Back to Journals » Infection and Drug Resistance » Volume 14

Longitudinal Study of the Drug Resistance in Klebsiella pneumoniae of a Tertiary Hospital, China: Phenotypic Epidemiology Analysis (2013–2018)

Authors Pei N, Liu Q, Cheng X, Liang T, Jian Z, Wang S, Zhong Y, He J, Zhou M, Kristiansen K, Chen W, Liu W, Li J

Received 2 December 2020

Accepted for publication 14 January 2021

Published 17 February 2021 Volume 2021:14 Pages 613—626


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Suresh Antony

Na Pei,1– 3,* Qingxia Liu,4,* Xinyi Cheng,1,5,6,* Tianzhu Liang,1,3 Zijuan Jian,4 Siyi Wang,4 Yiming Zhong,4 Jingxuan He,4 Mao Zhou,4 Karsten Kristiansen,1,2 Weijun Chen,1,6,7 Wenen Liu,4 Junhua Li1,3

1BGI-Shenzhen, Shenzhen, 518083, People’s Republic of China; 2Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Copenhagen, Denmark; 3Shenzhen Key Laboratory of Unknown Pathogen Identification, Shenzhen, 518083, People’s Republic of China; 4Department of Clinical Laboratory, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People’s Republic of China; 5School of Biology and Biological Engineering, South China University of Technology, Guangzhou, People’s Republic of China; 6BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, People’s Republic of China; 7BGI PathoGenesis Pharmaceutical Technology, Shenzhen, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Junhua Li
BGI-Shenzhen, Shenzhen, 518083, People’s Republic of China
Tel +86 13929566296
Wenen Liu
Department of Clinical Laboratory, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, People’s Republic of China
Tel +86 13973128689

Purpose: Multi-drug resistant Klebsiella pneumoniae (MDR KP) is spreading worldwide and has posed a huge medical burden to public health. However, studies on drug resistance surveillance of KP, especially MDR KP, with a large longitudinal sample size in a tertiary hospital are rare. This study aims to investigate phenotypic epidemiology characteristics of 4128 KP isolates in a Chinese tertiary hospital covering a period of 5 years.
Methods: All the KP clinical isolates were retrospectively collected from a tertiary hospital in Hunan province of China from Jan 5, 2013 to Jul 24, 2018. All the isolates were identified by MALDI-TOF MS analysis. Twenty-four antimicrobial agents were tested by antimicrobial susceptibility testing. Fisher exact test and logistic regression were used to analyze the association between clinical factors and antimicrobial non-susceptibility for seven second-choice antimicrobials.
Results: A total of 4128 KP isolates were collected in our study. The non-susceptible rates (NSRs) to ertapenem, imipenem and tigecycline increased considerably from 2013 to 2018 (13.6% to 28.6%, 10.1% to 28.9%, 10.8% to 46.5%, respectively). Amikacin presents the lowest NSR among 3 aminoglycosides (3.8– 22.8%). The multi-drug NSRs among KP isolates to second-choice antimicrobials (88.6– 100%) were higher than to all drugs (68.0%). The NSRs varied significantly among departments and sample sources. Higher ETP/IPM/AK NSRs (39.8/39.7/30.6%) were observed in Intensive Care Unit, and ETP/IPM non-susceptible isolates tended to distribute in cerebrospinal fluid. From 2015 to 2017, the NSRs of ETP, IPM, and AK showed an opposite trend of seasonal fluctuations to SXT.
Conclusion: Higher multi-drug resistance (MDR) rates were observed in KP isolates to second-choice antimicrobials than to others, among which MDR rates to carbapenems or AK are the highest. A unique pattern of MIC and time distributions of MDR were observed. Clinical factors including gender were correlated with MDR rates of KP. Isolates in ICU and CSF showed higher NSRs in carbapenems which should be paid more attention to, and temporal distribution of NSRs was observed.

Keywords: Klebsiella pneumoniae, drug resistance, NSR, phenotypic epidemiology


Klebsiella pneumoniae, a member of the Enterobacteriaceae family, is one of the main pathogenic bacteria that causes hospital and community acquired infections. K. pneumoniae commonly infects the urinary tract, respiratory tract, surgical sites, as well as the bloodstream and can cause severe diseases such as pneumonia and sepsis.1 According to the safety, efficacy, resistance, and price of antibiotics, antibiotics can be classified into non-restricted use (first-choice antimicrobials), restricted use (second-choice antimicrobials), and special use antimicrobials. First-choice antimicrobials have good efficacy and can be selected by doctors at all levels according to their needs. However, second-choice antimicrobials are usually allowed for use by the attending physician when patients are allergic or resistant to the first-choice antimicrobials. In recent years, the emergence of carbapenem-resistant Enterobacteriaceae (CRE) and extended-spectrum β-lactamase (ESBL) poses a global healthcare challenge. At the same time, due to the increasing use of other second-choice antimicrobials against carbapenem-resistant K. pneumoniae (CRKP) and extended-spectrum β-lactam producing K. pneumoniae (ESBL-KP), the corresponding drug resistance rates have also increased.2,3 Infections caused by these so-called superbugs are associated with high mortality because therapeutic options are limited.4–9

Carbapenems are especially effective in the treatment of Enterobacteriaceae bacterial infections that produce ultra-broad-spectrum beta-lactamase and cephalosporinase, and plays an important role in the treatment of multi-drug-resistant bacterial infections.10 However, with the widespread and even clinician unreasonable use of carbapenems in recent years, the detection rate of CRKP increased year by year, posing a challenge to the clinical treatment. In recent decades, sporadic CRKP events and outbreaks have been reported in many countries and regions, including China.11–13

Other commonly selected drugs for the treatment of MDR KP include tigecycline (TGC), colistin, sulfamethoxazole-trimethoprim (SXT) and aminoglycosides such as amikacin (AK), gentamicin (GEN) and tobramycin (TOB). These antimicrobials generally have a lower resistance rate than first-choice antimicrobials and carbapenems in MDR KP infection. Tigecycline is a novel broad-spectrum antimicrobial approved by FDA in 2005, with excellent activity against all Gram-positive and nearly all Gram-negative bacterium.14–17 Discovered in the 20th century, aminoglycosides are potent against various Gram-positive and negative bacterium, especially against Enterobacteriaceae. Aminoglycosides were substituted by cephalosporins, fluoroquinolones, and carbapenems for their toxicity and side effects since the 1980s, but received a renewed interest in recent years for the potential to treat multi-drug resistance (MDR) bacterial infections.18

The Chinese government pays great attention to the usage and resistance of carbapenems. According to the monitoring results of 192 tertiary hospitals in China, the consumption of carbapenems constantly increased from 1.83 defined daily doses (DDDs) per 100 bed days in 2011 to 3.38 DDDs per 100 bed days in 2017.19 China Antimicrobial Resistance Surveillance System (CARSS) reported that the detection rate of CRKP in China increased from 4.9% in 2013 to 10.7% in 2018.20 However, little is known about the department and temporal characteristics of the infection of other second-choice antimicrobials resistant KP in recent years in China. Longitudinal large-scale study can be useful for monitoring the drug resistance and controlling thenosocomial infections. In our study, we collected K. pneumoniae isolates during 2013–2018 from a tertiary hospital with 3500 beds and 76 wards in Hunan, China, investigating the multi-drug and second-line antimicrobial non-susceptible rates (NSRs) of isolates from various departments, sample types, and seasonal distributions, in order to provide a comprehensive landscape of the department-temporal characteristic of resistant KP infections in a typical tertiary hospital in China.


Bacterial Isolates and Identification

4128 Klebsiella pneumoniae isolates were recovered from the clinic laboratory of a tertiary hospital in Hunan province of China, covering all clinical samples tested positive for KP from January 5, 2013 to July 24, 2018. These isolates were continuously and unbiasedly collected, covering all patients who tested positive for KP in the hospital during this period. To avoid duplication and phenotypic changes, only the first strain, isolated from various samples of the same patient, was included. All isolates were identified by MALDI-TOF MS analysis. The isolates mainly came from ten departments in the hospital. Samples were taken from a variety of locations, including respiratory secretion, blood, drainage and puncture fluid, urine, wound secretion, digestive system secretion, abscess, tractus genitalis secretion, CSF, stool, and other sites. The patient information is managed through the hospital information management system. All patients will be given an ID number when they are admitted to the hospital, through which age and sex of the patients, date of sample submission, sample type, hospitalization, and department were collected.

Antimicrobial Susceptibility Test

All isolates were tested experimentally for their susceptibility to 24 common antimicrobial agents. The susceptibility to 20 antimicrobial agents was tested by the Vitek 2 system (bio Mérieux, Marcy l’Étoile, France) to determine the minimum inhibitory concentration (MIC). Susceptibility to other four antimicrobial agents, including cefuroxime (CXM), cefoperazone/sulbactam (SCF), tigecycline (TGC) and cefazolin (CFZ), was determined by the size of inhibition zone in Kirby-Bauer disk diffusion test. Bacteria were cultured on 5% sheep blood agar (BA) (Oxoid, UK) overnight at 37°C. At least 4 colonies were picked and emulsified in 0.8% saline to achieve a turbidity of 0.5 McFarland. The suspension was streaked onto the surface of Mueller-Hinton agar using a sterile cotton swab. Discs supplemented with antibiotics were placed onto the surface of agar plate using an automatic disc dispenser. The culture was then incubated at 37°C for 16 to18 hours before zone diameters were read. Antibiotic agents were classified into three categories as resistant, intermediate, or susceptible according to the CLSI guideline 2018. The MICs and inhibitory zone diameter (IZD) of different antimicrobials were interpreted using the CLSI 2018 breakpoints standards. Escherichia coli ATCC25922 and Pseudomonas aeruginosa ATCC27853 were used as controls.

Data Process and Statistical Analysis

Some patients were sampled multiple times for clinical purposes. As for the patients with multiple samples, the isolates with identical antibiotic phenotypes were considered to be duplicates, among which the isolate owns the most complete antimicrobial susceptibility test (AST) information was retained, and others were excluded from the dataset. If all isolates among the duplicates have equally complete AST information, the earliest isolate collected would be retained.

The category of antimicrobial agents (Supplementary Table 1) and the judgment of MDR KP were based on an international expert proposal for interim standard definitions for acquired resistance.21 Univariate analysis of clinical risk factors of non-susceptibility was finished by Monte Carlo simulation fisher exact test (repeated 200,000 times). Multivariate analysis was managed by logistic regression in order to avoid false correlations between the analyzed clinical factors. All P-values were two-tailed, and a statistical significance was considered when P < 0.05.


Clinical Characteristics of Klebsiella pneumoniae Isolates

Of the 4128 KP isolates, 509 isolates were regarded as duplicates according to their antimicrobial susceptibility results. 3619 non-redundant isolates were left after removing the duplicates (Supplementary Figure 1). These isolates were continuously and unbiasedly collected, covering all patients who tested positive for KP in the hospital from January 5, 2013, to July 24, 2018. The sample sizes of each year are shown in Table 1. Most samples (76.26%) were collected from 2015 to 2017 and isolates were only collected for half a year in 2018.

Table 1 Clinical Characteristics of 3619 Isolates

Among the 3619 isolates, the largest number of isolates were from the patients in intensive care unit (ICU) (n = 998, 27.6%), followed by surgery (n = 865, 23.9%), medicine (n = 625, 17.3%), and pediatrics (n = 404, 11.2%). Obstetrics and gynecology have the least number of isolates (n = 45.1.2%), five isolates had no department information (Table 1). Sample type distribution was also investigated. The majority of isolates came from respiratory tract (n = 2020, 55.8%), a reported main site of KP infection, followed by blood samples (n = 484, 13.4%), puncture/drainage fluid (n = 351, 9.7%), urine (n = 278, 7.7%), and stool had the lowest number of isolates among all sample types (n = 12, 0.3%).

The patients who were sampled had a wide range of age distribution (0–98 years old), with a median of 52. Among them, 2478 (68.5%) of the patients were male, while 1141 (31.5%) were female. For patients with admission information (n = 3335), the hospitalization rate was 60.8% (Table 1).

The Characteristics of Antimicrobial Resistance and MDR KP During 2013 to 2018

The resistance/intermediary/sensitive rates for 24 antimicrobial agents were calculated from 2013 to 2018, covering 14 antimicrobial categories (Table 2). The resistance rates toward ampicillin (AMP) were close to 100% in each year, which may be led by the intrinsic resistance of Klebsiella pneumoniae.22 Not considering the AMP, Nitrofurantoin showed the highest NSR in all categories (83.1% in total), followed by 1st and 2nd generation cephalosporins (81.9% for CFZ, 75.8% for CXM, in total) and Penicillins + β‐lactamase inhibitors (60.2% for AMC, 64.9% for SAM, in total). NSRs to 3rd and 4th generation cephalosporins were lower than 50% during 2013–2018, except CRO (58.6% in total).

Table 2 Sample Distribution (R%/I%/S%)a of Klebsiella pneumoniae by Year

Without regard to the intrinsic AMP resistance, 3355 (92.7%) samples were non-susceptible to at least one antimicrobial category, and 2462 (68.0%) samples had multi-drug resistance (non‐susceptible to ≥1 agent in ≥3 antimicrobial categories) (Figure 1A). Among all antimicrobial agents with antimicrobial susceptibility testing results, seven commonly used antimicrobials for KP treatment were selected for in-depth analysis, namely, 2 carbapenems (including ETP and IPM), 3 aminoglycosides (including AK, GEN, and TOB), SXT, and TGC. Isolates non-susceptible to the second-choice antimicrobials overall showed higher multidrug-resistant rates (88.6–100%), among which the isolates non-susceptible to carbapenems or AK showed stronger multidrug-resistance than those to other second-choice antimicrobials, with over 98% isolates being non-susceptible to >5 antimicrobial categories and over 30% non-susceptible to >10 categories (Figure 1B).

Figure 1 Distribution of multidrug-resistance patterns among KP isolates. The sample size distribution of KP in 24 common antimicrobial agents among all 3619 analyzed isolates (A) and percentage of isolates non-susceptible to seven second-choice antimicrobials in different amount antimicrobial categories (B). MDR KP was defined as the isolates non-susceptible to three or more than three categories. As an intrinsic resistance of KP, the resistance towards AMP was excluded from this analysis.

Abbreviations: ETP, ertapenem; IPM, imipenem; AK, amikacin; GEN, gentamicin; TOB, tobramycin; SXT, trimethoprim-sulfamethoxazole; TGC, tigecycline.

MICs results of six second-choice antimicrobials are shown in Figure 2. We discovered that the MIC values tended to distribute in low range or high range, rather than in the middle range. 876 (24.5%) isolates presented ETP MIC of ≥8 μg/mL, 763 (21.3%) isolates presented IPM MIC of ≥16 μg/mL. Unlike other five second-choice antimicrobials, 599 isolates presented TOB MIC of 8 μg/mL, leading to 17.1% intermediary rate.

Figure 2 Distribution of MIC for six second-choice antimicrobials. MIC distributions among isolates for six drugs: ETP, IPM, AK, GEN, TOB, and SXT. ND: data not available. CLSI 2018 breakpoints were presented as grey dashed lines in each subplot, dividing isolates into susceptible (isolates to the left of the first line), intermediate (isolates between the two lines) and resistant (isolates to the right of the second line except “ND”) types. The resistance to TGC was tested by Kirby-Bauer disk diffusion method, so there is no information on TCG MIC.

Abbreviations: ETP, ertapenem; IPM, imipenem; AK, amikacin; GEN, gentamicin; TOB, tobramycin; SXT, trimethoprim-sulfamethoxazole.

By comparing the NSRs to the seven second-choice antimicrobials by year, we found that the NSRs to three aminoglycosides (AK, GEN, TOB) increased from 2013 to 2015, and then followed with a decreased trend, among which the NSR to AK was the lowest (Figure 3B). While the NSR to SXT dropped slowly from 40.2% to 35.3% (Figure 3C), a considerable increase towards two carbapenems (ETP, IPM) and TGC, which was commonly used to treat carbapenems and fluoroquinolone resistant KP, was shown (Figure 3A and D). We can also observe that the intermediary rate of TGC increased from 2014 to 2016 in Table 2.

Figure 3 Dynamics in NSRs to second-choice antimicrobials from 2013 to 2018. The yearly change of NSRs to 2 carbapenems (ETP, IPM) (A), 3 aminoglycosides (AK, GEN, TOB) (B), sulfamethoxazole-trimethoprim (SXT) (C) and tigecycline (TGC) (D), between 2013 and 2018.

Abbreviations: ETP, ertapenem; IPM, imipenem; AK, amikacin; GEN, gentamicin; TOB, tobramycin; SXT, trimethoprim-sulfamethoxazole; TGC, tigecycline.

Clinical Factors Affecting the KP Non-Susceptibility to the Second-Choice Antimicrobials

The department-temporal clinical factors associated with non-susceptibility to the seven second-choice antimicrobials were calculated (Table 3). Some previous studies have shown that long duration of hospital stay was considered as one of the risk factors for antimicrobial resistance,23 in our study, however, NSR to tigecycline among the non-hospitalized group was significantly higher than that of the hospitalized group (40.60% VS 27.36%, P < 0.001). NSRs to other second-choice antimicrobials did not show significant difference between the two groups. For different genders, the NSRs to 2 carbapenems and 3 aminoglycosides among males were significantly higher than those among females (P < 0.05). For different age groups, the non-susceptibility to IPM, AK, GEN, TOB, SXT, and TGC showed significant bias (P < 0.001), with the lowest NSRs among newborns at the age of 0 to 1 (14.7%, 0.6%, 17.7%, 23.5%, 32.7%, 25.5%, respectively). Significant bias of non-susceptibility was also present in different sampling types/time. We subdivided the sampling time into quarterly units (Q1: Jan–Mar, Q2: Apr–Jun, Q3: Jul–Sep, Q4: Oct–Dec), and discovered the non-susceptibility towards ETP, IPM, AK, SXT, and TGC varied from quarter to quarter. All second-choice antimicrobials presented significantly different NSRs in different departments, while all second-choice antimicrobials (except TGC) presented significantly different non-susceptibility in various sample types.

Table 3 Univariate Analysis of Clinical Factors for Non-Susceptibility to Second-Choice Antimicrobials

Multivariate analysis by logistic regression was also managed (Table 4). We found that hospitalization showed a negative correlation with non-susceptibility to ETP, IPM, TOB, and TGC. Males were associated with non-susceptibility to ETP and IPM. Age was not correlated with any NSRs when it is regarded as a continuous variable. These results showed similar characteristics of antimicrobial non-susceptibility discovered in univariate analysis, except that no significant correlation of the non-susceptibility to AK with sample types was identified.

Table 4 Multivariate Analysis of Risk Factors for Non-Susceptibility to Second-Choice Antimicrobials

Department Distribution of Non-Susceptibility in KP

In the present study, we found that KP showed different department bias for non-susceptibility to different second-choice antimicrobials. For the seven second-choice antimicrobials, the NSRs to ETP, IPM, and AK were highest in ICU (39.8%, 39.7%, and 30.6%, respectively), while that to GEN, TOB, SXT, and TGC were higher in wards of integrated traditional Chinese and Western medicine (ITC & WM) and rehabilitation than in other departments (higher than 51.6%, 58.6%, 47.6%, and 42.1%, respectively). The resistance bias to TGC is not as obvious as that to other drugs, but is still significant (P = 0.037). The NSRs to second-choice antimicrobials were always lower in the oncology ward and obstetrics and gynecology ward (Figure 4A).

Figure 4 NSRs to seven second-choice antimicrobials in different departments and sample types. The Non-susceptible rates to seven second-choice antimicrobials of K. pneumoniae strains recovered from different departments (A) and different sample types (B) are presented in this figure.

Abbreviations: ETP, ertapenem; IPM, imipenem; AK, amikacin; GEN, gentamicin; TOB, tobramycin; SXT, trimethoprim-sulfamethoxazole; TGC, tigecycline.

As for different sample types, the NSRs to two carbapenems were higher in CSF (38.5% and 42.9%, respectively) and lower in genital secretion (2.1%), and three aminoglycosides (AK, GEN, and TOB) had higher NSRs in the wound secretion (24.8%, 58.0%, and 60.7%, respectively) (Figure 4B). The NSRs of KP from stool varied considerably, probably due to the small sample size.

Temporal Distribution of Non-Susceptibility in KP

We further analyzed the dynamics of NSRs with seasons for seven selected drugs. Interestingly, we found seasonal fluctuations in the non-susceptibility to four second-choice antimicrobials during 2015–2017, which constituted the majority (76.3%) of samples. During this period, ETP, IPM, and AK had higher NSRs in the first and second quarters of each year. However, the volatility of SXT NSR was the opposite of these three drugs, with the rate higher in the third and fourth quarters (Figure 5).

Figure 5 Seasonality of non-susceptibility to five second-choice antimicrobials which showed significance in univariable and multivariable test. The non-susceptible rates to five second-choice antimicrobials between 2013 and 2018, ETP, IPM, AK, SXT presented fluctuations on a yearly basis, and the seasonality of SXT non-susceptibility was opposite to that of ETP, IPM, and AK. Different antimicrobials were presented in different colors and line styles. Q1: Jan–Mar, Q2: Apr–Jun, Q3: Jul–Sep, Q4: Oct–Dec.


Multidrug-resistant Klebsiella pneumoniae is a common problem exposed in various countries in the world. Some studies have found that plasmids carrying carbapenem resistant gene often carry other drug-resistant genes as well, and can be widely spread in KP population, leading to the increase of MDR CRKP.24,25 This phenomenon is also reflected in Chinese data. According to the antimicrobial resistance report from CHINET in 2018, carbapenem-resistant Klebsiella pneumoniae were highly resistant to most commonly used antimicrobial agents.26 Consistent with the previous reports, in this study we found that isolates non-susceptible to carbapenems and AK were associated with stronger multidrug-resistance (with over 98% isolates being non-susceptible to >5 antimicrobial categories and over 30% non-susceptible to >10 categories) than other isolates. In addition, second-choice antimicrobials were frequently used in the treatment of MDR KP, which may also promote the NSR of MDR KP to second-choice antimicrobials.

According to the national drug resistance report of Klebsiella pneumoniae from China Antimicrobial Resistance Surveillance System (CARSS) ( in 2018, CRKP had a higher rate in neonatal and ICU populations (15.3% and 21.9%, respectively) as well as in CSF, and a lower rate in wound pus.20 However, in this study, KP isolated from genital secretions had the lowest NSR towards carbapenem, followed by samples of various abscesses, and the proportion of CRKP in the neonatal population was not significantly higher than that of other groups. The preference of CRKP for ICU and CSF samples was consistent with the national data. In addition, the CRKP detection rate from the 2018 national data (10.1% nationwide, 11.4% in Hunan) was lower than the carbapenem resistance rate in this study (ETP 28.2%, IPM 27.2%). The discrepancy between our discovery and the nationwide surveillance data could be caused by several reasons. First, the nationwide surveillance sampled from numerous hospitals in the country, including both primary and secondary hospitals, while our study focuses on samples from one large tertiary hospital in China. Most patients admitted to our hospital are critically ill patients after a referral from primary and secondary hospitals where these patients have already undergone medication. This may represent a sampling difference. Second, the varieties in the method of Antimicrobial Susceptibility Test (AST) in the nationwide data could also cause a discrepancy in non-susceptible rates, comparing to our standard MIC test system. In addition, we only rechecked the TGC sensitivity from a few sterile parts by manual broth dilution method, which may be the main reason for the high TGC drug resistance. These differences in resistance characteristics indicate the need to analyze regional KP drug resistance.

Department of ITC & WM in the local hospital takes the patients with nerve function defect as its main therapeutic group, which is similar to those patients treated in the rehabilitation department. In the present study, isolates from ICU had the highest NSRs to ETP, IPM, and AK (39.8%, 39.7%, and 30.6%, respectively), while isolates from ITC & WM and rehabilitation had the highest NSRs to GEN, TOB, SXT, and TGC (higher than 51.6%, 58.6%, 47.6%, and 42.1%, respectively). We analyzed the antimicrobial consumption in ICU, ITC & WM, and rehabilitation (Table 5), and discovered that ICU consumed much more carbapenems than other departments of the hospital, this may be one of the reasons for the high resistance to carbapenems in ICU. However, the consumption of AK, GEN, and TGC in these three departments shows no correlations with their NSRs, underlying a more complicated mechanism.

Table 5 Consumption of Four Second-Choice Antimicrobials in Hospital from 2013 to 2018

The antimicrobial usage could also influence the resistance characteristics in different sample types. Some antibiotics that can cross the blood-brain barrier during inflammation,27 IPM tend to reach higher concentrations than other second-choice antimicrobials in CSF. Though this unique mechanism may result in higher NSRs to ETP and IPM in isolates from CSF, drug penetration is also influenced by the nature and extent of the infection, more factors need to be investigated (Figure 4B).

A similar seasonal variation of drug resistance rates was also reported on Escherichia coli and Streptococcus pneumoniae.28–30 In addition, some studies have shown that the abundance of drug-resistant genes in the environment varies with the season.31–34 In our study, seasonal variation characters have also been found. The change of ETP, IPM, and AK in the period from 2015 to 2017 is basically consistent with the previous studies. The NSR reaches its peak in the first half of each year and drops to its trough in the second half of the year. However, the fluctuation pattern of SXT is contrary to the above three drugs, which is opposite to the previous report of Escherichia coli.30

In this research, 4128 isolates of KP were collected from a tertiary hospital in Hunan, China, covering a period of six years, and 3619 isolates were used in the analysis. The long-term, large sample-size retrospective study provides a fundamental picture of local KP infection. By analyzing the clinical information, we found that the NSRs to the second-choice antimicrobials varied significantly in different departments, sample types, and seasons. A full understanding of the department-temporal characteristics of the antimicrobial resistance provides reference for clinicians in KP prevention and treatment. Our research has several limitations. First, it is impossible to include all the influencing factors in the multivariate analysis so we can get more comprehensive information. This requires more investigation of clinical information in the later study. Second, the information of drug use has not been accurately counted, and antimicrobial consumption in the community was not taken into account with the analysis. All these suggest that we need to establish a more perfect and strict drug use supervision system in clinical practice. In addition, the special-temporal characteristics reported in the current study have regional limitations. In conclusion, our investigation of the NSRs in KP from a typical tertiary hospital revealed that MDR KP prevails and the carbapenem resistance rates of the strains in the ICU department and CSF source are higher. The non-susceptibility of ETP, IPM, and AK showed an opposite trend of seasonal fluctuations to non-susceptibility of SXT from 2015 to 2017. Our data provide a bias for the control and prevention work in the KP clinical treatment. More effective control measures should be taken to reduce the high resistance rates and curb the spread of MDR KP, and our study would be a good representation for the guidance of KP treatment in other clinical centers.


  • A total of 4128 Klebsiella pneumoniae isolates were collected in our study
  • The non-susceptible rates to ertapenem, imipenem, and tigecycline increased considerably from 2013 to 2018
  • Higher multi-drug resistance rates were observed in second-choice antimicrobials than all drugs of KP isolates
  • Higher ETP/IPM/AK NSRs were observed in ICU than in other departments, and ETP/IPM non-susceptible isolates tended to distribute in CSF than in the other sample types

Ethical Approval and Consent to Participate

The experimental protocol was established, according to the ethical guidelines of the Helsinki Declaration and was approved by the Human Ethics Committee of Xiangya Hospital of Central South University (XHCSU), Changsha, China (No. 201,806,861). Written informed consent was obtained from individual or guardian participants.


The authors gratefully acknowledge the contribution and support of Juanjuan Di for her efficient communication and coordination work in our study. We also thank China National GeneBank at Shenzhen for giving us necessary support.

Author Contributions

JL, WL and NP conceived and designed the project, YZ, SW participated in sample collection, QL, ZJ, MZ, and JH performed the bacterial culturing and drug sensitivity testing, XC and TL performed the bioinformatic analyses, NP, QL, and XC interpreted the data. All authors participated in discussions, XC and NP wrote the manuscript. All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.


This work was supported by the National Natural Science Foundation of China [grant number 81672066 to WL].


The authors declare that they have no conflict of interest.


1. Magill SS, Edwards JR, Bamberg W, et al. Multistate point-prevalence survey of health care-associated infections. N Engl J Med. 2014;370(13):1198–1208. doi:10.1056/NEJMoa1306801

2. Downie L, Armiento R, Subhi R, Kelly J, Clifford V, Duke T. Community-acquired neonatal and infant sepsis in developing countries: efficacy of WHO’s currently recommended antibiotics–systematic review and meta-analysis. Arch Dis Child. 2013;98(2):146–154. doi:10.1136/archdischild-2012-302033

3. van Duin D, Doi Y, Carroll KC. Outbreak of colistin-resistant, carbapenemase-producing klebsiella pneumoniae: are we at the end of the road? J Clin Microbiol. 2015;53(10):3116–3117. doi:10.1128/JCM.01399-15

4. Zhang Y, Wang Q, Yin Y, et al. Epidemiology of carbapenem-resistant enterobacteriaceae infections: report from the china CRE network. Antimicrob Agents Chemother. 2018;62(2).

5. Wang Q, Zhang Y, Yao X, et al. Risk factors and clinical outcomes for carbapenem-resistant Enterobacteriaceae nosocomial infections. Eur J Clin Microbiol Infect Dis. 2016;35(10):1679–1689. doi:10.1007/s10096-016-2710-0

6. Nordmann P, Cuzon G, Naas T. The real threat of Klebsiella pneumoniae carbapenemase-producing bacteria. Lancet Infect Dis. 2009;9(4):228–236. doi:10.1016/S1473-3099(09)70054-4

7. Gupta N, Limbago BM, Patel JB, Kallen AJ. Carbapenem-resistant Enterobacteriaceae: epidemiology and prevention. Clin Infect Dis. 2011;53(1):60–67. doi:10.1093/cid/cir202

8. Global priority list of antibiotic-resistant bacteria to guide research, discovery, and development of new antibiotics. Available from: Accessed February 27, 2020.

9. Fasciana T, Gentile B, Aquilina M, et al. Co-existence of virulence factors and antibiotic resistance in new Klebsiella pneumoniae clones emerging in south of Italy. BMC Infect Dis. 2019;19(1):928. doi:10.1186/s12879-019-4565-3

10. Podschun R, Ullmann U. Klebsiella spp. as nosocomial pathogens: epidemiology, taxonomy, typing methods, and pathogenicity factors. Clin Microbiol Rev. 1998;11(4):589–603. doi:10.1128/CMR.11.4.589

11. Munoz-Price LS, Poirel L, Bonomo RA, et al. Clinical epidemiology of the global expansion of Klebsiella pneumoniae carbapenemases. Lancet Infect Dis. 2013;13(9):785–796. doi:10.1016/S1473-3099(13)70190-7

12. Yu J, Tan K, Rong Z, et al. Nosocomial outbreak of KPC-2- and NDM-1-producing Klebsiella pneumoniae in a neonatal ward: a retrospective study. BMC Infect Dis. 2016;16(1):563. doi:10.1186/s12879-016-1870-y

13. Snitkin ES, Zelazny AM, Thomas PJ, et al. Tracking a hospital outbreak of carbapenem-resistant Klebsiella pneumoniae with whole-genome sequencing. Sci Transl Med. 2012;4(148):148ra16. doi:10.1126/scitranslmed.3004129

14. Falagas ME, Kasiakou SK. Toxicity of polymyxins: a systematic review of the evidence from old and recent studies. Crit Care. 2006;10(1):R27. doi:10.1186/cc3995

15. Hu F, Chen S, Xu X, et al. Emergence of carbapenem-resistant clinical Enterobacteriaceae isolates from a teaching hospital in Shanghai, China. J Med Microbiol. 2012;61(Pt 1):132–136. doi:10.1099/jmm.0.036483-0

16. Gurjar M. Colistin for lung infection: an update. J Intensive Care. 2015;3(1):3. doi:10.1186/s40560-015-0072-9

17. Cunha BA, Baron J, Cunha CB. Once daily high dose tigecycline - pharmacokinetic/pharmacodynamic based dosing for optimal clinical effectiveness: dosing matters, revisited. Expert Rev Anti Infect Ther. 2017;15(3):257–267. doi:10.1080/14787210.2017.1268529

18. Krause KM, Serio AW, Kane TR, Connolly LE. Aminoglycosides: an overview. Cold Spring Harb Perspect Med. 2016;6(6):a027029. doi:10.1101/cshperspect.a027029

19. Status report on antimicrobial management and bacterial resistance in China; 2018. Available from: Accessed April 12, 2020.

20. National surveillance report of bacterial resistance of China; 2018. Available from: Accessed November 19, 2020.

21. Magiorakos AP, Srinivasan A, Carey RB, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268–281. doi:10.1111/j.1469-0691.2011.03570.x

22. Holt KE, Wertheim H, Zadoks RN, et al. Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance in Klebsiella pneumoniae, an urgent threat to public health. Proc Natl Acad Sci USA. 2015;112(27):E3574–E81. doi:10.1073/pnas.1501049112

23. Kang C-I, Kim S-H, Park WB, et al. Risk factors for antimicrobial resistance and influence of resistance on mortality in patients with bloodstream infection caused by Pseudomonas aeruginosa. Microb Drug Resist. 2005;11(1):68–74. doi:10.1089/mdr.2005.11.68

24. Wyres KL, Holt KE. Klebsiella pneumoniae population genomics and antimicrobial-resistant clones. Trends Microbiol. 2016;24(12):944–956. doi:10.1016/j.tim.2016.09.007

25. Gootz TD, Lescoe MK, Dib-Hajj F, et al. Genetic organization of transposase regions surrounding blaKPC carbapenemase genes on plasmids from Klebsiella strains isolated in a New York City hospital. Antimicrob Agents Chemother. 2009;53(5):1998–2004. doi:10.1128/AAC.01355-08

26. Hu F, Guo Y, Yang Y, et al. Resistance reported from China antimicrobial surveillance network (CHINET) in 2018. Eur J Clin Microbiol Infect Dis. 2019;38(12):2275–2281. doi:10.1007/s10096-019-03673-1

27. Sullins AK, Abdel-Rahman SM. Pharmacokinetics of antibacterial agents in the CSF of children and adolescents. Paediatr Drugs. 2013;15(2):93–117. doi:10.1007/s40272-013-0017-5

28. Martinez EP, Cepeda M, Jovanoska M, et al. Seasonality of antimicrobial resistance rates in respiratory bacteria: a systematic review and meta-analysis. PLoS One. 2019;14(8):e0221133. doi:10.1371/journal.pone.0221133

29. Asencio Egea MÁ, Huertas Vaquero M, Carranza González R, Herráez Carrera Ó, Redondo González O, Arias Arias Á. Trend and seasonality of community-acquired Escherichia coli antimicrobial resistance and its dynamic relationship with antimicrobial use assessed by ARIMA models. Enferm Infecc Microbiol Clin. 2018;36(8):502–506. doi:10.1016/j.eimc.2017.10.013

30. Ramsey EG, Royer J, Bookstaver PB, et al. Seasonal variation in antimicrobial resistance rates of community-acquired Escherichia coli bloodstream isolates. Int J Antimicrob Agents. 2019;54(1):1–7. doi:10.1016/j.ijantimicag.2019.03.010

31. Schages L, Wichern F, Kalscheuer R, Bockmühl D. Winter is coming - impact of temperature on the variation of beta-lactamase and mcr genes in a wastewater treatment plant. Sci Total Environ. 2020;712:136499. doi:10.1016/j.scitotenv.2020.136499

32. Lu J, Zhang Y, Wu J. Continental-scale spatio-temporal distribution of antibiotic resistance genes in coastal waters along coastline of China. Chemosphere. 2020;247:125908. doi:10.1016/j.chemosphere.2020.125908

33. Liang X, Guan F, Chen B, et al. Spatial and seasonal variations of antibiotic resistance genes and antibiotics in the surface waters of Poyang Lake in China. Ecotoxicol Environ Saf. 2020;196:110543. doi:10.1016/j.ecoenv.2020.110543

34. Sun L, Klein EY, Laxminarayan R. Seasonality and temporal correlation between community antibiotic use and resistance in the United States. Clin Infect Dis. 2012;55(5):687–694. doi:10.1093/cid/cis509

Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF]