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. 2023 Jul 3;10(7):ofad334. doi: 10.1093/ofid/ofad334

Distribution, Trends, and Antimicrobial Susceptibility of Bacteroides, Clostridium, Fusobacterium, and Prevotella Species Causing Bacteremia in Japan During 2011–2020: A Retrospective Observational Study Based on National Surveillance Data

Toshiki Kajihara 1,✉, Koji Yahara 2, Norikazu Kitamura 3, Aki Hirabayashi 4, Yumiko Hosaka 5, Motoyuki Sugai 6,2
PMCID: PMC10352651  PMID: 37469615

Abstract

Background

The increasing prevalence of anaerobic bacteremia is a major concern worldwide and requires longitudinal monitoring.

Methods

We present one of the largest and longest longitudinal studies on the prevalence and antimicrobial resistance of Bacteroides, Clostridium, Fusobacterium, and Prevotella spp. isolated from blood culture samples using national comprehensive surveillance data in Japan during 2011–2020 as part of the Japan Nosocomial Infections Surveillance.

Results

Data for 41 949 Bacteroides spp., 40 603 Clostridium spp., 7013 Fusobacterium spp., and 5428 Prevotella spp. isolates were obtained. The incidences of bacteremia caused by Bacteroides fragilis, Clostridium perfringens, and Fusobacterium nucleatum significantly increased during the period (P < .0001). Among the 20 species analyzed, 18 showed no significant changes in susceptibility over time, including B. fragilis, C perfringens, and F. nucleatum. However, resistance to clindamycin increased in B. thetaiotaomicron (P = .0312), and resistance to ampicillin increased in B. ovatus (P = .0008).

Conclusions

Our comprehensive national surveillance data analysis demonstrated a continuous increase in the incidence of anaerobic bacteremia, particularly in B. fragilis, C. perfringens, and F. nucleatum. This may be linked to the increasing number of colorectal cancer cases or advancing methods for species identification and susceptibility testing, requiring cautious interpretation. The discovery of an upsurge in anaerobic bacteremia and potential alterations in susceptibility highlights the necessity for more extensive studies in this field.

Keywords: anaerobe, antimicrobial resistance, bacteremia, bloodstream infections

This study using comprehensive national surveillance data demonstrated a continuous increase in the incidence of anaerobic bacteremia and potential alterations of antimicrobial susceptibility in Japan during 2011-2020, highlighting the necessity for more extensive studies in this field.

Anaerobic bacteria continue to be important causative pathogens of bacteremia, which frequently leads to severe life-threatening conditions [1]. The difficulty in isolating these bacteria leads to delayed diagnosis and treatment. Routine susceptibility testing for anaerobic bacteria should be considered for specific clinical situations and monomicrobial infections [2].

Bacteremia caused by anaerobes is a re-emerging infectious disease. The incidence of anaerobic bacteria among all bacteria from positive blood cultures varies by country: 1.6% in Italy, 4.1% in Singapore, 3% in Iowa and Burlington in the United States in 2000, and 10.4% in Minnesota in the United States in 2004 [3–6]. In the United States, the incidence of bacteremia caused by anaerobes decreased by 45% between 1974 and 1988 [7], but Lassmann et al. reported a 30% increase in 2 hospitals during 1993–2004 [5]. In Italy, a slight upward trend was noted in anaerobic blood infections between 2016 and 2020 [3].

Antibiotic resistance among anaerobic microorganisms has significantly increased in recent decades [8, 9], and the resistance rates vary widely by region. Veloo et al. reported that 9.6% of Bacteroides isolates from Kuwait and 4% from Belgium were resistant to meropenem [10]. In the B. fragilis group, resistance to penicillin occurred in 80%–90% of isolates, and resistance to amoxicillin-clavulanate rose from 0.8% in 1992% to 6.2% in 2010–2011 [9]. The most significant change in Bacteroides spp. in recent years has been an increase in resistance to clindamycin (CLDM) by up to 30%–50% [11, 12]. In vitro susceptibility testing for Bacteroides isolates reliably predicts patient response to therapy [13]. Further studies are needed to evaluate trends in incidence and antimicrobial resistance and to inform prescribing and antimicrobial stewardship strategies.

In Japan, comprehensive surveillance data have been collected in a national antimicrobial resistance surveillance program—the Japan Nosocomial Infections Surveillance (JANIS)—in which all routine microbiological test results are being collected for all sample types from both symptomatic and asymptomatic patients from hundreds or thousands of participating hospitals since 2000 [14]. However, comprehensive national surveillance data have not yet been utilized for anaerobic bacteria studies, and only local surveillance in the Kansai region has been conducted for 4 months [15].

In this study, we focused on Bacteroides, Clostridium, Fusobacterium, and Prevotella spp. and evaluated their incidence rate, distribution trend, and antimicrobial susceptibility, using comprehensive national data from JANIS for the period 2011–2020.

METHODS

Data Preparation and Tabulation

All inpatient and outpatient data from January 2011 to December 2020 were extracted from the JANIS database, comprising all routine microbiological diagnostic tests (including culture-positive and culture-negative results) and antimicrobial susceptibility testing results [14]. A total of 2167 hospitals across Japan submitted their data to the JANIS database in 2020. These included 46 of 52 (88.5%) hospitals with >900 beds, 287 of 349 (82.2%) hospitals with 500–899 beds, 1031 of 2130 (48.4%) hospitals with 200–499 beds, and 803 of 5769 (13.9%) hospitals with <200 beds. We specifically targeted Bacteroides spp., Clostridium spp., Fusobacterium spp., and Prevotella spp. due to their high crude mortality [16]. We used a Java toolkit to extract the data of isolates of Bacteroides spp. (B. fragilis, B. thetaiotaomicron, B. vulgatus, B. uniformis, B. ovatus, B. caccae, Parabacteroides distasonis, and other Bacteroides), Clostridium spp. (C. perfringens, C. septicum, and other Clostridium), Fusobacterium spp. (F. nucleatum, F. necrophorum, F. mortiferum, F. varium, and other Fusobacterium), and Prevotella spp. (P. oralis, P. meraninogenica, P. buccae, P. bivia, P. intermedia, P. denticola, P. loescheii, P. corporis, P. ruminicola, and other Prevotella), which were isolated from blood samples and subjected to antimicrobial susceptibility testing for ampicillin (ABPC), ampicillin-sulbactam (SBT/ABPC), piperacillin-tazobactam (TAZ/PIPC), CLDM, cefmetazole (CMZ), cefotaxime (CTX), imipenem (IPM), and meropenem (MEPM). The antimicrobial susceptibility testing data in JANIS comprises minimum inhibitory concentration (MIC) data. Participating hospitals in JANIS may employ various CLSI methods, but for this study, we used the CLSI 2020 criteria to interpret the MIC data for susceptibility, employing breakpoints. The data were organized using the “one isolate per patient for each species” deduplication algorithm of the World Health Organization's Global Antimicrobial Surveillance System [17, 18]. The collection of data on susceptibility testing methods, such as Walkaway, Vitek II, or Dryplate Eiken, was also implemented for each participating hospital in JANIS and subsequently incorporated into the tabulated results.

Statistical Analysis

The statistical significance of the differences in proportions was tested using the Pearson chi-square or Fisher exact test (when the minimum count in a contingency table was <5). To account for multiple comparisons, we separately applied the Benjamini-Hochberg false discovery rate correction [19] for each species. To maintain a false discovery rate <5% for each species, the significance threshold was established. The Cochran-Armitage trend test was used to test for any trend in the incidence (ie, number of anaerobic bacteremia cases divided by the total number of patients who underwent blood culture testing) across the years. The level of significance was set at P < .05. All statistical analyses were performed using R software (version 4.0.5) and JMP Pro (version 13; SAS Institute, Cary, NC, USA).

Patient Consent

Patient identifiers were de-identified by each hospital before data submission to JANIS. The anonymous data stored in the JANIS database were exported and analyzed. The protocol of this study was approved by the Ministry of Health, Labor and Welfare (approval number: 0425–3) according to Article 32 of the Statistics Act and in accordance with the Helsinki Declaration. The requirement for informed consent was waived by the Ministry of Health, Labor and Welfare (approval number: 0425–3).

RESULTS

Trends and Incidence of Bacteremia due to Bacteroides, Clostridium, Fusobacterium, and Prevotella Species

The annual number of patients with bacteremia due to Bacteroides, Clostridium, Fusobacterium, and Prevotella spp. and the number of patients from whom blood samples were collected from January 2011 to December 2020 are shown in Table 1. A total of 13 118 386 blood samples were collected from patients during this period, with 40 841, 40 214, 6978, and 5367 patients diagnosed with Bacteroides, Clostridium, Fusobacterium, and Prevotella bacteremia, respectively.

Table 1.

Distribution and Trend of Bacteremia Caused by Bacteroides, Clostridium, Fusobacterium, and Prevotella spp. in Japan Between 2011 and 2020

Total 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
No. of participating hospitals 593 660 745 883 1435 1653 1795 1947 2075 2167
No. of patients who underwent blood culture testing 13 118 386 565 036 662 045 783 151 915 448 1 403 631 1 577 451 1 672 373 1 811 038 1 930 940 1 797 273
No. of Bacteroides isolates 41 949 1794 2041 2533 2844 4328 4852 5205 5874 6109 6369
No. of bacteremia episodes 40 841 1760 2007 2477 2788 4236 4720 5076 5690 5903 6184
Incidence of bacteremia (per 100 000 tested patients) 319.8 317.5 308.3 323.4 310.7 308.3 307.6 311.2 324.3 316.4 354.4
Male sex, % 56.8 59.3 59.9 57.0 58.3 58.3 57.3 56.2 57.0 54.8 54.9
Unknown sex 1176 64 59 74 106 117 151 130 156 149 170
Age, mean ± SD, y 73.4 ± 14.9 70.9 ± 15.3 70.8 ± 15.7 71.8 ± 15.5 71.7 ± 15.7 72.6 ± 14.9 73.2 ± 14.4 74.1 ± 14.9 74.3 ± 14.4 74.4 ± 14.9 75.0 ± 14.6
Unknown age 1465 19 22 24 53 197 164 225 249 263 249
No. of Clostridium isolates 40 603 1351 1670 2220 2752 4087 4929 5385 5956 5961 6292
No. of bacteremia episodes 40 214 1336 1655 2192 2725 4048 4887 5344 5899 5898 6230
Incidence of bacteremia (per 100 000 tested patients) 309.5 239.1 252.2 283.5 300.6 291.2 312.5 322.0 328.9 308.7 350.1
Male sex, % 53.9 54.6 57.8 56.0 55.8 55.7 53.0 52.9 52.7 52.8 53.6
Unknown sex 1360 46 43 76 125 167 163 178 197 181 184
Age, mean ± SD, y 79.0 ± 12.5 77.0 ± 14.0 77.3 ± 13.2 77.7 ± 12.8 78.1 ± 11.9 78.6 ± 12.7 79.1 ± 12.2 79.4 ± 12.4 79.5 ± 12.4 79.5 ± 12.3 79.9 ± 12.2
Unknown age 1615 9 20 18 52 179 190 261 291 306 289
No. of Fusobacterium isolates 7013 247 275 426 500 704 798 902 948 1055 1158
No. of bacteremia episodes 6978 247 275 422 498 704 791 897 944 1049 1151
Incidence of bacteremia
(per 100 000 tested patients)		 53.5 43.7 41.5 54.4 54.6 50.2 50.6 53.9 52.3 54.6 64.4
Male sex, % 65.0 69.9 65.0 67.7 63.8 64.8 64.8 66.0 65.0 64.3 62.0
Unknown sex 197 8 9 16 12 19 27 30 23 25 28
Age, mean ± SD, y 68.0 ± 18.4 65.4 ± 18.0 68.6 ± 16.6 66.8 ± 18.4 66.1 ± 18.6 68.0 ± 17.8 67.4 ± 18.0 67.6 ± 19.1 68.1 ± 18.4 69.5 ± 18.0 69.2 ± 19.0
Unknown age 183 1 0 4 3 15 19 30 35 39 37
No. of Prevotella isolates 5428 231 257 373 446 596 629 686 689 753 768
No. of bacteremia episodes 5367 229 257 367 439 588 614 677 693 745 758
Incidence of bacteremia (per 100 000 tested patients) 41.4 40.9 38.8 47.6 48.7 42.5 39.9 41.0 38.0 39.0 42.7
Male sex, % 57.7 56.2 54.7 55.0 58.3 60.1 57.7 59.3 55.4 58.3 58.6
Unknown sex 147 10 3 7 15 21 13 23 14 19 22
Age, mean ± SD, y 71.4 ± 15.8 69.8 ± 14.8 70.6 ± 15.5 70.0 ± 17.4 70.5 ± 15.8 71.6 ± 15.5 71.9 ± 15.2 71.8 ± 15.4 71.0 ± 16.7 72.7 ± 15.5 71.4 ± 15.7
Unknown age 104 2 0 0 5 6 8 12 28 28 15
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The incidence of bacteremia due to Bacteroides spp., Clostridium spp., Fusobacterium spp., and Prevotella spp. was 354, 350, 64, and 43/100 000 patients, respectively, who underwent blood culture testing in 2020 (Figure 1). The incidence of bacteremia caused by Bacteroides spp., Clostridium spp., and Fusobacterium spp. significantly increased from 2011 to 2020 by 11.7% (P < .0001), 52.2% (P < .0001), and 47.4% (P < .0001), respectively. In 2016, the incidence rate of bacteremia caused by Clostridium spp. was similar to that caused by Bacteroides spp. The annual incidence from 2011 to 2020 stratified by species is shown in Figure 2, where only B. fragilis showed a 1.12-fold increase in incidence among Bacteroides spp. (P < .0001, blue in Figure 2A); C. perfringens and F. nucleatum showed a significant increase (P < .0001, blue in Figure 2B and C).

Figure 1.

Figure 1.

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Combined annual incidence of bacteremia caused by Bacteroides, Clostridium, Fusobacterium, and Prevotella spp. during 2011–2020.

Figure 2.

Figure 2.

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Distribution and individual annual incidences of bacteremia caused by Bacteroides, Clostridium, Fusobacterium, and Prevotella spp. during 2011–2020. A, Bacteroides spp., (B) Clostridium spp., (C) Fusobacterium spp., and (D) Prevotella spp.

Notable Susceptibility Patterns to Antimicrobial Agents

Only some of the isolates submitted to the JANIS database (32.9% [13 788/41 949] of all Bacteroides spp., 33.6% [13 658/40 603] of all Clostridium spp., 31.7% [2220/7013 isolates] of all Fusobacterium spp., and 36.6% [1985/5428 isolates] of all Prevotella spp.) were subjected to antimicrobial susceptibility testing. The susceptibility trends of Bacteroides spp., Clostridium spp., Fusobacterium spp., and Prevotella spp. are summarized in Figure 3. All Bacteroides isolates remained highly susceptible to CMZ (gray line), IPM (light blue line), MEPM (green line), SBT/ABPC (dark blue line), and TAZ/PIPC (brown line). All Clostridium isolates remained highly susceptible to ABPC (blue line), CMZ, CTX (yellow line), IPM, MEPM, SBT/ABPC, and TAZ/PIPC. The resistance rates of Prevotella spp. to ABPC, CTX, and CLDM (orange line) were higher (62.7%, 23.3%, and 29.8% in 2020) than those to the others. The resistance rates of Bacteroides, Clostridium, Fusobacterium, and Prevotella spp., except for P. ruminicola during 2011 and 2020, and the comparison between the early (2011–2015) and late (2016–2020) phases are shown in Table 2. P. ruminicola was excluded because the number of isolates subjected to antimicrobial susceptibility testing was <30. Significant increases in resistance rates were observed for B. thetaiotaomicron to CLDM and B. ovatus to ABPC (P = .0312 and P = .0008). Conversely, the resistance rates of P. distasonis to IPM and P. loescheii to ABPC (P = .0008 and P < .0001) significantly decreased.

Figure 3.

Figure 3.

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Individual antimicrobial resistance rates of Bacteroides, Clostridium, Fusobacterium, and Prevotella spp. during 2011–2020. A, Bacteroides spp., (B) Clostridium spp., (C) Fusobacterium spp., and (D) Prevotella spp. The following antibiotics are shown: ABPC is indicated by the blue line, CLDM is indicated by the orange line, CMZ is indicated by the gray line, CTX is indicated by the yellow line, IPM is indicated by the light blue line, MEPM is indicated by the green line, SBT/ABPC is indicated by the dark blue line, and TAZ/PIPC is indicated by the brown line. Abbreviations: ABPC, ampicillin; CLDM, clindamycin; CMZ, cefmetazole; CTX, cefotaxime; IPM, imipenem; MEPM, meropenem; SBT/ABPC, sulbactam/ampicillin; TAZ/PIPC, tazobactam/piperacillin.

Table 2.

Resistance Rates of Anaerobic Bacteria to Eight Antibiotics During 2011–2020 and Comparison With the Findings Obtained During 2011–2015 and 2016–2020

Total, % (No.) Early Period, % (No.) Late Period, % (No.)
Species 2011–2020 2011–2015 2016–2020 Difference, % Adjusted P Value*
Bacteroides fragilis
ABPC 96.8 (7167/7401) 96.6 (2190/2268) 97.0 (4977/5133) +0.4 n.s.
CLDM 32.7 (2557/7824) 32.1 (733/2284) 32.9 (1824/5540) +0.8 n.s.
CMZ 5.6 (401/7127) 6.6 (132/2009) 5.3 (269/5118) −1.3 n.s.
CTX 38.1 (758/1991) 35.9 (208/579) 39.0 (550/1412) +3.1 n.s.
IPM 2.0 (152/7625) 2.6 (58/2259) 1.8 (94/5366) −0.8 n.s.
MEPM 3.6 (253/7126) 3.5 (71/2056) 3.6 (182/5070) +0.1 n.s.
SBT/ABPC 3.3 (242/7224) 3.6 (73/2052) 3.3 (169/5172) −0.3 n.s.
TAZ/PIPC 1.5 (82/5344) 1.5 (21/1368) 1.5 (61/3976) 0 n.s.
Bacteroides thetaiotaomicron
ABPC 97.6 (2008/2058) 97.3 (619/636) 97.7 (1389/1422) +0.4 n.s.
CLDM 51.5 (1128/2190) 46.7 (307/657) 53.6 (821/1533) +7.1 0.0312
CMZ 32.3 (652/2016) 33.9 (205/605) 31.7 (447/1411) −2.2 n.s.
CTX 64.0 (311/486) 57.0 (86/151) 67.2 (225/335) +10.2 n.s.
IPM 1.5 (32/2142) 1.2 (8/663) 1.6 (24/1479) +0.4 n.s.
MEPM 1.8 (35/1944) 1.5 (8/551) 1.9 (27/1393) +0.4 n.s.
SBT/ABPC 4.0 (80/2015) 3.3 (19/572) 4.2 (61/1443) +0.9 n.s.
TAZ/PIPC 2.8 (40/1432) 2.6 (9/350) 2.9 (31/1082) +0.3 n.s.
Bacteroides caccae
ABPC 95.5 (299/313) 95.2 (100/105) 95.7 (199/208) +0.5 n.s.
CLDM 35.5 (119/335) 32.7 (37/113) 36.9 (82/222) +3.2 n.s.
CMZ 7.7 (21/272) 8.5 (8/94) 7.3 (13/178) −1.2 n.s.
CTX 35.5 (27/76) N/A 39.3 (22/56) N/A N/A
IPM 2.4 (8/328) 2.8 (3/109) 2.3 (5/219) −0.5 n.s.
MEPM 3.4 (10/296) 4.7 (4/85) 2.8 (6/211) −1.9 n.s.
SBT/ABPC 3.8 (11/289) 4.4 (4/90) 3.5 (7/199) −0.9 n.s.
TAZ/PIPC 3.1 (7/223) 3.3 (2/60) 3.1 (5/163) −0.2 n.s.
Bacteroides vulgatus
ABPC 95.5 (779/816) 93.1 (176/189) 96.2 (603/627) +3.2 n.s.
CLDM 42.4 (342/806) 44.6 (82/184) 41.8 (260/622) −2.8 n.s.
CMZ 5.3 (42/797) 7.1 (13/184) 4.7 (29/613) −2.4 n.s.
CTX 35.2 (62/176) 36.2 (17/47) 34.9 (45/129) −1.3 n.s.
IPM 1.3 (11/816) 1.6 (3/185) 1.3 (8/628) −0.3 n.s.
MEPM 0.8 (6/757) 0.6 (1/169) 0.9 (5/588) +0.3 n.s.
SBT/ABPC 3.1 (24/778) 1.8 (3/166) 3.4 (21/612) +1.6 n.s.
TAZ/PIPC 2.0 (12/593) 2.7 (3/112) 1.9 (9/481) −0.8 n.s.
Parabacteroides distasonis
ABPC 94.2 (537/570) 93.3 (194/208) 94.8 (343/362) +1.5 n.s.
CLDM 39.1 (218/557) 41.3 (76/184) 38.1 (142/373) −3.2 n.s.
CMZ 25.2 (130/515) 26.5 (43/162) 24.6 (87/353) −1.9 n.s.
CTX 47.5 (58/122) 45.5 (20/44) 48.7 (38/78) +3.2 n.s.
IPM 6.0 (36/605) 11.3 (24/213) 3.1 (12/392) −8.2 0.0008
MEPM 1.5 (8/509) 1.2 (2/166) 1.7 (4/341) +0.5 n.s.
SBT/ABPC 16.1 (87/542) 21.1 (38/180) 13.5 (49/362) −7.6 n.s.
TAZ/PIPC 5.8 (23/398) 6.9 (7/102) 5.4 (16/298) −1.5 n.s.
Bacteroides uniformis
ABPC 94.3 (549/582) 92.1 (152/165) 95.2 (397/417) +3.1 n.s.
CLDM 49.7 (286/576) 43.8 (64/146) 51.6 (222/430) +7.8 n.s.
CMZ 9.7 (53/549) 9.7 (14/145) 9.7 (39/404) 0 n.s.
CTX 51.1 (69/135) 48.9 (22/45) 52.2 (47/90) +3.3 n.s.
IPM 1.0 (6/586) 1.3 (2/156) 0.9 (4/430) −0.4 n.s.
MEPM 0.9 (5/567) 1.3 (2/154) 0.7 (3/413) −0.6 n.s.
SBT/ABPC 2.9 (16/556) 4.8 (7/145) 2.2 (9/411) −2.6 n.s.
TAZ/PIPC 0.9 (4/428) 1.1 (1/91) 0.9 (3/337) −0.2 n.s.
Bacteroides ovatus
ABPC 93.3 (567/608) 87.3 (172/197) 96.1 (395/411) +8.8 .0008
CLDM 39.8 (229/576) 35.2 (64/182) 41.9 (165/394) +6.7 n.s.
CMZ 23.0 (139/605) 20.2 (39/193) 24.3 (100/412) +4.1 n.s.
CTX 46.7 (64/137) 46.5 (20/43) 46.8 (44/94) +0.3 n.s.
IPM 1.8 (11/607) 1.0 (2/203) 2.2 (9/403) +1.2 n.s.
MEPM 1.2 (7/568) 1.2 (2/166) 1.2 (5/402) 0 n.s.
SBT/ABPC 3.3 (19/575) 3.3 (6/183) 3.3 (13/392) 0 n.s.
TAZ/PIPC 2.6 (11/417) 0.9 (1/115) 3.3 (10/302) +2.4 n.s.
Clostridium perfringens
ABPC 1.8 (138/7696) 1.8 (40/2180) 1.8 (98/5516) 0 n.s.
CLDM 9.8 (794/8064) 9.5 (203/2137) 10.0 (591/5927) +0.5 n.s.
CMZ 0.3 (19/7344) 0.3 (6/1922) 0.2 (13/5422) −0.1 n.s.
CTX 0.4 (7/1843) 0.6 (3/507) 0.3 (4/1336) −0.3 n.s.
IPM 0.3 (21/7802) 0.3 (6/2096) 0.3 (15/5706) 0 n.s.
MEPM 0.1 (7/7204) 0.2 (3/1901) 0.1 (4/5303) −0.1 n.s.
SBT/ABPC 0.3 (24/7410) 0.2 (3/1900) 0.4 (21/5470) +0.2 n.s.
TAZ/PIPC 0.1 (6/5367) 0 (0/1202) 0.1 (6/4165) +0.1 n.s.
Clostridium septicum
ABPC 2.5 (4/157) 1.7 (1/59) 3.1 (3/98) +1.4 n.s.
CLDM 17.6 (26/148) 18.9 (10/53) 16.8 (16/95) −2.1 n.s.
CMZ 0 (0/138) 0 (0/49) 0 (0/89) 0 n.s.
CTX 0 (0/40) N/A N/A N/A N/A
IPM 0 (0/142) 0 (0/50) 0 (0/92) 0 n.s.
MEPM 0 (0/141) 0 (0/50) 0 (0/91) 0 n.s.
SBT/ABPC 0 (0/144) 0 (0/49) 0 (0/95) 0 n.s.
TAZ/PIPC 0 (0/97) N/A 0 (0/71) N/A N/A
Fusobacterium nucleatum
ABPC 3.6 (27/759) 6.2 (14/225) 2.4 (13/534) −3.8 n.s.
CLDM 1.6 (12/757) 1.4 (3/221) 1.7 (9/536) +0.3 n.s.
CMZ 0.4 (3/730) 1.4 (3/212) 0 (0/518) −1.4 n.s.
CTX 1.0 (2/198) 1.8 (1/55) 0.7 (1/143) −1.1 n.s.
IPM 0 (0/732) 0 (0/222) 0 (0/510) 0 n.s.
MEPM 0.1 (1/724) 0.5 (1/219) 0 (0/505) −0.5 n.s.
SBT/ABPC 0.5 (4/740) 1.4 (3/209) 0.2 (1/531) −1.2 n.s.
TAZ/PIPC 0.7 (4/566) 2.2 (3/137) 0.2 (1/429) −2.0 n.s.
Fuobacterium necrophorum
ABPC 4.7 (11/235) 7.1 (6/84) 3.3 (5/151) −3.8 n.s.
CLDM 2.8 (7/246) 3.3 (3/91) 2.6 (4/155) −0.7 n.s.
CMZ 1.8 (4/221) 3.9 (3/76) 0.7 (1/145) −3.2 n.s.
CTX 5.5 (3/55) N/A 0 (0/34) N/A N/A
IPM 0.8 (2/242) 1.2 (1/81) 0.6 (1/161) −0.6 n.s.
MEPM 0.4 (1/234) 1.1 (1/89) 0 (0/145) −1.1 n.s.
SBT/ABPC 0.4 (1/251) 1.1 (1/91) 0 (0/160) −1.1 n.s.
TAZ/PIPC 0.6 (1/157) 0 (0/49) 0.9 (1/109) +0.9 n.s.
Fusobacterium mortiferum
ABPC 20.4 (44/216) 23.3 (14/60) 19.2 (30/156) −4.1 n.s.
CLDM 1.8 (4/221) 3.2 (2/63) 1.3 (2/158) −1.9 n.s.
CMZ 1.5 (3/205) 1.7 (1/58) 1.4 (2/147) −0.3 n.s.
CTX 14.9 (7/47) N/A 11.4 (4/35) N/A N/A
IPM 1.4 (3/218) 1.6 (1/62) 1.3 (2/156) −0.3 n.s.
MEPM 1.4 (3/216) 0 (0/65) 2.0 (3/151) +2.0 n.s.
SBT/ABPC 2.9 (6/210) 3.4 (2/58) 2.6 (4/152) −0.8 n.s.
TAZ/PIPC 4.0 (6/151) 5.6 (2/36) 3.5 (4/115) −2.1 n.s.
Fusobacterium varium
ABPC 42.2 (70/166) 40 (18/45) 43.0 (52/121) +3.0 n.s.
CLDM 37.8 (62/164) 28.9 (13/45) 41.2 (49/119) +12.3 n.s.
CMZ 3.3 (5/153) 5.1 (2/39) 2.6 (3/114) −2.5 n.s.
CTX 2.4 (1/42) N/A 3.2 (1/31) N/A N/A
IPM 4.2 (7/165) 2.4 (1/42) 4.9 (6/123) +2.5 n.s.
MEPM 1.3 (2/152) 2.3 (1/44) 0.9 (1/108) −1.4 n.s.
SBT/ABPC 2.5 (4/161) 5.0 (2/40) 1.7 (2/121) −3.3 n.s.
TAZ/PIPC 3.2 (4/126) N/A 3.1 (3/97) N/A N/A
Prevotella oralis
ABPC 73.9 (224/276) 78.4 (87/111) 70.9 (117/165) −7.5 n.s.
CLDM 32.6 (95/291) 33.0 (37/112) 32.4 (58/179) −0.6 n.s.
CMZ 10.4 (25/240) 11.4 (10/88) 9.7 (15/152) −1.7 n.s.
CTX 38.9 (35/90) 41.9 (13/31) 37.3 (22/59) −4.6 n.s.
IPM 1.1 (3/276) 1.0 (1/102) 1.1 (2/174) +0.1 n.s.
MEPM 0.4 (1/260) 1.0 (1/105) 0 (0/155) −1.0 n.s.
SBT/ABPC 3.4 (9/268) 3.0 (3/99) 3.6 (6/169) +0.6 n.s.
TAZ/PIPC 2.2 (4/181) 3.4 (2/58) 1.6 (2/123) −1.8 n.s.
Prevotella melaninogenica
ABPC 70.3 (142/202) 74.7 (68/91) 66.7 (74/111) −8.0 n.s.
CLDM 29.0 (61/210) 31.9 (30/94) 26.7 (31/116) −5.2 n.s.
CMZ 11.5 (21/183) 16.7 (14/84) 7.1 (7/99) −9.6 n.s.
CTX 36.5 (19/52) N/A N/A N/A N/A
IPM 1.4 (3/215) 2.0 (2/98) 0.9 (1/117) −1.1 n.s.
MEPM 2.1 (4/191) 2.5 (2/80) 1.8 (2/111) −0.7 n.s.
SBT/ABPC 3.7 (7/189) 6.5 (5/77) 1.8 (2/112) −4.7 n.s.
TAZ/PIPC 1.4 (2/139) 2.0 (1/51) 1.1 (1/88) −0.9 n.s.
Prevotella buccae
ABPC 54.3 (120/221) 59.6 (34/57) 52.4 (86/164) −7.2 n.s.
CLDM 25.6 (57/223) 29.1 (16/55) 24.4 (41/168) −4.7 n.s.
CMZ 2.3 (5/215) 5.4 (3/56) 1.3 (2/159) −4.1 n.s.
CTX 19.6 (9/46) N/A 19.4 (6/31) N/A N/A
IPM 0.4 (1/231) 0 (0/58) 0.6 (1/173) +0.6 n.s.
MEPM 1.9 (4/210) 4.3 (2/47) 1.2 (2/163) −3.1 n.s.
SBT/ABPC 0.5 (1/203) 0 (0/46) 0.6 (1/157) +0.6 n.s.
TAZ/PIPC 0 (0/153) N/A 0 (0/129) N/A N/A
Prevotella bivia
ABPC 73.4 (127/173) 63.8 (30/47) 77.0 (97/126) +13.2 n.s.
CLDM 35.1 (65/185) 21.6 (11/51) 40.3 (54/134) +18.7 n.s.
CMZ 2.9 (5/175) 7.0 (3/43) 1.5 (2/132) −5.5 n.s.
CTX 11.9 (7/59) N/A 10.5 (4/38) N/A N/A
IPM 1.2 (2/173) 4.5 (2/44) 0 (0/124) −4.5 n.s.
MEPM 0 (0/156) 0 (0/33) 0 (0/124) 0 n.s.
SBT/ABPC 0.6 (1/171) 2.8 (1/36) 0 (0/135) −2.8 n.s.
TAZ/PIPC 0 (0/126) N/A 0 (0/103) N/A N/A
Prevotella intermedia
ABPC 41.0 (64/156) 40.0 (20/50) 41.5 (44/106) +1.5 n.s.
CLDM 13.9 (23/166) 13.5 (7/52) 14.0 (16/114) +0.5 n.s.
CMZ 0 (0/143) 0 (0/43) 0 (0/100) 0 n.s.
CTX 2.7 (1/37) N/A N/A N/A N/A
IPM 0 (0/164) 0 (0/52) 0 (0/112) 0 n.s.
MEPM 0 (0/146) 0 (0/40) 0 (0/106) 0 n.s.
SBT/ABPC 0 (0/151) 0 (0/42) 0 (0/109) 0 n.s.
TAZ/PIPC 0 (0/110) N/A 0 (0/84) N/A N/A
Prevotella denticola
ABPC 71.9 (46/64) N/A 65.1 (28/43) N/A N/A
CLDM 28.3 (17/60) N/A 27.3 (12/44) N/A N/A
CMZ 1.8 (1/55) N/A 2.6 (1/39) N/A N/A
CTX N/A N/A N/A N/A N/A
IPM 0 (0/58) N/A 0 (0/39) N/A N/A
MEPM 1.6 (1/61) N/A 2.3 (1/43) N/A N/A
SBT/ABPC 1.6 (1/62) N/A 2.3 (1/43) N/A N/A
TAZ/PIPC 0 (0/45) N/A 0 (0/34) N/A N/A
Prevotella loescheii
ABPC 78.0 (96/123) 94.4 (67/71) 55.8 (29/52) −38.6 <0.0001
CLDM 40.7 (57/140) 49.3 (36/73) 31.3 (21/67) −18.0 n.s.
CMZ 11.0 (10/91) 9.8 (5/51) 12.5 (5/40) +2.7 n.s.
CTX 46.2 (24/52) N/A N/A N/A N/A
IPM 1.5 (2/135) 2.9 (2/68) 0 (0/67) −2.9 n.s.
MEPM 1.6 (2/122) 3.0 (2/66) 0 (0/66) −3.0 n.s.
SBT/ABPC 5.6 (7/126) 9.7 (6/62) 1.5 (1/64) −8.2 n.s.
TAZ/PIPC 0 (0/51) N/A N/A N/A N/A
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Abbreviations: ABPC, ampicillin; CLDM, clindamycin; CMZ, cefmetazole; CTX, cefotaxime; IPM, imipenem; MEPM, meropenem; N/A, not analyzed because the total number of tests was <30 for the period; n.s., not significant; SBT/ABPC, sulbactam/ampicillin; TAZ/PIPC, tazobactam/piperacillin.

DISCUSSION

This study showed a continuous increase in the incidence of anaerobic bacteremia, particularly in B. fragilis, C. perfringens, and F. nucleatum. However, most species (18 of 20) showed no significant changes in susceptibility over the study duration, including B. fragilis, C perfringens, and F. nucleatum. Notably, resistance to CLDM increased in B. thetaiotaomicron, and resistance to ABPC increased in B. ovatus. Our results provide a comprehensive overview of the epidemiology of the 4 anaerobic species that caused bacteremia in Japan.

Dorsher et al. reported that the incidence rate of anaerobic bacteremia decreased over a 15-year period in Minnesota the United States in 1991 [7]. In contrast, some studies have reported increasing bacteremia caused by anaerobic bacteria [3, 5, 20]. Consistent with these reports, in the present study, we observed an increase in the incidence of anaerobic bacteremia caused by Bacteroides, Clostridium, and Fusobacterium spp. Note that we could not show the incidence of anaerobic bacteremia in terms of the number of hospitalizations because the number of admissions is not mandatory in the voluntary-based JANIS database. Therefore, we used the number of patients who underwent blood culture tests to evaluate the incidence of anaerobic bacteremia.

Table 1 demonstrates that the incidence of anaerobic bacteremia is generally higher in males than in females. Male sex was identified as a risk factor for the development of anaerobic bacteremia [21]. Notably, the occurrence of Fusobacterium spp. is particularly elevated in males, with rates in the range of 64.3%–69.9% (Table 1). Mason et al. have reported that smoking increases the abundance of Fusobacterium spp., especially F. nucleatum, in both periodontally healthy and diseased individuals [22]. In Japan, the percentage of male smokers has been considerably higher than that of female smokers (35.9% vs 13.6% in 2022) [23]. Hence, smoking habits may be associated with the incidence of bacteremia caused by Fusobacterium spp.

Figure 2 illustrates an increase in bacteremia caused by B. fragilis, C. perfringens, and F. nucleatum. This trend may be attributed to the rising incidence of colorectal cancer. Kwong et al. reported significant associations between colorectal cancer and bloodstream infections caused by Streptococcus gallolyticus, B. fragilis, F. nucleatum, Peptostreptococcus spp., C. perfringens, and other anaerobic bacteria [24]. In Japan, the annual incidence of colorectal cancer continues to increase [25]. The surge in surgical procedures involving the small intestine, colon, rectum, anus, gall bladder, and pancreas may also contribute to this trend [26]. According to a report from the JANIS SSI section, in 2020 B. fragilis ranked as the third most frequent pathogen in colon surgeries and the fourth most frequent pathogen in rectal surgeries (source: https://janis.mhlw.go.jp/report/open_report/2021/3/5/SSI_Open_Report_202100.xls). Another potential factor could be advancements in species identification and susceptibility testing methods, such as the Rapid ID 32A API, the system for microorganism identification, susceptibility testing (eg, WalkAway and BD Phoenix), and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, which are commonly utilized in Japanese hospital laboratories. However, the impact of these methods could not be verified because information regarding the species identification practices at each hospital was not recorded in the JANIS system.

The breakdown of 4 anaerobic bacteria causing bacteremia showed little change from 2011 to 2020, except for an increase in Fusobacterium nucleatum from 36.0% to 44.5% (P < .001) (Supplementary Figure 1). This increase may be associated with colorectal cancer and colorectal surgeries [24]. On the other hand, the breakdown (Supplementary Figure 1C) showed a relative decrease in F. necrophorum, primarily associated with nongut infections [27, 28], from 17.8% in 2011 to 13.1% in 2020 (P < .001), which corresponds to the increase in F. nucleatum primarily associated with the gut.

We also analyzed the annual trends in resistance rates for various antimicrobials and compared the data from 2011–2015 with 2016–2020 (Figure 3, Table 2). Metronidazole (MNZ) was not included due to the absence of susceptibility data in the JANIS database, although MNZ injections have been used since 2014. Notably, high resistance rates of Bacteroides spp. and Prevotella spp. to ABPC were observed (>90% and >60%, respectively, in Figure 3). Eitel et al. have identified the cepA, cfxA, and cfiA genes as β-lactamase genes detected in the B. fragilis group. Tran et al. and Hashimoto et al. reported that the cfxA gene, specifically associated with resistance to ABPC, has been predominantly found in Bacteroides spp. isolates from Japanese patients [29, 30]. In contrast, carbapenems retained high activity against these 4 bacteria, with Bacteroides spp., Clostridium spp., Fusobacterium spp., and Prevotella spp. showing resistance rates of <4%, 0.5%, 1%, and 3%, respectively, to meropenem. Among the Bacteroides species, the resistance rate of B. fragilis to meropenem has been relatively high (up to 3.6%). It was reported that 9.6% of Bacteroides isolates in Kuwait and 4% in Belgium were resistant to meropenem, whereas none of the clinical isolates from Germany, Turkey, Hungary, Croatia, and the Netherlands showed resistance to carbapenems [31]. Snydman et al. reported that the resistance rate of carbapenems against B. fragilis in United States was low (1.1%–2.5%) [32]. In Canada, the resistance rate of gram-negative anaerobic bacteria to imipenem during 2012–2019 was reported to be <4% [33]. However, in China, 18.2% and 29.5% of B. fragilis isolates were found to be resistant to imipenem and meropenem, respectively, during 2009–2015 [34]. SBT/ABPC and TAZ/PIPC also showed low resistance rates against all 4 bacteria. These results are similar to those obtained in Canada, Argentina, and European countries [3, 35–38].

The resistance rate of B. thetaiotaomicron to CLDM, CTX, and CMZ was higher than that of B. fragilis (Table 2), consistent with previous reports of higher resistance to cephalosporins and CLDM in Korea, Canada, Argentina, and European countries [9, 35, 39, 40]. Kierzkowska et al. reported a higher resistance rate to CLDM in non-fragilis Bacteroides during 2013–2017 than during 2007–2012 [41]. The observed resistance to CLDM in Bacteroides, Fusobacterium, and Prevotella spp. was found to be related to the presence of ermF genes [42, 43]. This study revealed a significant increase in the resistance rate to CLDM by B. thetaiotaomicron. The resistance rate of C. perfringens to CLDM was higher (7.3%–11.6%) than to other antimicrobials. The resistance rates of Prevotella spp. to ABPC (62.8%), CLDM (29.8%), IPM, and SBT/ABPC were similar to those observed in Italy [3].

This study had several limitations. First, the JANIS surveillance system relies on voluntary participation. Thus, the number of participating hospitals can vary each year. Second, JANIS did not collect information on how species identification is conducted in each hospital. Third, JANIS has not collected strains but has rather collected data on species, specimens, and antimicrobial susceptibility reported by the participating hospitals. Fourth, drug susceptibility tests were conducted only for 30%–40% of the strains isolated in these hospitals, and there were no data on MNZ susceptibility tests. Additionally, each participating hospital used their own microbiological diagnostic and antimicrobial susceptibility testing instruments, which could introduce variability in the results.

Despite the limitations of this study, it provides the largest longitudinal overviews using national surveillance data of culturing and antimicrobial susceptibilities of 41 949 Bacteroides, 40 603 Clostridium, 7013 Fusobacterium, and 5428 Prevotella isolates from >2000 hospitals collected for 10 years. The incidence of anaerobic bacteremia, particularly B. fragilis, C. perfringens, and F. nucleatum, has been continuously increasing, which may be attributed to the rising number of patients with colorectal cancer or the advancing methods for species identification and susceptibility testing, requiring cautious interpretation. The resistance rate of B. thetaiotaomicron to CLDM and CTX was significantly increased. These results could help guide empirical therapies for anaerobic bacteremia, and the findings of increased anaerobic bacteremia and possible changes in susceptibility highlight the need for further extensive and diverse studies in this field.

Supplementary Material

ofad334_Supplementary_Data
Click here for additional data file. (1.5MB, jpeg)

Acknowledgments

We are grateful to all the hospitals that participated and contributed data to JANIS as well as Editage (www.editage.jp) for English language editing.

Financial support. This study was supported by the Research Program on Emerging and Re-emerging Infectious Diseases from the Japan Agency for Medical Research and Development under grant number 21fk0108604j0001 to M.S.

Contributor Information

Toshiki Kajihara, Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan.

Koji Yahara, Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan.

Norikazu Kitamura, Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan.

Aki Hirabayashi, Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan.

Yumiko Hosaka, Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan.

Motoyuki Sugai, Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan.

Supplementary Data

Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.

References

  • 1. Goldstein EJ. Anaerobic bacteremia. Clin Infect Dis 1996; 23(Suppl 1):S97–101. [DOI] [PubMed] [Google Scholar]
  • 2. Brook I. Spectrum and treatment of anaerobic infections. J Infect Chemother 2016; 22:1–13. [DOI] [PubMed] [Google Scholar]
  • 3. Di Bella S, Antonello RM, Sanson G, et al. Anaerobic bloodstream infections in Italy (ITANAEROBY): a 5-year retrospective nationwide survey. Anaerobe 2022; 75:102583. [DOI] [PubMed] [Google Scholar]
  • 4. Diekema DJ, Beekmann SE, Chapin KC, Morel KA, Munson E, Doern GV. Epidemiology and outcome of nosocomial and community-onset bloodstream infection. J Clin Microbiol 2003; 41:3655–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Lassmann B, Gustafson DR, Wood CM, Rosenblatt JE. Reemergence of anaerobic bacteremia. Clin Infect Dis 2007; 44:895–900. [DOI] [PubMed] [Google Scholar]
  • 6. Ng LSY, Kwang LL, Rao S, Tan TY. Anaerobic bacteraemia revisited: species and susceptibilities. Ann Acad Med Singap 2015; 44:13–8. [PubMed] [Google Scholar]
  • 7. Dorsher CW, Rosenblatt JE, Wilson WR, Ilstrup DM. Anaerobic bacteremia: decreasing rate over a 15-year period. Rev Infect Dis 1991; 13:633–6. [DOI] [PubMed] [Google Scholar]
  • 8. Hecht DW. Prevalence of antibiotic resistance in anaerobic bacteria: worrisome developments. Clin Infect Dis 2004; 39:92–7. [DOI] [PubMed] [Google Scholar]
  • 9. Karlowsky JA, Walkty AJ, Adam HJ, Baxter MR, Hoban DJ, Zhanel GG. Prevalence of antimicrobial resistance among clinical isolates of Bacteroides fragilis group in Canada in 2010-2011: CANWARD surveillance study. Antimicrob Agents Chemother 2012; 56:1247–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Veloo ACM, Baas WH, Haan FJ, Coco J, Rossen JW. Prevalence of antimicrobial resistance genes in Bacteroides spp. and Prevotella spp. Dutch clinical isolates. Clin Microbiol Infect 2019; 25:1156.e9–13. [DOI] [PubMed] [Google Scholar]
  • 11. Boyanova L, Kolarov R, Mitov I. Recent evolution of antibiotic resistance in the anaerobes as compared to previous decades. Anaerobe 2015; 31:4–10. [DOI] [PubMed] [Google Scholar]
  • 12. Cobo F, Rodriguez-Granger J, Perez-Zapata I, Sampedro A, Aliaga L, Navarro-Mari JM. Antimicrobial susceptibility and clinical findings of significant anaerobic bacteria in southern Spain. Anaerobe 2019; 59:49–53. [DOI] [PubMed] [Google Scholar]
  • 13. Nguyen MH, Yu VL, Morris AJ, et al. Antimicrobial resistance and clinical outcome of Bacteroides bacteremia: findings of a multicenter prospective observational trial. Clin Infect Dis 2000; 30:870–6. [DOI] [PubMed] [Google Scholar]
  • 14. Kajihara T, Yahara K, Hirabayashi A, et al. Japan nosocomial infections surveillance (JANIS): current status, international collaboration, and future directions for a comprehensive antimicrobial resistance surveillance system. Jpn J Infect Dis 2021; 74:87–96. [DOI] [PubMed] [Google Scholar]
  • 15. Shimura S, Watari H, Komatsu M, et al. Antimicrobial susceptibility surveillance of obligate anaerobic bacteria in the Kinki area. J Infect Chemother 2019; 25:837–44. [DOI] [PubMed] [Google Scholar]
  • 16. Wilson JR, Limaye AP. Risk factors for mortality in patients with anaerobic bacteremia. Eur J Clin Microbiol Infect Dis 2004; 23:310–6. [DOI] [PubMed] [Google Scholar]
  • 17. Kajihara T, Yahara K, Stelling J, et al. Comparison of de-duplication methods used by WHO Global Antimicrobial resistance Surveillance System (GLASS) and Japan Nosocomial Infections Surveillance (JANIS) in the surveillance of antimicrobial resistance. PLoS One 2020; 15:e0228234. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. World Health Organization . Global Antimicrobial Resistance Surveillance System (GLASS) Guide to Preparing Aggregated Antimicrobial Resistance Data Files. World Health Organization; 2016.
  • 19. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 1995; 57:289–300. [Google Scholar]
  • 20. Sarvari KP, Racz NB, Burian K. Epidemiology and antibiotic susceptibility in anaerobic bacteraemia: a 15-year retrospective study in south-eastern Hungary. Infect Dis 2022; 54:16–25. [DOI] [PubMed] [Google Scholar]
  • 21. Ngo JT, Parkins MD, Gregson DB, et al. Population-based assessment of the incidence, risk factors, and outcomes of anaerobic bloodstream infections. Infection 2013; 41:41–8. [DOI] [PubMed] [Google Scholar]
  • 22. Mason MR, Preshaw PM, Nagaraja HN, et al. The subgingival microbiome of clinically healthy current and never smokers. ISME J 2015; 9:268–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Odani S, Tabuchi T. Prevalence and denial of current tobacco product use: combustible and heated tobacco products, Japan, 2022. Prev Med Rep 2022; 30:102031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Kwong TNY, Wang X, Nakatsu G, et al. Association between bacteremia from specific microbes and subsequent diagnosis of colorectal cancer. Gastroenterology 2018; 155:383–8. [DOI] [PubMed] [Google Scholar]
  • 25. Foundation for Promotion of Cancer Research . Cancer statistics in Japan. 2022. Available at: https://ganjoho.jp/public/qa_links/report/statistics/pdf/cancer_statistics_2022.pdf. Accessed March 8, 2023.
  • 26. Marubashi S, Takahashi A, Kakeji Y, et al. Surgical outcomes in gastroenterological surgery in Japan: report of the National Clinical Database 2011-2019. Ann Gastroenterol Surg 2021; 5:639–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Kristensen LH, Prag J. Lemierre's syndrome and other disseminated Fusobacterium necrophorum infections in Denmark: a prospective epidemiological and clinical survey. Eur J Clin Microbiol Infect Dis 2008; 27:779–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Riordan T. Human infection with Fusobacterium necrophorum (necrobacillosis), with a focus on Lemierre's syndrome. Clin Microbiol Rev 2007; 20:622–59. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Hashimoto T, Hashinaga K, Komiya K, Hiramatsu K. Prevalence of antimicrobial resistant genes in Bacteroides spp. isolated in Oita Prefecture, Japan. J Infect Chemother 2023; 29:284–8. [DOI] [PubMed] [Google Scholar]
  • 30. Tran CM, Tanaka K, Watanabe K. PCR-based detection of resistance genes in anaerobic bacteria isolated from intra-abdominal infections. J Infect Chemother 2013; 19:279–90. [DOI] [PubMed] [Google Scholar]
  • 31. Veloo ACM, Tokman HB, Jean-Pierre H, et al. Antimicrobial susceptibility profiles of anaerobic bacteria, isolated from human clinical specimens, within different European and surrounding countries. A joint ESGAI study. Anaerobe 2020; 61:102111. [DOI] [PubMed] [Google Scholar]
  • 32. Snydman DR, Jacobus NV, McDermott LA, et al. Trends in antimicrobial resistance among Bacteroides species and Parabacteroides species in the United States from 2010-2012 with comparison to 2008-2009. Anaerobe 2017; 43:21–6. [DOI] [PubMed] [Google Scholar]
  • 33. Forbes JD, Kus JV, Patel SN. Antimicrobial susceptibility profiles of invasive isolates of anaerobic bacteria from a large Canadian reference laboratory: 2012-2019. Anaerobe 2021; 70:102386. [DOI] [PubMed] [Google Scholar]
  • 34. Gao Q, Wu S, Xu T, Zhao X, Huang H, Hu F. Emergence of carbapenem resistance in Bacteroides fragilis in China. Int J Antimicrob Agents 2019; 53:859–63. [DOI] [PubMed] [Google Scholar]
  • 35. Fernandez-Canigia L, Litterio M, Legaria MC, et al. First national survey of antibiotic susceptibility of the Bacteroides fragilis group: emerging resistance to carbapenems in Argentina. Antimicrob Agents Chemother 2012; 56:1309–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Seifert H, Dalhoff A; PRISMA Study Group . German multicentre survey of the antibiotic susceptibility of Bacteroides fragilis group and Prevotella species isolated from intra-abdominal infections: results from the PRISMA study. J Antimicrob Chemother 2010; 65:2405–10. [DOI] [PubMed] [Google Scholar]
  • 37. Soki J, Wybo I, Hajdu E, et al. A Europe-wide assessment of antibiotic resistance rates in Bacteroides and Parabacteroides isolates from intestinal microbiota of healthy subjects. Anaerobe 2020; 62:102182. [DOI] [PubMed] [Google Scholar]
  • 38. Wybo I, Van den Bossche D, Soetens O, et al. Fourth Belgian multicentre survey of antibiotic susceptibility of anaerobic bacteria. J Antimicrob Chemother 2014; 69:155–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Nagy E, Urban E, Nord CE, et al. Antimicrobial susceptibility of Bacteroides fragilis group isolates in Europe: 20 years of experience. Clin Microbiol Infect 2011; 17:371–9. [DOI] [PubMed] [Google Scholar]
  • 40. Yim J, Lee Y, Kim M, et al. Antimicrobial susceptibility of clinical isolates of Bacteroides fragilis group organisms recovered from 2009 to 2012 in a Korean hospital. Ann Lab Med 2015; 35:94–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Kierzkowska M, Majewska A, Mlynarczyk G. Trends and impact in antimicrobial resistance among Bacteroides and Parabacteroides species in 2007-2012 compared to 2013-2017. Microb Drug Resist 2020; 26:1452–7. [DOI] [PubMed] [Google Scholar]
  • 42. Kierzkowska M, Majewska A, Szymanek-Majchrzak K, et al. In vitro effect of clindamycin against Bacteroides and Parabacteroides isolates in Poland. J Glob Antimicrob Resist 2018; 13:49–52. [DOI] [PubMed] [Google Scholar]
  • 43. Sood A, Ray P, Angrup A. Anaerobic gram-negative bacteria: role as a reservoir of antibiotic resistance. Antibiotics (Basel) 2023; 12:942. [DOI] [PMC free article] [PubMed] [Google Scholar]

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