care-unit-acquired infection: a quasi-experimental, before and after observational cohort study.
Lancet Infect Dis. 2012;12(10):774-780. doi:
10.1016/S1473-3099(12)70151-2PubMedGoogle ScholarCrossref 14.Kett
DH, Cano
E, Quartin
AA,
et al; Improving Medicine through Pathway Assessment of Critical Therapy of Hospital-Acquired Pneumonia (IMPACT-HAP) Investigators. Implementation of guidelines for management of possible multidrug-resistant pneumonia in intensive care: an observational, multicentre cohort study.
Lancet Infect Dis. 2011;11(3):181-189. doi:
10.1016/S1473-3099(10)70314-5PubMedGoogle ScholarCrossref 17.Choudhry
SA, Li
J, Davis
D, Erdmann
C, Sikka
R, Sutariya
B. A public-private partnership develops and externally validates a 30-day hospital readmission risk prediction model.
Online J Public Health Inform. 2013;5(2):219. doi:
10.5210/ojphi.v5i2.4726PubMedGoogle ScholarCrossref 20.Petrick
JL, Nguyen
T, Cook
MB. Temporal trends of esophageal disorders by age in the Cerner Health Facts database.
Ann Epidemiol. 2016;26(2):151-154.e4.
PubMedGoogle ScholarCrossref 21.Vandenbroucke
JP, von Elm
E, Altman
DG,
et al; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration.
PLoS Med. 2007;4(10):e297. doi:
10.1371/journal.pmed.0040297PubMedGoogle Scholar 23.Tabah
A, Koulenti
D, Laupland
K,
et al. Characteristics and determinants of outcome of hospital-acquired bloodstream infections in intensive care units: the EUROBACT International Cohort Study.
Intensive Care Med. 2012;38(12):1930-1945. doi:
10.1007/s00134-012-2695-9PubMedGoogle ScholarCrossref 24.Kadri
SS, Adjemian
J, Lai
YL,
et al; National Institutes of Health Antimicrobial Resistance Outcomes Research Initiative (NIH–ARORI). Difficult-to-treat resistance in gram-negative bacteremia at 173 US hospitals: retrospective cohort analysis of prevalence, predictors, and outcome of resistance to all first-line agents.
Clin Infect Dis. 2018;67(12):1803-1814. doi:
10.1093/cid/ciy378PubMedGoogle Scholar 25.Kalil
AC, Metersky
ML, Klompas
M,
et al. Executive summary: management of adults with hospital-acquired and ventilator-associated pneumonia: 2016 Clinical Practice Guidelines by the Infectious Diseases Society of America and the American Thoracic Society.
Clin Infect Dis. 2016;63(5):575-582. doi:
10.1093/cid/ciw504PubMedGoogle ScholarCrossref 26.Cooper
AJ, Keller
S, Chan
C,
et al; CDC Prevention Epicenters Program. Improvements in sepsis-associated mortality in hospitalized cancer vs non-cancer patients: a 12-year analysis using clinical data.
Ann Am Thorac Soc. 2019. doi:
10.1513/AnnalsATS.201909-655OCPubMedGoogle Scholar 27.Kadri
SS, Hohmann
SF, Orav
EJ,
et al. Tracking colistin-treated patients to monitor the incidence and outcome of carbapenem-resistant Gram-negative infections.
Clin Infect Dis. 2015;60(1):79-87. doi:
10.1093/cid/ciu741PubMedGoogle ScholarCrossref 28.Moore
BJ, White
S, Washington
R, Coenen
N, Elixhauser
A. Identifying increased risk of readmission and in-hospital mortality using hospital administrative data: the AHRQ Elixhauser Comorbidity Index.
Med Care. 2017;55(7):698-705. doi:
10.1097/MLR.0000000000000735PubMedGoogle ScholarCrossref 29.Cassini
A, Högberg
LD, Plachouras
D,
et al; Burden of AMR Collaborative Group. Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis.
Lancet Infect Dis. 2019;19(1):56-66. doi:
10.1016/S1473-3099(18)30605-4PubMedGoogle ScholarCrossref 37.Maxson
T, Blancett
CD, Graham
AS, Stefan
CP, Minogue
TD. Rapid antibiotic susceptibility testing from blood culture bottles with species agnostic real-time polymerase chain reaction.
PLoS One. 2018;13(12):e0209042. doi:
10.1371/journal.pone.0209042PubMedGoogle Scholar 38.Maurer
FP, Christner
M, Hentschke
M, Rohde
H. Advances in rapid identification and susceptibility testing of bacteria in the clinical microbiology laboratory: implications for patient care and antimicrobial stewardship programs.
Infect Dis Rep. 2017;9(1):6839. doi:
10.4081/idr.2017.6839PubMedGoogle ScholarCrossref 39.Vazquez-Guillamet
MC, Vazquez
R, Micek
ST, Kollef
MH. Predicting resistance to piperacillin-tazobactam, cefepime and meropenem in septic patients with bloodstream infection due to gram-negative bacteria.
Clin Infect Dis. 2017;65(10):1607-1614. doi:
10.1093/cid/cix612PubMedGoogle ScholarCrossref 40.Paul
M, Shani
V, Muchtar
E, Kariv
G, Robenshtok
E, Leibovici
L. Systematic review and meta-analysis of the efficacy of appropriate empiric antibiotic therapy for sepsis.
Antimicrob Agents Chemother. 2010;54(11):4851-4863. doi:
10.1128/AAC.00627-10PubMedGoogle ScholarCrossref 41.Zilberberg
MD, Shorr
AF, Micek
ST, Vazquez-Guillamet
C, Kollef
MH. Multi-drug resistance, inappropriate initial antibiotic therapy and mortality in gram-negative severe sepsis and septic shock: a retrospective cohort study.
Crit Care. 2014;18(6):596. doi:
10.1186/s13054-014-0596-8PubMedGoogle ScholarCrossref 42.Depuydt
PO, Vandijck
DM, Bekaert
MA,
et al. Determinants and impact of multidrug antibiotic resistance in pathogens causing ventilator-associated-pneumonia.
Crit Care. 2008;12(6):R142. doi:
10.1186/cc7119PubMedGoogle ScholarCrossref 43.Zilberberg
MD, Nathanson
BH, Sulham
K, Fan
W, Shorr
AF. A novel algorithm to analyze epidemiology and outcomes of carbapenem resistance among patients with hospital-acquired and ventilator-associated pneumonia: a retrospective cohort study.
Chest. 2019;155(6):1119-1130. doi:
10.1016/j.chest.2018.12.024PubMedGoogle ScholarCrossref 46.Carignan
A, Allard
C, Pépin
J, Cossette
B, Nault
V, Valiquette
L. Risk of
Clostridium difficile infection after perioperative antibacterial prophylaxis before and during an outbreak of infection due to a hypervirulent strain.
Clin Infect Dis. 2008;46(12):1838-1843. doi:
10.1086/588291PubMedGoogle ScholarCrossref 47.Brown
KA, Khanafer
N, Daneman
N, Fisman
DN. Meta-analysis of antibiotics and the risk of community-associated
Clostridium difficile infection.
Antimicrob Agents Chemother. 2013;57(5):2326-2332. doi:
10.1128/AAC.02176-12PubMedGoogle ScholarCrossref 49.Hammond
DA, Smith
MN, Li
C, Hayes
SM, Lusardi
K, Bookstaver
PB. Systematic review and meta-analysis of acute kidney injury associated with concomitant vancomycin and piperacillin/tazobactam.
Clin Infect Dis. 2017;64(5):666-674.
PubMedGoogle Scholar 51.Bhalodi
AA, van Engelen
TSR, Virk
HS, Wiersinga
WJ. Impact of antimicrobial therapy on the gut microbiome.
J Antimicrob Chemother. 2019;74(Supplement_1):i6-i15.
PubMedGoogle ScholarCrossref 52.Koo
HL, Van
JN, Zhao
M,
et al. Real-time polymerase chain reaction detection of asymptomatic
Clostridium difficile colonization and rising
C. difficile-associated disease rates.
Infect Control Hosp Epidemiol. 2014;35(6):667-673. doi:
10.1086/676433PubMedGoogle ScholarCrossref