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〈Research Report〉

Comprehensive analysis of antibiotic-induced
agranulocytosis using the Japanese adverse
drug event report database
Yuki Asai, Takanori Yamamoto and Yasuharu Abe
Pharmacy, National Hospital Organization Mie Chuo Medical Center(Received for publication July 1, 2021)

Although infrequent, drug-induced agranulocytosis can be caused by antibiotics.
Here, we analyzed the Japanese Adverse Drug Event Report (JADER) database to
identify proﬁles of antibiotic-induced agranulocytosis.
We analyzed reports of agranulocytosis from April 2004 to January 2021 from the
JADER database. The reporting odds ratio and 95% conﬁdence interval were used todetect agranulocytosis signals. We evaluated the time-to-onset proﬁle and hazard
type using the Weibull shape parameter.
Ten out of 60 antibiotics showed signals for agranulocytosis; the reporting odds
ratios (95% conﬁdence intervals) for ampicillin/sulbactam, amikacin, cefmetazole,cefozopran, clindamycin, ciprofloxacin, imipenem/cilastatin, kanamycin,
teicoplanin, and vancomycin were 2.65 (1.79–3.80), 2.94 (1.91–4.34), 4.48 (2.27–
6.92), 2.77 (1.88–3.95), 1.64 (1.04–2.47), 2.01 (1.40–2.82), 2.78 (2.11–3.60), 6.05
(2.16–13.7), 2.05 (1.31–3.07), and 3.54 (2.73–4.54), respectively. The median timesto-onset of agranulocytosis for ampicillin/sulbactam, cefmetazole, cefozopran,clindamycin, imipenem/cilastatin, kanamycin, teicoplanin, and vancomycin were 20,
6, 10, 16, 12, 3, 18, and 13 days, respectively. The 95% conﬁdence intervals of the
Weibull shape parameter β for these antibiotics were over and excluded 1, indicatingthat the antibiotics were the wear out failure type.
We identiﬁed 10 antibiotics that may be associated with high risk ofagranulocytosis, suggesting that absolute neutrophil counts in patients taking thesedrugs should be monitored carefully in the clinical setting.

Corresponding author: Yuki Asai, Ph.D., Pharmacy, National Hospital Organization Mie Chuo Medical Center; 2158–5
Hisaimyojincho, Tsu, Mie 514–1101, Japan, Tel: ＋81–59–259–1211, Fax: ＋81–59–256–2651, E-mail: yuki0715asai@gmail.
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219（ 39 ）Introduction
Neutropenia is characterized as a decrease in the absolute neutrophil count, categorized as
mild (1,000–1,500/μL), moderate (500–1,000/μL), or severe (＜ 500/μL)1). The most severe form,
called agranulocytosis, is a life-threating condition in which the patient becomes highly susceptible to infectious diseases and shows a mortality rate of 10–20%2). Agranulocytosis can be caused
by a wide range of medications, including clozapine3) and antibiotics1), and infection control becomes particularly diﬃcult in patients with antibiotic-induced agranulocytosis. Furthermore, inpatients who continue to have a fever, it is necessary to switch to another antibiotic and add concomitant treatment with granulocyte-colony-stimulating factor4). Accordingly, there is an urgent
need to identify antibiotics that have a low risk of inducing agranulocytosis.
Although the mechanisms of antibiotic-induced agranulocytosis remain unknown, Weitzman
and Stossel5) speculated that antibiotic-induced agranulocytosis may be caused by opsonizing antineutrophil antibodies, i.e., an IgG or IgM immune-mediated hypersensitivity reaction. However,
because agranulocytosis is a rare adverse event (AE)6), it is diﬃcult to collect a suﬃcient numberof samples to conduct clinical studies. Recently, spontaneous reporting systems (SRSs) have beenshown to be useful for detection of rare AEs and used as primary tools in post marketing surveillance. In Japan, individual AEs are collected by healthcare workers at the Pharmaceuticals andMedical Devices Agency (PMDA). The Japanese Adverse Drug Event Report (JADER) database,which is available online, was established in April 2004 by the PMDA and reﬂects the realities ofclinical practice7). Thus, data mining using the JADER database can be used as a screening tool
for antibiotic-induced agranulocytosis.
In this study, we evaluated the expression proﬁles of antibiotic-induced agranulocytosis
using the JADER database.

Materials and Methods
Data source
The JADER database, including data from April 2004 to January 2021, was searched fromthe PMDA website (https://www.info.pmda.go.jp/fukusayoudb/CsvDownload.jsp). The JADER
database consisted of four data tables, as follows: 1) DEMO (patientsʼ demographic information,
including sex, age, and weight); 2) DRUG (drug name, causality, etc.); 3) REAC (AEs, outcomes,etc.); and 4) HIST (medical history, primary illness, etc.). We created relational database from thefour data tables according to patient identiﬁcation numbers using Microsoft Access 2019 (Microsoft, Redmond, WA, USA). Because duplicate reports in the SRS database may aﬀect the evaluation from the relational database, we extracted only the latest of AE reports based on the DEMO
ﬁle. Data with inaccurate dates were excluded.

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Drugs and AE names
The 60 antibiotics analyzed in the current study are shown in Table 1. We focused on agranulocytosis, the most life-threatening type of neutropenia. Agranulocytosis was deﬁned using thepreferred term (PT) code (10001507) according to the Medical Dictionary for Regulatory Activities version 23.1J.
Data analysis
We selected the reporting odds ratio (ROR) for the detection of signals associated with antibiotic-induced agranulocytosis. As shown Fig. 1, the ROR and 95% conﬁdence interval (95% CI)
were calculated from a two-by-two contingency table. Signal detection was deﬁned as follows:
ROR greater than 1, lower limit of the corresponding 95% CI greater than 1, and number of cases
three or more8). Conversely, the condition of ROR less than 1 was considered no exposure-event
association. The adjusted odds ratio was not calculated by multivariate analysis because the data
mining by JADER cannot evaluate risk factors for the development of agranulocytosis. Staticalanalysis was conducted with SPSS Statistics version 27 (IBM Japan, Tokyo, Japan). In addition,
the clinical outcomes from agranulocytosis develops were investigated for signal-detected antibiotics.
The median of period until agranulocytosis onset from the time of ﬁrst administration foreach patient was evaluated using the Weibull shape parameter (WSP), which does not require areference population9). The elapsed time from the ﬁrst administration was calculated by subtracting the ﬁrst administration date from the agranulocytosis expression date. Fifty cases were excluded because the date of ﬁrst administration or onset of agranulocytosis was not available. The
combination of WSP β and 95% CI could be interpreted as follows: when β was equal to 1 (random failure) and 95% CI of β included the 1, the hazard was estimated to be constant over time;
if β was greater than 1 (wear out failure) and the 95% CI (lower) of β exceeded 1, the hazard wasconsidered to increase over time; if β was less than 1 (early failure) and the 95% CI (upper) of βwas less than 1, the hazard was considered to increase at an early stage and then decrease. Timeto-onset analyses were performed using JMP version 15 software (SAS Institute, Cary, NC,
USA).
Ethics approval and consent to participate
Ethics approval and consent to participate were not applicable to this study because we usedpublicly available voluntarily provided reports.

Results
As shown in Fig. 2, we extracted 72,723 reports of suspected AEs related to antibiotic treat-Sept. 2021

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221（ 41 ）Fig. 1. Two-by-two contingency table for the calculation of reporting odds ratios

Fig. 2. Flowchart for the construction of data analysis tables from the JADER databasement among the 1,048,576 reports in the JADER database between April 2004 and January 2021.
The number of reports of agranulocytosis was 3,221. As shown in Table 1, 10 out of 60 antibiotics were detected as signals; the RORs (95% CIs) for ampicillin/sulbactam, amikacin, cefmetazole, cefozopran, clindamycin, ciproﬂoxacin, imipenem/cilastatin, kanamycin, teicoplanin,and vancomycin were 2.65 (1.79–3.80), 2.94 (1.91–4.34), 4.48 (2.27–6.92), 2.77 (1.88–3.95),

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Table 1. Number of reports and reporting odds ratios of agranulocytosis associated with antibiotics
Group

Antibiotics

Total (n)Case (n)Non-case (n)

ROR

95%CI

Anti-MRSA agents

ArbekacinLinezolid
Teicoplanin
Vancomycin
Amphotericin B
Fluconazole
Flucytosine
Fos-ﬂuconazole
Itraconazole
Ketoconazole
MicafunginMiconazole
Voriconazole
Amikacin
Dibekacin
Gentamicin
Kanamycin
Streptomycin
Ciproﬂoxacin
Gatiﬂoxacin
Levoﬂoxacin
Norﬂoxacin
Pazuﬂoxacin
Tosuﬂoxacin
Azithromycin
Clarithromycin
Erythromycin
Imipenem/cilastatin
Doripenem
Biapenem
Meropenem
Doxycycline
Minocycline
Acyclovir
Valaciclovir
Amoxicillin
Amoxicillin/clavulanate
Ampicillin
Ampicillin/sulbactam
Benzylpenicillin
Faropenem
Piperacillin
Piperacillin/tazobactam
Cefaclor
Cefazolin
Cefcapene
Cefditoren
Cefepime
Cefmetazole
Cefoperazone/sulbactam
Cefotaxime
Cefotiam
CefozopranCeftazidime
Cefteram
Ceftriaxone
Cephalexin
Flomoxef
Clindamycin
Trimethoprim/sulfamethoxazole

435
74
1,356
2,428
1,055
2,960
22
2,002
1,646
125
2,482
351
378
1,037
9
467
113
183
2,005
673
4,267
111
1,072
448
1,508
3,921
651
2,734
18
535
3,651
23
1,908
2,012
1,927
805
59
341
1,365
18
187
1,670
535
439
1,446
2,191
541
1,572
561
1,565
259
1,884
1,351
1,408
156
1,415
67
959
1,612
5,730

3
0
25
72
0
22
0
24
4
0
3
0
0
27
0
4
6
0
36
0
15
0
3
1
5
17
1
65
0
4
33
0
25
8
1
1
0
0
32
0
1
14
6
3
14
4
2
9
22
12
3
18
33
5
2
12
0
11
24
47

432
74
1,331
2,356
1,055
2,938
22
1,978
1,642
125
2,479
351
378
1,010
9
463
107
183
1,969
673
4,252
111
1,069
447
1,503
3,904
650
2,669
18
531
3,618
23
1,883
2,004
1,926
804
59
341
1,333
18
186
1,656
529
436
1,432
2,187
539
1,563
539
1,553
256
1,866
1,318
1,403
154
1,403
67
948
1,588
5,683

0.74
NA
2.05
3.54
NA
0.80
NA
1.31
0.26
NA
0.13
NA
NA
2.94
NA
0.92
6.05
NA
2.01
NA
0.36
NA
0.30
0.24
0.35
0.45
0.16
2.78
NA
0.81
0.98
NA
1.44
0.42
0.05
0.13
NA
NA
2.65
NA
0.58
0.90
1.22
0.74
1.05
0.19
0.40
0.61
4.48
0.82
1.26
1.03
2.77
0.38
1.39
0.91
NA
1.25
1.64
0.88

0.15–2.19
0.00–5.48
1.31–3.07
2.73–4.54
0.00–0.37
0.49–1.22
0.00–19.6
0.83–1.97
0.07–0.66
0.00–3.21
0.03–2.40
0.00–1.13
0.00–1.04
1.91–4.34
0.00–54.3
0.25–2.40
2.16–13.7
0.00–2.18
1.40–2.82
0.00–0.58
0.20–0.61
0.00–3.62
0.06–1.34
0.01–0.92
0.11–0.83
0.26–0.73
0.004–0.92
2.11–3.60
0.00–24.41
0.22–2.08
0.67–1.39
0.00–18.67
0.92–2.15
0.18–0.84
0.00–10.30
0.003–0.74
0.00–6.92
0.00–1.16
1.79–3.80
0.00–24.43
0.01–3.26
0.50–1.53
0.44–2.68
0.15–2.17
0.57–1.78
0.05–0.49
0.01–1.44
0.28–1.17
2.77–6.92
0.43–1.45
0.26–3.73
0.61–1.65
1.88–3.95
0.12–0.89
0.17–5.13
0.47–1.61
0.00–6.07
0.62–2.26
1.04–2.47
0.64–1.18

Anti-fungal agents

Aminoglycoside

Quinolone

Macrolide
Carbapenem

Tetracycline
Anti-viral agents
Penicillin

Cephalosporin

Lincomycin
Other

NA; not available. MRSA: methicillin-resistant Staphylococcus aureus. ROR: reporting odds ratio. 95%CI: 95%
conﬁdence interval.

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Table 2. Clinical outcomes after the onset of antibiotic-induced agranulocytosis
Total (n)Amikacin
Ampicillin/sulbactam
Cefmetazole
CefozopranCiproﬂoxacin
Clindamycin
Imipenem/cilastatin
Kanamycin
Teicoplanin
Vancomycin

Outcomes (n)RecoveryUnrecovered

Death

Unknown

27
29
19
26
21
22
58
3
25
71

0
0
0
1
0
0
0
0
0
0

0
3
2
6
15
2
7
3
0
1

0
0
1
0
0
0
0
0
0
0

27
32
22
33
36
24
65
6
25
72

Table 3. Time-to-onset analysis of antibiotics using Weibull distributions
Antibiotics

Case
(n)

Median Day(25–75%)

Amikacin
Ampicillin/sulbactam
Cefmetazole
CefozopranCiproﬂoxacin
Clindamycin
Imipenem/cilastatin
Kanamycin
Teicoplanin
Vancomycin

25
16
22
25
35
22
56
6
21
64

2 (1–3)20 (14–29)
6 (4–8)10 (8–17)
4 (1–8.5)
16 (10–23)
12 (9–23)
3 (2–4)18 (6–20)
13 (9–20)

Scale parameter: αScale parameter: βα

95% CIβ

95% CI

6.76
23.37
6.59
12.55
7.32
18.32
16.56
3.36
16.49
17.42

3.87–11.44
18.7–28.8
6.62–7.68
9.32–12.65
4.73–11.10
15.6–21.3
14.16–19.27
2.47–4.48
12.76–19.53
15.40–19.63

0.80
2.57
2.95
1.49
0.85
2.98
1.81
3.46
2.74
2.17

0.59–1.04
1.66–3.70
2.09–3.90
1.03–2.06
0.64–1.07
2.06–4.12
1.43–2.24
1.61–6.35
1.82–3.95
1.78–2.59

Pattern
Random failure
Wear out failure
Wear out failure
Wear out failure
Random failure
Wear out failure
Wear out failure
Wear out failure
Wear out failure
Wear out failure0＜β＜1, early failure; β＝1, random failure; β＞1, wear out failure.
95% CI: 95% conﬁdence interval.

1.64 (1.04–2.47), 2.01 (1.40–2.82), 2.78 (2.11–3.60), 6.05 (2.16–13.7), 2.05 (1.31–3.07), and3.54 (2.73–4.54), respectively. The clinical outcomes after the onset of antibiotic-induced agranulocytosis were evaluated (Table 2). Most antibiotics were found to be recovered from agranulocytosis.
For the time-to-onset analysis, we extracted 292 cases for the 10 antibiotics with signal detection (Table 3). The median durations (interquartile ranges) of agranulocytosis onset following
treatment with amikacin, cefmetazole, ciproﬂoxacin, and kanamycin were within 1 week of theﬁrst treatment. Although the 95% CIs of WSP β for eight antibiotics (excluding amikacin and ciproﬂoxacin) were over and excluded 1, indicating a wear out failure type, the proﬁles of amikacinand ciproﬂoxacin were consistent with the random failure type (Table 3).

Discussion
Since the occurrence of agranulocytosis is rare, retrospective study are diﬃcult to evaluate
the proﬁles of antibiotic-induced agranulocytosis. Therefore, data mining may be appropriate224（ 44 ）THE JAPANESE JOURNAL OF ANTIBIOTICS

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method as a pilot study for developing antibiotic-induced agranulocytosis.
Because neutrophils are produced in bone marrow, we speculated that antibiotics with highmigration to bone marrow may have a high risk of inducing agranulocytosis before data mining.
However, signals were not detected for antibiotics with high cerebrospinal ﬂuid transferability,
such as ceftriaxone10) and cefotaxime11), whereas teicoplanin12), an antibiotic with poor cerebrospinal ﬂuid transferability, was detected. Therefore, these ﬁndings suggested that the risk ofagranulocytosis could not be clariﬁed by analysis of migration to the bone marrow only. A retrospective study reported that the development of vancomycin-induced neutropenia was not associated with the dosage, trough concentration, or administration period13). Although other antibiotics
also need to be investigated, antibiotic-induced agranulocytosis may not be a cumulative toxicity.
The incidence of neutropenia induced by vancomycin is approximately 2–18%14,15). In contrast, Smith et al. reported that linezolid, an anti-methicillin-resistant Staphylococcus aureus(MRSA) agent, may be safe and eﬀective for the treatment of febrile neutropenia16). In addition,
carbapenems targeting Pseudomonas aeruginosa are empirically used for the treatment of febrileneutropenia17), indicating that when using antibiotics with anti-Pseudomonas aeruginosa or antiMRSA activity in the empirical treatment of high-risk patients, such as those with febrile neutropenia, it may be better to preferentially use antibiotics with the same spectrum for which no signal was detected in this study.
In the clinical setting, aminoglycosides are often administered with β-lactam antibiotics to
induce synergistic eﬀects18,19). Moreover, infective endocarditis caused by MRSA may be treatedwith vancomycin or teicoplanin in combination with aminoglycosides20). In the current study, because amikacin and kanamycin were detected as signals, we speculate that it may be better to use
gentamicin as the aminoglycoside in combination therapy.
It was suggested that even if agranulocytosis develops, it may be recovered by discontinuing
the causative drug (Table 2). Because the data mining method using the JADER database does
not include the number of all patients who received antibiotics, the recovery rate of agranulocytosis cannot be compared among antibiotics. On the other hand, based on analysis using medical receipt data, the recovery rate can be calculated and may be compared among antibiotics. Thisshould be considered to be an area for future study.
In recent reports of SRS data mining, WSP analysis has been performed to evaluate the timeto-onset data for target AEs9). Accordingly, time-to-onset analysis using WSP is likely to be a useful tool for determination of the speciﬁc safety monitoring period for agranulocytosis. The mechanisms of agranulocytosis involve immune responses toward opsonizing antineutrophil
antibodies5) or drugs themselves, suggesting that the diﬀerences in the time-of-onset of agranulocytosis may occur through diﬀerent mechanisms.
Data mining using the JADER database has some limitations that should be considered because the JADER database has several biases. First, because the JADER database does not con-

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225（ 45 ）tain information for control patients, the intensity of RORs cannot be quantiﬁed and comparedamong antibiotics. Second, there are also some reporting biases, such as under-reporting and lackof data. Third, the number of reports was small and may have been underestimated because thePT codes 10018687 (granulocytopenia) and 10018681 (granulocyte count decreased) were not included in the current study. Fourth, because agranulocytosis may be induced by severe infections21), the agranulocytosis reported by SRS may not be caused by administration of antibiotics.
Fifth, data mining methods cannot evaluate comorbidities that are involved in the risk of developing agranulocytosis.
In conclusion, this comprehensive analysis was the ﬁrst report evaluating the incidences ofantibiotic-induced agranulocytosis. Despite the various limitations of using the JADER database,
we identiﬁed 10 antibiotics that may be associated with high risk of agranulocytosis, suggestingthat absolute neutrophil counts in patients taking these drugs should be monitored carefully in theclinical setting. Finally, further clinical studies are needed to verify the mechanisms throughwhich ampicillin/sulbactam, amikacin, cefmetazole, cefozopran, clindamycin, ciproﬂoxacin, imipenem/cilastatin, kanamycin, teicoplanin, and vancomycin may induce agranulocytosis. The difference in the onset time may have been related to the variations in pharmacokinetics of each antibiotic and the onset mechanism of agranulocytosis; however, the details are unknown, andfurther research is needed.
Acknowledgments
Not applicable.
Competing interests
The authors declare that they have no competing interests.

References
1） Boxer LA: How to approach neutropenia. Hematology Am Soc Hematol Educ Program. 2012;2012: 174–82.
2） Andrès E, Maloisel F, Kurtz JE, et al.: Modern management of non-chemotherapy drug-induced
agranulocytosis: a monocentric cohort study of 90 cases and review of the literature. Eur J Intern
Med. 2002; 13: 324–8.
3） Mijovic A, MacCabe JH: Clozapine-induced agranulocytosis. Ann Hematol. 2020; 99: 2477–82.
4） Genchanok Y, Tolu SS, Wang H, Arora S: Agranulocytosis from outpatient antimicrobial treatment with ceftriaxone: a case report. Perm J. 2019; 23: 18–190.
5） Weitzman SA, Stossel TP: Drug-induced immunological neutropenia. Lancet. 1978; 1: 1068–72.
6） Olaison L, Belin L, Hogevik H, Alestig K: Incidence of beta-lactam-induced delayed hypersensitivity and neutropenia during treatment of infective endocarditis. Arch Intern Med. 1999; 159:
607–15.
7） Noguchi Y, Ueno A, Otsubo M, et al.: A simple method for exploring adverse drug events in pa-

226（ 46 ）THE JAPANESE JOURNAL OF ANTIBIOTICS

74―3

Sept. 2021

tients with diﬀerent primary diseases using spontaneous reporting system. BMC Bioinformatics.
2018; 19: 124.
8） Hashiguchi M, Imai S, Uehara K, Maruyama J, Shimizu M, Mochizuki M: Factors aﬀecting thetiming of signal detection of adverse drug reactions. PLoS One. 2015; 10: e0144263.
9） Sauzet O, Carvajal A, Escudero A, Molokhia M, Cornelius VR: Illustration of the weibull shapeparameter signal detection tool using electronic healthcare record data. Drug Saf. 2013; 36: 995–
1006.
10） Kotani A, Hirai J, Hamada Y, Fujita J, Hakamata H. Determination of ceftriaxone concentration inhuman cerebrospinal ﬂuid by high-performance liquid chromatography with UV detection. J
Chromatogr B Analyt Technol Biomed Life Sci. 2019; 1124: 161–4.
11） Chen XK, Shi HY, Leroux S, et al.: Penetration of cefotaxime into cerebrospinal ﬂuid in Neonates
and Young Infants. Antimicrob Agents Chemother. 2018; 62: e02448-17.
12） Wilson AP: Clinical pharmacokinetics of teicoplanin. Clin Pharmacokinet. 2000; 39: 167–83.
13） Pai MP, Mercier RC, Koster SA: Epidemiology of vancomycin-induced neutropenia in patients
receiving home intravenous infusion therapy. Ann Pharmacother. 2006; 40: 224–8.
14） Farber BF, Moellering RC Jr: Retrospective study of the toxicity of preparations of vancomycin
from 1974 to 1981. Antimicrob Agents Chemother. 1983; 23: 138–41.
15） Morris A, Ward C: High incidence of vancomycin-associated leucopenia and neutropenia in a cardiothoracic surgical unit. J Infect. 1991; 22: 217–23.
16） Smith PF, Birmingham MC, Noskin GA, et al.: Safety, eﬃcacy and pharmacokinetics of linezolid
for treatment of resistant Gram-positive infections in cancer patients with neutropenia. Ann
Oncol. 2003; 14: 795–801.
17） Khoo AL, Zhao YJ, Teng M, et al.: Evaluation of a risk-guided strategy for empirical carbapenem
use in febrile neutropenia. Int J Antimicrob Agents. 2018; 52: 350–7.
18） Kurtz TO, Winston DJ, Bruckner DA, Martin WJ: Comparative in vitro synergistic activity of
new beta-lactam antimicrobial agents and amikacin against Pseudomonas aeruginosa and Serratia
marcescens. Antimicrob Agents Chemother. 1981; 20: 139–243.
19） Scudamore RA, Goldner M: Penetration of the outer membrane of Pseudomonas aeruginosa bysynergistic combinations of beta-lactam and aminoglycoside antibiotics. Antimicrob Agents Chemother. 1982; 21: 1007–10.
20） Baddour LM, Wilson WR, Bayer AS, et al.: Infective endocarditis in adults: diagnosis, antimicrobial therapy, and management of complications: a scientiﬁc statement for healthcare professionals
from the American Heart Association. Circulation. 2015; 132: 1435–86.
21） Shi R, Zhou Q, Fang R, Xiong X, Wang Q: Severe acute pancreatitis with blood infection by Candida glabrata complicated severe agranulocytosis: a case report. BMC Infect Dis. 2018; 18: 706.