Relationship between Antibiotic Consumption and Resistance: A Systematic Review

Abejew, Asrat Agalu; Wubetu, Gizachew Yismaw; Fenta, Teferi Gedif

doi:https://doi.org/10.1155/2024/9958678

Canadian Journal of Infectious Diseases and Medical Microbiology

On this page

Abstract Introduction Results Discussion Data Availability Ethical Approval Conflicts of Interest Authors’ Contributions Supplementary Materials References Copyright Related Articles

Review Article | Open Access

Volume 2024 | Article ID 9958678 | https://doi.org/10.1155/2024/9958678

Relationship between Antibiotic Consumption and Resistance: A Systematic Review

Asrat Agalu Abejew,^1,2Gizachew Yismaw Wubetu,³and Teferi Gedif Fenta¹

Academic Editor: Mian Muhammad Awais

Received29 Jun 2023

Revised20 Nov 2023

Accepted24 Feb 2024

Published05 Mar 2024

Abstract

Background. Unreserved use of antibiotics exerted selective pressure on susceptible bacteria, resulting in the survival of resistant strains. Despite this, the relationship between antibiotic resistance (ABR) and antibiotic consumption (ABC) is rarely studied. This systematic review aims to review the relationship between ABC and ABR from 2016 to 2022. Methods. Articles published over 7 years (2016–2022) were searched from December 23 to 31, 2022. The search strategy was developed by using keywords for ABC and ABR. From 3367 articles, 58 eligible articles were included in the final review. Results. The pooled ABC was 948017.9 DPDs and 4108.6 DIDs where over 70% of antibiotics were from the Watch and Reserve category based on the WHO AWaRe classification. The average pooled prevalence of ABR was 38.4%. Enterococcus faecium (59.4%), A. baumannii (52.6%), and P. aeruginosa (48.6%) were the most common antibiotic-resistant bacteria. Cephalosporins (76.8%), penicillin (58.3%), and aminoglycosides (52%) were commonly involved antibiotics in ABR. The positive correlation between ABR and consumption accounted for 311 (81%). The correlation between ABR P. aeruginosa and ABC accounted for 87 (22.7%), followed by 78 (20.3%) and 77 (20.1%) for ABR E. coli and K. pneumoniae with ABCs, respectively. Consumption of carbapenems and fluoroquinolones was most commonly correlated with resistance rates of P. aeruginosa, K. pneumoniae, E. coli, and A. baumannii. Conclusion. There is a positive correlation between ABC and the rate of ABR. The review also revealed a cross-resistance between the consumption of different antibiotics and ABR. Optimizing antibiotic therapy and reducing unnecessary ABC will prevent the emergence and spread of ABR. Thus, advocating the implementation of stewardship programs plays a pivotal role in containing ABR.

1. Introduction

The discovery of antibiotics is the most significant achievement in the twentieth century [1]. It changed medical practice and significantly decreased morbidity and mortality associated with bacterial infections. In recent years, the emergence and spread of antibiotic-resistant pathogens on the one hand and decreased invention of new antibiotics on the other hand challenged healthcare [2, 3]. High rates of resistance against frequently used antibiotics to treat infections have been observed worldwide, resulting in running out of effective antibiotics to treat common infections [4]. Due to this, access to antibiotics remains a critical issue globally [3, 5]. According to the Centers for Disease Control and Prevention (CDC), there were 2,868,700 infections due to resistant pathogens and 35,900 deaths from antibiotic-resistant bacterial infections each year [6].

ABR is a natural phenomenon augmented by human actions such as the inappropriate use of antibiotics [7]. Increased utilization of antibiotics results in an increased frequency of inappropriate antibiotic use [8]. Given the association between antibiotic use and the selection of resistant pathogens, inappropriate use of antibiotics is often used as a surrogate marker for the avoidable ABR [9]. Thus, the increase in bacterial resistance is contributed by selection pressure on antibiotics as a result of use, overuse, and misuse [10–12], and total consumption of antibiotics is the critical factor in selecting resistance [11]. There were individual studies that confirmed the correlation between ABC and ABR patterns [13–17]. Antibiotic stewardship programs (ASPs) are usually aimed at reducing overall ABC, and thus, preventing and reversing resistance [1, 11]. Thus, it is recommended to monitor antibiotic prescribing to improve the quality of antibiotic use and to reduce ABR [18]. Thus, this review aims to determine the relationship between ABC and rates of ABR based on articles published globally from 2016 to 2022.

2. Methodology

2.1. Study and Data Collection

Eligible articles were identified by the search strategy developed by using keywords for antibiotic resistance and ABC. Mainly the PubMed (Medline) database was used to search for eligible articles. Additional articles were identified by searching from Google Scholar. Searches were performed for 7 years, and it was performed from December 23 to 31, 2022. Search terms used included a combination of keywords like “drug resistance,” “antimicrobial resistance,” “bacterial resistance,” “antibiotic resistance,” “antibiotic use,” “ABC,” “antimicrobial use,” and “antimicrobial consumption.” Articles were initially reviewed based on title and abstracts, and then, the whole document was read to select eligible articles for review. Articles that had determined the correlation between ABR and ABC using correlation coefficients and association at a P value of 0.05 were included in the review. Thus, articles relating to nonhuman infections, previous systematic reviews, commentaries, editorial letters, and available only in the abstracts were excluded from the review (Figure 1).

For the sake of discussion, the correlation coefficients were classified as very strong (0.9–1), strong (0.7–0.89), moderate (0.4–0.69), weak (0.1–0.39), and negligible (<0.1) [19]. Finally, the results were compiled and described. The defined daily dose (DDD)/100(0) patient days (DPDs) and DDD/1000 inhabitant days per year (DIDs) were used to report ABCs.

3. Results

3.1. General Description of Articles Included in the Review

Overall, 58 articles [20–77] published globally from 2016 to 2022 were included in the systematic review. The summary of articles included, including the correlation between bacterial resistance and ABC, is summarized and annexed in Annex 1.

The majority of the articles 13 (22.3%) were published in China [21, 25–28, 42, 60, 62–64, 68, 72, 77], 4 (6.9%) Europe [48, 49, 74, 75], 4 (6.9%) South Korea [31, 54, 61, 65], 4 (6.9%) Serbia [34, 36, 39, 52], 3 (5.2%) Japan [20, 30, 40], 2 (3.4%) Italy [22, 33], 2 (3.4%) Thailand [35, 57], 2 (3.4%) France [46, 56], 2 (3.4%) Spain [43, 59], 2 (3.4%) Slovenia [47, 71], 2 (3.4%) Switzerland [45, 70], and the rest were in different countries [23, 29, 32, 37, 38, 41, 44, 50, 51, 53, 55, 58, 66, 67, 69, 73, 76, 77]. The majority of the articles 11(23.4%) were published in 2017 [22, 33, 36, 44, 47, 48, 52, 56, 59, 64, 67], 2018 [20, 23, 26, 35, 45, 46, 53, 54, 61, 63, 65], 2019 [21, 25, 30, 31, 40, 42, 43, 50, 51, 55, 62], 2021 [24, 29, 32, 38, 43, 60, 69–71, 75, 76], and each 5 (8.6%) in 2016 [34, 37, 41, 57, 58] and 2022 [68, 72–74, 77], but only 4 were published in 2020 [27, 38, 39, 49]. Almost all 53 (91.4%) of the articles were based on retrospective data, and the rest (8.6%) were prospective observational studies.

3.2. Antibiotic consumption

ABC was measured by different metrics. The unit of measure for ABC was not uniform for all articles. The units of ABC were standardized to 1000 patient days (DPDs) [21–23, 25, 30, 31, 35, 37, 40, 41, 44, 46, 49–52, 55–61, 64–68, 77] and 100 patient days (DPDs) [20, 26–29, 32–34, 36, 38, 39, 42, 43, 45, 53, 69, 70, 73, 76], but in addition, DIDs [30, 40, 47, 48, 56, 59, 65, 66, 68, 71, 72, 74, 75], grams [24], and average/percentage trend [54, 62] were used to measure ABC. Accordingly, about 948017.9 DPDs (904622.9 standardized per 1000 patient days and 4339.5 per 100 patient days) and 4108.6 DIDs were reported, but about 173616.9 and 99800 were reported in average consumption and in grams, respectively. More than 70% of antibiotics were consumed in the Watch and Reserve categories based on the WHO AWaRe classification. Due to a lack of uniform measurement and recording of antibiotics among the articles, overall ABC was not summarized (Table 1).

3.3. Prevalence of Antibiotic Resistance

ABR was reported as a percentage (rate, trend, or prevalence) in all articles except three, which reported the incidence density of ABR [22, 52, 63, 68]. The average pooled prevalence of antibiotic-resistant bacteria was 38.4%, with Enterococcus faecium (59.4%), A. baumannii (52.6%), P. aeruginosa (48.5%), coagulase-negative Staphylococcus (43.7%), Enterobacter (46.1%), and P. mirabilis (48.5%) being the most common resistant bacteria. Cephalosporins (76.8%), penicillin (58.3%), aminoglycosides (52%), fluoroquinolones (48.3%), tetracyclines (48.6%), and carbapenems (30%) were resistant in a different way for each bacterium (Table 2).

3.4. Distribution of Antibiotic Consumption and Resistant Bacteria

The overall systematic review of 58 articles revealed a positive association between bacterial resistance and ABC, both in community and hospital settings. Except for some antibiotics, either increased consumption was associated with increased resistance, or decreased consumption was associated with decreased resistance. The analysis revealed that about 311 (81%) of the correlations between ABC and the ABR rate were directly related to ABC, but 73 (19%) were negatively correlated, indicating the protective nature of ABC for the development of resistance. P. aeruginosa, K. pneumoniae, E. coli, and A. baumannii were the bacteria for which a relationship between ABC and the resistance rate or pattern was commonly studied. About 73 (83.9%), 63 (81.8%), 68 (87.2%), and 53 (85.5%) antibiotics were positively correlated with the resistance rates of P. aeruginosa, K. pneumonia, E. coli, and A. baumannii, respectively (Table 3).

3.5. Relationship between ABC and ABR

Here, the relationship between ABC and ABR is described for each bacterium based on the correlation coefficient reported by articles [20–78]. However, it has to be noted that all studies did not provide detailed information and similar reports.

There was a very strong correlation between the consumption of meropenem and the incidence of carbapenem-resistant P. aeruginosa [44] and meropenem-resistant P. aeruginosa [69], penicillin with the incidence of combined-resistant P. aeruginosa [44], imipenem [57], and ertapenem [69] with imipenem resistance P. aeruginosa [57, 69]. There was also a very strong correlation between amikacin consumption and the resistance rate of P. aeruginosa to amikacin [24] and between piperacillin/tazobactam and piperacillin/tazobactam-resistant P. aeruginosa [69]. Similarly, there was a strong correlation between imipenem and meropenem and the rate of carbapenem-resistant P. aeruginosa [34], carbapenems with the rate of imipenem-resistant [44], meropenem-resistant [44], carbapenem-resistant [44], and ceftazidime-resistant [77] P. aeruginosa. There was also a very strong correlation between ciprofloxacin consumption and the resistance rate of P. aeruginosa [42].

A strong correlation was observed between the consumption of aminoglycosides and the rate of P. aeruginosa resistance to amikacin and gentamicin, gentamicin with the rate of aminoglycoside-resistant P. aeruginosa [34], and levofloxacin with the resistance rate of P. aeruginosa to levofloxacin [42]. A moderate correlation was found between the consumption of extended-spectrum antibiotics and cephalosporin with resistant P. aeruginosa [37], piperacillin/tazobactam with the incidence of combined-resistant P. aeruginosa, and amikacin with aminoglycoside-resistant P. aeruginosa [34]. Moderate correlations were found between the consumption of carbapenem and the rate of carbapenem-resistant P. aeruginosa [37, 57], carbapenem with imipenem and meropenem-resistant P. aeruginosa [30], and amikacin, gentamicin, and levofloxacin with resistant P. aeruginosa to respective antibiotics [72].

Some studies reported a decreased resistance rate of P. aeruginosa from the consumption of carbapenems. There was a very strong negative correlation between consumption of carbapenem and resistance rates in P. aeruginosa [20, 57], a strong negative correlation between carbapenem and the rate of imipenem resistance in P. aeruginosa [25], and a moderate negative correlation between carbapenem and the rate of carbapenem-resistant P. aeruginosa [37], and amikacin was very strongly correlated with decreased rates of multidrug-resistant (MDR) P. aeruginosa [57].

There was also cross-resistance between ABC and resistance to another antibiotic, which was also common. There was a very strong correlation between consumption of ceftazidime and meropenem-resistant P. aeruginosa [69]. There is a very strong correlation between the consumption of carbapenems and the incidence density of P. aeruginosa resistance to third-generation cephalosporins and aminoglycosides [22] and aminoglycosides with the rate of imipenem resistance in P. aeruginosa [25]. There was a very strong cross-correlation between consumption of amikacin and rates of imipenem resistance strains of P. aeruginosa and MDR strains of P. aeruginosa [57] and aminoglycosides with rates of P. aeruginosa resistance to tazobactam-piperacillin [39].

A strong cross-correlation was recorded between consumption of all beta-lactam antibiotics and the rate of carbapenem-resistant P. aeruginosa [34], penicillin with the resistance density of carbapenem-resistant P. aeruginosa [53], beta-lactam/beta-lactamase inhibitor combinations, oxacephems, sulfonamides, and quinolones with the rate of imipenem resistance in P. aeruginosa [25], and carbapenems with the rate of ceftazidime-resistant P. aeruginosa [77]. But moderate cross-resistance was observed between quinolone consumption and resistance density of carbapenem-resistant P. aeruginosa [53] and all beta-lactam antibiotics with rate carbapenem-resistant P. aeruginosa [34], carbapenems and glycoproteins with aminoglycosides-resistant P. aeruginosa [68], cephalosporin/beta-lactamase inhibitor and penicillin/beta-lactamase inhibitor combinations with ceftazidime-resistant P. aeruginosa [77], and penicillin/beta-lactamase inhibitor combinations, fluoroquinolones, imidazole, colistin, and tigecycline consumption with piperacillin-tazobactam-resistant P. aeruginosa [39].

Similar to P. aeruginosa, there were records on the relationship between the rate of antibiotic-resistant A. baumannii and ABC. Consumption of carbapenems was very strongly correlated with imipenem resistance in A. baumannii [25] and with carbapenem resistance in A. baumannii [60, 68]. Consumption of carbapenems was strongly correlated with the rate of carbapenem-resistant A. baumannii [33, 37, 52, 77] and carbapenems and imipenem with imipenem-resistant A. baumannii [55, 61], but meropenem was moderately correlated with the rate of meropenem-resistant A. baumannii [32].

Likewise, consumption of cefepime was very strongly correlated with cefepime-resistant A. baumannii [33] and tigecycline with the incidence density of Acinetobacter [52]. The consumption of piperacillin/tazobactam and extended-spectrum cephalosporins was strongly correlated with piperacillin/tazobactam-resistant and extended-spectrum cephalosporin-resistant A. baumannii retrospectively [37]. There was also a strong correlation between the consumption of fluoroquinolones and ciprofloxacin-resistant A. baumannii [62]. A moderate correlation was found between the consumption of cefepime and ciprofloxacin with cefepime and ciprofloxacin-resistant A. baumannii, respectively [32], gentamicin with gentamicin-resistant A. baumannii [58], and fosfomycin with the rate of fosfomycin resistance in A. baumannii [55]. However, there were strong negative correlations between the consumption of aminoglycosides and an incidence density of aminoglycoside-resistant Acinetobacter spp. [52] and a moderate negative correlation between ciprofloxacin and ciprofloxacin-resistant A. baumannii [37].

Cross-resistance was also reported for different antibiotics and resistant A. baumannii. There was a very strong correlation between consumption of ceftazidime and both imipenem and meropenem-resistant A. baumannii [69], cephalosporin/beta-lactamase inhibitor combinations [60, 77], and tetracyclines [60] with carbapenem-resistant A. baumannii. There was a strong correlation between consumption of cephalosporins, cephalosporin/beta-lactamase inhibitor combinations, and other beta-lactam/beta-lactamase inhibitor combinations with carbapenem-resistant A. baumannii [77], but a moderate correlation was evident between cephalosporin carbapenem-resistant A. baumannii [77] and glycoprotein with carbapenem-resistant A. baumannii [68], and monobactams were moderately correlated with rates of carbapenem-resistant A. baumannii [77], but amikacin was very strongly and negatively correlated with rates of MDR strain A. baumannii, rates of imipenem-resistant strain A. baumannii, and rates of resistant meropenem strain A. baumannii [57]. A negative strong cross-correlation was also reported between the consumption of glycopeptides and amikacin-resistant A. baumannii [62] and aminoglycosides, quinolones, and oxacephems with imipenem-resistant A. baumannii [25], whereas ciprofloxacin was strongly and negatively correlated with both imipenem and meropenem-resistant A. baumannii [69].

Similarly, there was a very strong correlation between the consumption of imipenem/cilastatin and the resistance rate of K. pneumoniae to imipenem/cilastatin and fluoroquinolones with the prevalence of ciprofloxacin-resistant K. pneumoniae [43], but there were very strong negative correlations between imipenem and imipenem- and meropenem-resistant K. pneumoniae [69]. There was a strong correlation between the consumption of carbapenems and carbapenem-resistant K. pneumoniae [77] and extended-spectrum cephalosporins with extended-spectrum cephalosporin-resistant K. pneumoniae [69]. Colistin resistance was strongly correlated with the consumption of colistin [39]. Consumption of carbapenems was moderately correlated with doripenem-resistant, ertapenem-resistant, and meropenem-resistant K. pneumoniae [39] and carbapenem-resistant K. pneumoniae [44]. Consumption of cephalosporins was also moderately correlated with the rate of cephalosporin-resistant K. pneumoniae [44] and fluoroquinolones with ciprofloxacin-resistant K. pneumoniae [61].

A very strong cross-correlation was observed between the consumption of piperacillin/tazobactam and aminoglycoside-resistant K. pneumoniae [22], meropenem-resistant and imipenem-resistant K. pneumoniae [69], fluoroquinolones with trimethoprim/sulfamethoxazole-resistant K. pneumoniae [22], and the beta-lactam/beta-lactamase inhibitor combinations with carbapenem-resistant K. pneumoniae [22]. Consumption of sulfonamides was also very strongly correlated with the rate of ceftazidime-resistant K. pneumoniae and ceftazidime with quinolone-resistant K. pneumoniae [25]. There was a strong correlation between colistin-resistant K. pneumoniae and imidazoles, carbapenems, and colistin [39], doripenem-resistant K. pneumoniae with the consumption of imidazoles, ertapenem-resistant K. pneumoniae with glycopeptides, and meropenem-resistant K. pneumoniae with glycopeptides [39], and ceftriaxone was moderately correlated with the rate of carbapenem-resistant K. pneumoniae [35] and carbapenems with K. pneumoniae resistant to third-generation cephalosporin [63]. A moderate cross-correlation was observed between the consumption of glycopeptides and carbapenem-resistant K. pneumoniae [68].

A very strong negative cross-resistance was found between consumption of beta-lactam/beta-lactamase inhibitor combinations with fluoroquinolone-resistant K. pneumoniae [22], between doripenem-resistant K. pneumoniae and first- and second-generation cephalosporins, and aminoglycosides [39]. There was a strong negative correlation between the consumption of ciprofloxacin, ofloxacin, and norfloxacin with carbapenem‐resistant K. pneumoniae [35]; colistin-resistant K. pneumoniae with first- and second-generation cephalosporins and penicillin/beta-lactamase inhibitor; between doripenem-resistant K. pneumoniae and third- and fourth-generation cephalosporin and glycopeptides; between ertapenem-resistant K. pneumoniae and first- and second-generation cephalosporins; and between meropenem-resistant K. pneumoniae and penicillin/beta-lactamase inhibitor combinations, fluoroquinolone, and tigecycline [39]. A strong correlation was also found between carbapenem and rates of ceftazidime resistance in K. pneumoniae [25], fourth-generation cephalosporins, and fluoroquinolone within cefepime-resistant and ciprofloxacin-resistant K. pneumoniae [62].

Antibiotic-resistant E. coli was also correlated with the consumption of several antibiotics. There was a very strong correlation between ciprofloxacin consumption with fluoroquinolone-resistant E. coli [65], and a strong correlation was found between fluoroquinolone and fluoroquinolone-resistant E. coli [48, 65], fluoroquinolones with the resistance rate of E. coli to levofloxacin and resistance rate of E. coli to ciprofloxacin [42], and ciprofloxacin with ciprofloxacin-resistant E. coli [37], but there was a strong negative correlation between fluoroquinolone and ciprofloxacin-resistant E. coli [62]. There was also a very strong correlation between cefotaxime and cefotaxime-resistant E. coli and a strong correlation between cefoxitin and cefoxitin-resistant E. coli [65], gentamicin with resistant E. coli [33], extended-spectrum cephalosporin with resistant E. coli [37], and imipenem/cilastatin with imipenem/cilastatin-resistant E. coli [62].

There was a very strong cross-correlation between third- and fourth-generation cephalosporin use and E. coli resistance rates to cefotaxime and cephamycin use with E. coli resistance rates to cefoxitin [65]. A strong cross-correlation was found between carbapenems and third-generation cephalosporin-resistant E. coli [61] and beta-lactam/beta-lactamase inhibitor combinations with resistance density of third-generation cephalosporin-resistant E. coli [62], but fourth-generation cephalosporins were negatively correlated with cefepime-resistant E.coli, glycopeptides with amikacin-resistant E. coli [62], aminoglycosides [35, 61], and ofloxacin with carbapenem-resistant E. coli [35].

Antibiotic-resistant N. gonorrhoeae was reported in two studies [23, 49]. Consumption of ceftriaxone was strongly correlated with resistant N. gonorrhoeae, but consumption of ciprofloxacin was moderately correlated [23]. Macrolide consumption and cefixime resistance in N. gonorrhoeae and consumption of cephalosporin, macrolide, and quinolone were strongly correlated with ciprofloxacin resistance in N. gonorrhoeae [49]. Consumption of quinolones and cefotaxime was positively associated with ciprofloxacin-resistant and cefotaxime-resistant N. gonorrhoeae, respectively [74].

Consumption of aminoglycosides, quinolones, and carbapenem was strongly correlated with amikacin-resistant E. cloacae [25]. But carbapenem-resistant E. cloacae showed significant, very strong negative correlations with the usage of penicillin/beta-lactamase inhibitor I combinations, beta-lactam/beta-lactamase inhibitor combinations, meropenem, and carbapenems, but a very strong positive correlation was shown with total cephalosporin use [60]. Consumption of piperacillin/tazobactam was very strongly correlated with resistant C. difficile, but it was very strongly but negatively correlated with vancomycin [31] and ESBL-positive Enterobacteriaceae rates [33]. A positive association was also reported from the consumption of macrolides and clarithromycin-resistant H. pylori [50, 75] and consumption of quinolones with levofloxacin-resistant H. pylori [75].

Consumption of meropenem was very strongly correlated with piperacillin/tazobactam-resistant Enterobacter spp. [69] and meropenem and ciprofloxacin with piperacillin/tazobactam-resistant Enterobacter spp. [69], and piperacillin/tazobactam and resistant C. difficile [31] and strong correlation between carbapenems with carbapenem-resistant E. cloacae [77], aminoglycoside and quinolone with amikacin-resistant E. cloacae [25], and fluoroquinolone and MDR H. influenzae and Shigella spp. [41], but the moderate correlation was shown between macrolide and macrolide-resistant T. pallidum [51], carbapenem and carbapenem-resistant Enterobacteriales [70], and carbapenems, monobactams, cephalosporin/beta-lactamase inhibitor, and penicillin/beta-lactamase inhibitor with carbapenem-resistant E. cloacae [77]. A very strong negative correlation was reported between the consumption of vancomycin and resistant C. difficile [31] and piperacillin/tazobactam and third- and fourth-generation cephalosporin-resistant P. mirabilis [22]; a strong negative relationship was observed between piperacillin/tazobactam and piperacillin/tazobactam-resistant Proteus spp. and ESBL-positive Enterobacteriaceae [33].

A very strong correlation was observed between the consumption of beta-lactams or beta-lactam/beta-lactamase inhibitors and methicillin-resistant S. aureus [22] and clindamycin with oxacillin-resistant S. aureus [69]. There was a strong correlation between the consumption of extended-spectrum cephalosporin [70] and cloxacillin [48] and methicillin-resistant S. aureus [48, 70], and third-generation cephalosporins, carbapenems, glycopeptides, and monobactams were also moderately correlated with MRSA [63]; monobactams and sulphonamides were also were moderately correlated with MRSA [64]. A very strong correlation was between the consumption of linezolid [38] and vancomycin [69] with vancomycin-resistant E. faecium [38, 69]. A moderate correlation was shown between glycopeptides and glycopeptide-resistant E. faecalis/faecium [70], penicillin with penicillin resistance in S. pneumoniae [71], and extended-spectrum penicillin and penicillin/beta-lactamase inhibitor combinations with the resistance of S. pneumoniae to respective antibiotics [71].

There was a very strong negative correlation between the consumption of fluoroquinolone with ciprofloxacin-resistant E. faecalis [62] and third-generation cephalosporins and Hlr-gentamicin-resistant E. faecalis [22] and strong negative correlation between the consumption of fluoroquinolone and ciprofloxacin-resistant S. aureus, glycopeptides, and gentamicin-resistant S. aureus, glycopeptides, and gentamicin-resistant CoN Staphylococcus; glycopeptides with amikacin-resistant E. faecium and gentamicin-resistant E. faecalis [62] and piperacillin/tazobactam and vancomycin with oxacillin-resistant S. aureus [33]. A moderate correlation was shown between the consumption of gentamicin and gentamicin-resistant E. faecalis [48] and fluoroquinolone with ciprofloxacin-resistant CoN Staphylococcus [62]. The consumption of amoxicillin/clavulanate and oxacillin resistance in S. aureus [33] and imipenem/cilastatin and imipenem/cilastatin-resistant MRSA were very strongly and negatively correlated [42]. Consumption of glycopeptides and aminoglycosides was negatively correlated with MRSA [64].

4. Discussion

ABR is identified as one of the top threats to public health and challenges progress in health care, food production, and life expectancy [6, 78]. Due to overuse and misuse of antibiotics, bacteria have become increasingly resistant to various antibiotics [1]. A recent point prevalence survey at the global level reported about 136 million per year hospital-associated infections resistant to antibiotics caused by high-priority pathogens (E. coli, Acinetobacter spp., Klebsiella spp., S. aureus, Enterobacter spp., and Pseudomonas spp.) [79]. The current review revealed 38.4% of the average pooled prevalence of antibiotic resistance to bacteria, with E. faecium (59.4%), A. baumannii (52.6%), P. aeruginosa (48.5%), coagulase-negative Staphylococcus (43.7%), Enterobacter (46.1%), and P. mirabilis (48.5%). This complements the global concerns on the ABR [1, 6, 78, 79]. The burden of the ESKAPE and antibiotic resistance pattern calls for surveillance of antibiotic resistance targeting these pathogens by incorporating them into the infection control policy [80, 81]. It requires preventing infections as priority, slowing the development of ABR through better antibiotic use, and stopping the spread of ABR when it develops [78].

According to a recent report from a global point prevalence survey, high use of antibiotics (62.0%) and prolonged surgical antibiotic prophylaxis (60.9%) were the most common problems [82]. Thus, overuse and inappropriate use of antibiotics are recognized as a significant driver of the emergence of resistant strains of bacteria as the increased exposure to antibiotics encourages the development of ABR [83–85]. Increased ABC of broad-spectrum and last-resort antibiotics is a serious concern for public health [84–86]. Inappropriate consumption of antibiotics has also been shown to contribute to the occurrence of MDR organisms [86]. The current review [20–78] has clearly shown the relationship between ABC and ABR. It revealed more than 70% consumption of antibiotics from the Watch and Reserve categories based on the WHO AWaRe classification, among which consumption of carbapenems and fluoroquinolones were the most frequently involved in ABR including cross-resistance with consumption of other antibiotics. This was in line with a recent report from the global level which concluded, “a large proportion of prescriptions for key Watch antibiotics were issued for indications other than those for which they were included in the Essential Medicine List” [82]. Thus, a direct epidemiological relationship between ABC and the emergence and dissemination of resistant bacterial strains needs to be worked on for further understanding.

Biofilm-forming pathogens such as P. aeruginosa, A. baumannii, C. jejuni, C. difficile, C. perfringens, E. faecalis, K. pneumonia, P. mirabilis, B. cepacia, P. pseudomallei, H. influenza, E. coli, S. aureus, S. epidermidis, S. pneumonia, S. pyogenes, Salmonella spp., L. monocytogenes, S. agalactiae, and V. cholerae are very difficult to treat with conventional antibiotics due to their greater resistance profile [87, 88]. The CDC and WHO classified most of these microorganisms as threats to healthcare [6, 78] and call for close monitoring of resistance patterns for highly susceptible antibiotics [6, 78]. WHO classified carbapenem- and third-generation cephalosporin-resistant P. aeruginosa, A. baumannii, Enterobacteriaceae, K. pneumoniae, E. coli, Enterobacter spp., Serratia spp., Proteus spp., Providencia spp., and Morganella spp. as critical threats (top priority) to health care and vancomycin-resistant E. faecium, methicillin-resistant and vancomycin-intermediate and resistant S. aureus, clarithromycin-resistant H. pylori, fluoroquinolone-resistant Campylobacter spp., fluoroquinolone-resistant Salmonella spp., and third-generation cephalosporin-resistant fluoroquinolone-resistant N. gonorrhoeae as a high priority [78]. The direct relationship between ABCs as evidenced from the current review [20–78] indicates a need for developing new therapeutic strategies that can be effective against common infections in addition to optimizing the use of available antibiotics.

Similarly, the CDC classified carbapenem-resistant Acinetobacter, C. difficile, carbapenem-resistant Enterobacteriaceae, and drug-resistant N. gonorrhoeae as urgent threats and drug-resistant Campylobacter, extended-spectrum beta-lactamase-producing Enterobacteriaceae, vancomycin-resistant Enterococci, MDR P. aeruginosa, drug-resistant nontyphoidal Salmonella, drug-resistant Salmonella serotype Typhi, drug-resistant Shigella, methicillin-resistant S. aureus, drug-resistant S. pneumoniae, and drug-resistant Tuberculosis as serious threats to health care [6]. As can be noted, the current review strengthens the need to approach pathogens as a major issue problem related to resistance against antimicrobial agents.

Antibiotics with “high resistance potential,” even with limited use, have been associated with the emergence of MDR Gram-negative bacteria, e.g., imipenem, ceftazidime, gentamicin/tobramycin, and ciprofloxacin [89]. ASP is known to result in decreased ABC and ABR [90]. Due to a strong association between ABC and the development of antibiotic resistance [83], reducing the need for and inappropriate consumption of antibiotics through the implementation of appropriate ASPs can help delay the emergence and spread of ABR [90, 91]. Prudent use of antibiotics has to be a pillar in the fight against ABR [82]. This requires aligning practice with evidence which requires changes in prescribing behavior based on the implementation of effective strategies to modify prescribing practices by aligning them with evidence-based recommendations for diagnosis and management [92]. Thus, the initial step in fight against ABR in healthcare institutions has to be to measure the situation of antimicrobial use and resistance in their setting to raise awareness on areas of improvement of local prescribing behaviors [82]. The current review will help to understand the relationship between ABC and resistance and justify the need for universal funding and urgency for implementation of ASPs taking into account the local context for sustainable behavioral change in physicians’ antibiotic prescribing practices.

The review will serve as an important basis to better understand the issue and will inform policies, regulations, and interventions to optimize antibiotic use while reducing ABR. However, it has to be noted that the review does have limitations. The review includes literature in the English language and was not evaluated by independent evaluators. Because of the multiple numbers of antibiotics and microorganisms tested, risk assessment for bias and quality was not considered. Since most of the studies were done retrospectively, they may not necessarily show the true relationship between ABC and the rate of resistance. There are no data on the relationship between the consumption of antibiotics and the respective resistance rates in all parts of the world.

In conclusion, there was a strong relationship between antibiotic consumption and antibiotic resistance. The review also revealed a significant cross-resistance among different antibiotics. Most correlations were positively related, but a minority was negatively correlated, indicating the protective nature of antibiotic consumption for the development of resistance. There was a very strong correlation between fluoroquinolones, carbapenems, aminoglycosides, and penicillin consumption and respective resistance rates, but colistin, imipenem/cilastatin, and fluoroquinolones consumption was strongly correlated with the resistance rate of K. pneumoniae. Carbapenems were the most commonly used and strongly correlated with the rate of resistance for A. baumannii. Strict use of antibiotics is thus crucial to minimize the risk of emerging resistant organisms. ASP will help to optimize antibiotic therapy while reducing the amount of ABC to prevent the development and rate of ABR. Systems to assess institutional antibiotic utilization and the relationship between the trend of antibiotic use and rates of antibiotic resistance are strongly needed in health facilities to reduce resistance. Furthermore, special emphasis should be paid to antibiotics in the Watch and Reserve category of the WHO AWaRe classifications such as carbapenems, fluoroquinolones, macrolides, glycopeptides, and second-fourth generation cephalosporins.

Data Availability

Since all data are included in the review, no additional data is required to support the findings of this study.

Ethical Approval

Ethical clearance is not required for the review article.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

AAA was involved in the conception, study design, execution, and acquisition of data, analysis and interpretation, and writing and review of manuscript. TGF was involved in the conception, study design, manuscript writing, and review. GY was involved in the writing and review of the manuscript.

Supplementary Materials

Annex 1: summary of relationship between antibiotic consumption and antibiotic resistance, 2016-2022, (N=58). (Supplementary Materials)

References

WHO, in Antibiotic Stewardship Programs in Health-Care Facilities in Low- and Middle-Income Countries. A Practical Toolkit, World Health Organization, Geneva, Switzerland, 2019.
D. N. Obe, in Antibiotic Stewardship from Principles to Practice, British Society for Antibiotic Chemotherapy, England, UK, 2018.
S. Dhingra, N. A. A. Rahman, E. Peile et al., “Microbial resistance movements: an overview of global public health threats posed by antimicrobial resistance, and how best to counter,” Frontiers in Public Health, vol. 8, Article ID 535668, 2020.
View at: Publisher Site | Google Scholar
WHO, “Antibiotic resistance,” 2020, https://www.who.int/news-room/fact-sheets/detail/antibiotic-resistance.
View at: Google Scholar
A. M. Spera, S. Esposito, and P. Pagliano, “Emerging antibiotic resistance: carbapenemase-producing Enterobacteria. New bad bugs, still no new drugs,” Infections in Medicine, vol. 4, pp. 357–364, 2019.
View at: Google Scholar
CDC, Antibiotic Resistance Threats in the United States, 2019, U.S. Department of Health and Human Services, CDC, Atlanta, GA, USA, 2019.
World Bank, in Drug-Resistant Infections: A Threat to Our Economic Future (Discussion Draft), World Bank, Washington, DC, USA, 2016.
A. K. Thabit, K. M. Shea, O. E. Guzman, and K. W. Garey, “Antibiotic utilization within 18 community hospitals in the United States: a 5-year analysis,” Pharmacoepidemiology and Drug Safety, vol. 30, no. 4, pp. 403–408, 2021.
View at: Publisher Site | Google Scholar
T. H. Dellit, R. C. Owens, J. E. McGowan et al., “Infectious diseases society of America and the society for healthcare epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship,” Clinical Infectious Diseases, vol. 44, no. 2, pp. 159–177, 2007.
View at: Publisher Site | Google Scholar
M. H. Sedláková, K. Urbánek, V. Vojtová, H. Suchánková, P. Imwensi, and M. Kolář, “Antibiotic consumption and its influence on the resistance in Enterobacteriaceae,” BMC Research Notes, vol. 7, no. 1, p. 454, 2014.
View at: Publisher Site | Google Scholar
EFMHACA, “A practical guide to antibiotic stewardship program in Ethiopian hospitals,” 2018.
View at: Google Scholar
H.-S. Lee, Y.-X. Loh, J.-J. Lee, C.-S. Liu, and C. Chu, “Antibiotic consumption and resistance in five Gram-negative bacterial species in a hospital from 2003 to 2011,” Journal of Microbiology, Immunology, and Infection, vol. 48, 2015.
View at: Google Scholar
M. McLaughlin, M. R. Advincula, M. Malczynski, C. Qi, M. Bolon, and M. H. Scheetz, “Correlations of antibiotic use and carbapenem resistance in Enterobacteriaceae,” Antimicrobial Agents and Chemotherapy, vol. 57, no. 10, pp. 5131–5133, 2013.
View at: Publisher Site | Google Scholar
H.-H. Wu, H.-Y. Liu, Y.-C. Lin, P.-R. Hsueh, and Y.-J. Lee, “Correlation between levofloxacin consumption and the incidence of nosocomial infections due to fluoroquinolone-resistant Escherichia coli,” Journal of Microbiology, Immunology, and Infection, vol. 49, no. 3, pp. 424–429, 2016.
View at: Publisher Site | Google Scholar
J. Cao, W. Song, B. Gu et al., “Correlation between carbapenem consumption and antibiotic resistance rates of Acinetobacter baumannii in a university-affiliated hospital in China,” The Journal of Clinical Pharmacology, vol. 53, no. 1, pp. 96–102, 2013.
View at: Publisher Site | Google Scholar
T.-C. Weng, Y.-H. Chen, C.-C. Lee et al., “Correlation between fluoroquinolone consumption in hospitals and ciprofloxacin resistance amongst Pseudomonas aeruginosa isolates causing healthcare-associated infections, Taiwan, 2000–2009,” International Journal of Antimicrobial Agents, vol. 37, no. 6, pp. 581–584, 2011.
View at: Publisher Site | Google Scholar
C. C. Lai, C. Y. Wang, C. C. Chu et al., “Correlation between antimicrobial consumption and resistance among Staphylococcus aureus and enterococci causing healthcare-associated infections at a university hospital in Taiwan from 2000 to 2009,” European Journal of Clinical Microbiology and Infectious Diseases, vol. 30, no. 2, pp. 265–271, 2011.
View at: Publisher Site | Google Scholar
A. Versporten, P. Zarb, I. Caniaux et al., “Antimicrobial consumption and resistance in adult hospital inpatients in 53 countries: results of an internet-based global point prevalence survey,” Lancet Global Health, vol. 6, pp. e619–e629, 2018.
View at: Publisher Site | Google Scholar
P. Schober, C. Boer, and L. A. Schwarte, “Correlation coefficients: appropriate use and interpretation,” Anesthesia and Analgesia, vol. 126, no. 5, pp. 1763–1768, 2018.
View at: Publisher Site | Google Scholar
S. Hirayama, K. Yasui, H. Murakami et al., “A new carbapenem drug dosage metric for carbapenem usage and correlation with carbapenem resistance of Pseudomonas aeruginosa,” Journal of Infection and Chemotherapy, vol. 24, no. 12, pp. 949–953, 2018.
View at: Publisher Site | Google Scholar
D. Zhang, S. Hu, J. Sun et al., “Antibiotic consumption versus the prevalence of carbapenem-resistant Gram-negative bacteria at a tertiary hospital in China from 2011 to 2017,” Journal of Infection and Public Health, vol. 12, no. 2, pp. 195–199, 2019.
View at: Publisher Site | Google Scholar
G. Barberi, M. C. De Cola, D. C. Dell’Utri et al., “Antimicrobial consumption and antimicrobial resistance: a snapshot of an Italian neuromuscular rehabilitation center,” New Microbiologica, vol. 40, no. 2, pp. 119–129, 2017.
View at: Google Scholar
C. Kenyon, J. Buyze, and T. Wi, “Antimicrobial consumption and susceptibility of Neisseria gonorrhoeae: a global ecological analysis,” Frontiers of Medicine, vol. 5, p. 329, 2018.
View at: Publisher Site | Google Scholar
D. A. Rosado-Rosado, R. Arias-Flores, J. G. Vázquez-Rosales, R. J. Robles-Ramírez, R. Del Campo-Ortega, and I. J. Ascencio-Montiel, “Antimicrobial resistance and antibiotic consumption in a third level pediatric hospital in Mexico City,” The Journal of Infection in Developing Countries, vol. 15, no. 04, pp. 573–578, 2021.
View at: Publisher Site | Google Scholar
W. Guo, F. Sun, F. Liu, L. Cao, J. Yang, and Y. Chen, “Antibiotic resistance surveillance and prediction of Gram-negative bacteria based on antibiotic consumption in a hospital setting: a 15-year retrospective study,” Medicine, vol. 98, no. 37, Article ID e17157, 2019.
View at: Publisher Site | Google Scholar
P. Yang, Y. Chen, S. Jiang, P. Shen, X. Lu, and Y. Xiao, “Association between antibiotic consumption and the rate of carbapenem-resistant Gram-negative bacteria from China based on 153 tertiary hospitals data in 2014,” Antimicrobial Resistance and Infection Control, vol. 7, no. 1, p. 137, 2018.
View at: Publisher Site | Google Scholar
P. Yang, Y. Chen, S. Jiang, P. Shen, X. Lu, and Y. Xiao, “Association between the rate of fluoroquinolones-resistant gram-negative bacteria and antibiotic consumption from China based on 145 tertiary hospitals data in 2014,” BMC Infectious Diseases, vol. 20, no. 1, p. 269, 2020.
View at: Publisher Site | Google Scholar
P. Yang, Y. Chen, S. Jiang, P. Shen, X. Lu, and Y. Xiao, “Association between the rate of third generation cephalosporin-resistant Escherichia coli and Klebsiella pneumoniae and antibiotic consumption based on 143 Chinese tertiary hospitals data in 2014,” European Journal of Clinical Microbiology and Infectious Diseases, vol. 39, no. 8, pp. 1495–1502, 2020.
View at: Publisher Site | Google Scholar
M. Barchitta, A. Maugeri, M. C. La Rosa et al., “Carbapenem Consumption and Rate of carbapenem resistant gram-negative bacteria: results from the Sicilian Surveillance System,” Annals of Hygiene, Preventive and Community Medicine, vol. 33, no. 3, pp. 289–296, 2021.
View at: Publisher Site | Google Scholar
F. Terahara and H. Nishiura, “Carbapenem-resistant Pseudomonas aeruginosa and carbapenem use in Japan: an ecological study,” Journal of International Medical Research, vol. 47, no. 10, pp. 4711–4722, 2019.
View at: Publisher Site | Google Scholar
M. R. Seo, B. Kim, J. Kim, and H. Pai, “Change in antimicrobial susceptibility and PCR ribotypes of Clostridioides difficile in a hospital over 5 years: correlation analysis with antimicrobial consumption,” International Journal of Antimicrobial Agents, vol. 54, no. 2, pp. 154–158, 2019.
View at: Publisher Site | Google Scholar
R. Kousovista, C. Athanasiou, K. Liaskonis, O. Ivopoulou, G. Ismailos, and V. Karalis, “Correlation between Acinetobacter baumannii resistance and hospital use of meropenem, cefepime, and ciprofloxacin: time series analysis and dynamic regression models,” Pathogens, vol. 10, no. 4, p. 480, 2021.
View at: Publisher Site | Google Scholar
M. Mascarello, O. Simonetti, A. Knezevich et al., “Correlation between antibiotic consumption and resistance of bloodstream bacteria in a University Hospital in North Eastern Italy, 2008–2014,” Infection, vol. 45, no. 4, pp. 459–467, 2017.
View at: Publisher Site | Google Scholar
S. Mladenovic-Antic, B. Kocic, R. Velickovic-Radovanovic et al., “Correlation between antimicrobial consumption and antimicrobial resistance of Pseudomonas aeruginosa in a hospital setting: a 10-year study,” Journal of Clinical Pharmacy and Therapeutics, vol. 41, no. 5, pp. 532–537, 2016.
View at: Publisher Site | Google Scholar
N. Prakobsrikul, K. Malathum, P. Santanirand, S. Chumnumwat, P. Piebpien, and P. Montakantikul, “Correlation between antibiotic consumption and the prevalence of carbapenem‐resistant Escherichia coli and carbapenem-resistant Klebsiella pneumoniae at a university hospital in Thailand,” Journal of Clinical Pharmacy and Therapeutics, vol. 44, no. 2, pp. 292–299, 2019.
View at: Publisher Site | Google Scholar
V. Zivanovic, L. Gojkovic-Bukarica, R. Scepanovic et al., “Differences in antimicrobial consumption, prescribing and isolation rate of multidrug resistant Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii on surgical and medical wards,” PLoS One, vol. 12, no. 5, Article ID e0175689, 2017.
View at: Publisher Site | Google Scholar
C.-C. Lai, Z.-Y. Shi, Y.-H. Chen, and F.-D. Wang, “Effects of various antibiotic stewardship programs on antibiotic usage and resistance among common gram-negative bacilli causing health care-associated infections: a multicenter comparison,” Journal of Microbiology, Immunology, and Infection, vol. 49, 2016.
View at: Google Scholar
F. Olearo, A. Both, C. Belmar Campos et al., “Emergence of linezolid-resistance in vancomycin-resistant Enterococcus faecium ST117 associated with increased linezolid-consumption,” International Journal of Medical Microbiology, vol. 311, no. 2, Article ID 151477, 2021.
View at: Publisher Site | Google Scholar
R. Popović, Z. Tomić, A. Tomas et al., “Five-year surveillance and correlation of antibiotic consumption and resistance of Gram-negative bacteria at an intensive care unit in Serbia,” Journal of Chemotherapy, vol. 32, no. 6, pp. 294–303, 2020.
View at: Publisher Site | Google Scholar
F. Terahara and H. Nishiura, “Fluoroquinolone consumption and Escherichia coli resistance in Japan: an ecological study,” BMC Public Health, vol. 19, no. 1, p. 426, 2019.
View at: Publisher Site | Google Scholar
S. Shakoor, S. Tahseen, K. Jabeen et al., “Fluoroquinolone consumption and-resistance trends in Mycobacterium tuberculosis and other respiratory pathogens: ecological antibiotic pressure and consequence s in Pakistan, 2009–2015,” International Journal of Mycobacteriology, vol. 5, no. 4, pp. 412–416, 2016.
View at: Publisher Site | Google Scholar
H. Wang, H. Wang, X. Yu et al., “Impact of antimicrobial stewardship managed by clinical pharmacists on antibiotic use and drug resistance in a Chinese hospital, 2010–2016: a retrospective observational study,” BMJ Open, vol. 9, no. 8, Article ID e026072, 2019.
View at: Publisher Site | Google Scholar
J. Ruiz, M. Gordon, E. Villarreal et al., “Influence of antibiotic pressure on multi-drug resistant Klebsiella pneumoniae colonisation in critically ill patients,” Antimicrobial Resistance and Infection Control, vol. 8, no. 1, p. 38, 2019.
View at: Publisher Site | Google Scholar
L. Baditoiu, C. Axente, D. Lungeanu et al., “Intensive care antibiotic consumption and resistance patterns: a cross-correlation analysis,” Annals of Clinical Microbiology and Antimicrobials, vol. 16, no. 1, p. 71, 2017.
View at: Publisher Site | Google Scholar
A. Cusini, D. Herren, L. Bütikofer, C. Plüss-Suard, A. Kronenberg, and J. Marschall, “Intra-hospital differences in antibiotic use correlate with antimicrobial resistance rate in Escherichia coli and Klebsiella pneumoniae: a retrospective observational study,” Antimicrobial Resistance and Infection Control, vol. 7, no. 1, p. 89, 2018.
View at: Publisher Site | Google Scholar
A. Marquet, M. A. Vibet, J. Caillon et al., “Is there an association between use of amoxicillin-clavulanate and resistance to third-generation cephalosporins in Klebsiella pneumoniae and Escherichia coli at the hospital level?” Microbial Drug Resistance, vol. 24, no. 7, pp. 987–994, 2018.
View at: Publisher Site | Google Scholar
T. Kastrin, M. Paragi, V. Erculj, T. Žohar Čretnik, T. Bajec, and M. Cižman, “Lack of correlation between reduced outpatient consumption of macrolides and macrolide resistance of invasive Streptococcuspneumoniae isolates in Slovenia during 1997–2017,” Journal of Global Antimicrobial Resistance, vol. 16, pp. 242–248, 2019.
View at: Publisher Site | Google Scholar
L. McDonnell, D. Armstrong, M. Ashworth, A. Dregan, U. Malik, and P. White, “National disparities in the relationship between antimicrobial resistance and antimicrobial consumption in Europe: an observational study in 29 countries,” Journal of Antimicrobial Chemotherapy, vol. 72, no. 11, pp. 3199–3204, 2017.
View at: Publisher Site | Google Scholar
C. Kenyon, J. Buyze, G. Spiteri, M. J. Cole, and M. Unemo, “Population level consumption of cephalosporins and macrolides may select for reduced antibiotic susceptibility to unrelated antibiotics in Neisseria gonorrhoeae: an ecological analysis,” The Journal of Infectious Diseases, vol. 221, no. 7, pp. 1107–1116, 2020.
View at: Publisher Site | Google Scholar
C. Kenyon, “Population-level macrolide consumption is associated with clarithromycin resistance in Helicobacter pylori: an ecological analysis,” International Journal of Infectious Diseases, vol. 85, pp. 67–69, 2019.
View at: Publisher Site | Google Scholar
C. Kenyon, “Prevalence of macrolide resistance in Treponema pallidum is associated with macrolide consumption,” Journal of Medical Microbiology, vol. 68, no. 2, pp. 119–123, 2019.
View at: Publisher Site | Google Scholar
Z. M. Djordjevic, M. M. Folic, and S. M. Jankovic, “Previous antibiotic exposure and antibiotic resistance patterns of acinetobacter spp. and Pseudomonas aeruginosa isolated from patients with nosocomial infections,” Balkan Medical Journal, vol. 34, no. 6, pp. 527–533, 2017.
View at: Publisher Site | Google Scholar
Á. C. D. S. Ribeiro, M. T. L. Crozatti, A. A. Silva, R. S. Macedo, A. M. D. O. Machado, and A. T. D. A. P. Silva, “Pseudomonas aeruginosa in the ICU: prevalence, resistance profile, and antimicrobial consumption,” Journal of the Brazilian Society of Tropical Medicine, vol. 53, Article ID e20180498, 2019.
View at: Publisher Site | Google Scholar
S. Ryu, E. Y. Klein, and B. C. Chun, “Temporal association between antibiotic use and resistance in Klebsiella pneumoniae at a tertiary care hospital,” Antimicrobial Resistance and Infection Control, vol. 7, no. 1, p. 83, 2018.
View at: Publisher Site | Google Scholar
J. Nadia, M. Wejdene, B. Remy A et al., “Temporal variation in antibiotic resistance of Acinetobacter baumannii in a teaching hospital in Tunisia: correlation with antibiotic consumption,” The Open Microbiology Journal, vol. 13, no. 1, pp. 106–111, 2019.
View at: Publisher Site | Google Scholar
E. Batard, M.-A. Vibet, S. Thibaut et al., “Tetracycline use in the community may promote decreased susceptibility to quinolones in Escherichia coli isolates,” European Journal of Clinical Microbiology and Infectious Diseases, vol. 37, no. 2, pp. 271–276, 2018.
View at: Publisher Site | Google Scholar
O. Hongchumpae and W. Santimaleeworagun, “The correlation between defined daily dose/1000 patient-day of antibiotics 3 the resistance rate of P. aeruginosa and A. Baumannii: a case study at hua-hin hospital,” Thai Pharmaceutical and Health Science Journal, vol. 11, no. 1, pp. 27–32, 2016.
View at: Google Scholar
M. A. Asencio Egea, M. Huertas Vaquero, R. Carranza González, Ó. Herráez Carrera, O. Redondo González, and Á. Arias Arias, “Trend and seasonality of community-acquired Escherichia coli antimicrobial resistance and its dynamic relationship with antimicrobial use assessed by ARIMA models,” Infectious Diseases and Clinical Microbiology, vol. 36, no. 8, pp. 502–506, 2018.
View at: Publisher Site | Google Scholar
D. Granov, A. D. Ljubovic, S. L. Zec, N. Granov, and M. Hukic, “The impact of antibiotic consumption on development of acinetobacter baumannii resistance,” Materia Socio Medica, vol. 28, no. 6, pp. 449–453, 2016.
View at: Publisher Site | Google Scholar
C. Liang, X. Zhang, L. Zhou, G. Meng, L. Zhong, and P. Peng, “Trends and correlation between antibacterial consumption and carbapenem resistance in gram-negative bacteria in a tertiary hospital in China from 2012 to 2019,” BMC Infectious Diseases, vol. 21, no. 1, p. 444, 2021.
View at: Publisher Site | Google Scholar
B. Kim, Y. Kim, H. Hwang et al., “Trends and correlation between antibiotic usage and resistance pattern among hospitalized patients at university hospitals in Korea, 2004 to 2012. A nationwide multicenter study,” Medicine, vol. 97, Article ID e13719, 2018.
View at: Publisher Site | Google Scholar
R. Wang, Q. Yang, S. Zhang, Y. Hong, M. Zhang, and S. Jiang, “Trends and correlation of antibiotic susceptibility and antibiotic consumption at a large teaching hospital in China (2007–2016): a surveillance study,” Therapeutics and Clinical Risk Management, vol. 15, pp. 1019–1027, 2019.
View at: Publisher Site | Google Scholar
H. Wushouer, Z.-X. Zhang, J.-H. Wang et al., “Trends and relationship between antimicrobial resistance and antibiotic use in Xinjiang Uyghur Autonomous Region, China: based on a 3 year surveillance data, 2014–2016,” Journal of Infection and Public Health, vol. 11, pp. 339–346, 2018.
View at: Publisher Site | Google Scholar
D. Zhang, K. Cui, T. Wang et al., “Trends in and correlations between antibiotic consumption and resistance of Staphylococcus aureus at a tertiary hospital in China before and after introduction of an antibiotic stewardship program,” Epidemiology and Infection, vol. 147, no. 48, pp. 1–6, 2019.
View at: Publisher Site | Google Scholar
Y. A. Kim, Y. S. Park, T. Youk, H. Lee, and K. Lee, “Trends in South Korean antibiotic use and association with changes in Escherichia coli resistance rates: 12-year ecological study using a nationwide surveillance and antibiotic prescription database,” PLoS One, vol. 13, no. 12, Article ID e0209580, 2018.
View at: Publisher Site | Google Scholar
E. P. Martinez, J. van Rosmalen, R. Bustillos, S. Natsch, J. W. Mouton, and A. Verbon, “Trends, seasonality and the association between outpatient antibiotic use and antimicrobial resistance among urinary bacteria in The Netherlands,” Journal of Antimicrobial Chemotherapy, vol. 75, no. 8, pp. 2314–2325, 2020.
View at: Publisher Site | Google Scholar
A. Wang, N. Daneman, C. Tan, J. S. Brownstein, and D. R. MacFadden, “Evaluating the relationship between hospital antibiotic use and antibiotic resistance in common nosocomial pathogens,” Infection Control and Hospital Epidemiology, vol. 38, no. 12, pp. 1457–1463, 2017.
View at: Publisher Site | Google Scholar
S. Chen, Z. Li, J. Shi et al., “A nonlinear time-series analysis to identify the thresholds in relationships between antimicrobial consumption and resistance in a Chinese tertiary hospital,” Infectious Disease and Therapy, vol. 11, no. 3, pp. 1019–1032, 2022.
View at: Publisher Site | Google Scholar
G. Pérez-Lazo, S. Abarca-Salazar, R. Lovón et al., “Antibiotic consumption and its relationship with bacterial resistance profiles in ESKAPE pathogens in a Peruvian hospital,” Antibiotics, vol. 10, p. 1221, 2021.
View at: Publisher Site | Google Scholar
S. Barnsteiner, F. Baty, W. C. Albrich et al., “Antimicrobial resistance and antibiotic consumption in intensive care units, Switzerland, 2009 to 2018,” Euro Surveillance, vol. 26, no. 46, 2021.
View at: Publisher Site | Google Scholar
M. Cižman, V. Mioč, T. Bajec, M. Paragi, T. Kastrin, and J. Gonçalves, “Correlation between antibiotic consumption and resistance of invasive Streptococcus pneumoniae,” Antibiotics, vol. 10, no. 7, p. 758, 2021.
View at: Publisher Site | Google Scholar
H.-W. Huang, H.-Y. Liu, H.-C. Chuang et al., “Correlation between antibiotic consumption and resistance of Pseudomonas aeruginosa in a teaching hospital implementing an antibiotic stewardship program: a longitudinal observational study,” Journal of Microbiology, Immunology, and Infection, vol. 56, no. 2, pp. 337–343, 2023.
View at: Publisher Site | Google Scholar
S. Khare, V. Diwan, A. Pathak, M. R. Purohit, and C. Stålsby Lundborg, “Correlation between individual child-level antibiotic consumption and antibiotic-resistant among commensal Escherichia coli: results from a cohort of children aged 1–3 Years in rural ujjain India,” Infection and Drug Resistance, vol. 15, pp. 6255–6266, 2022.
View at: Publisher Site | Google Scholar
S. Manoharan-Basil, N. Gonzalez, and C. Kenyon, “Country-level association between antibiotic consumption and resistance in Neisseria meningitidis: an ecological study,” Journal of Infection and Public Health, vol. 15, no. 3, pp. 293–296, 2022.
View at: Publisher Site | Google Scholar
F. Megraud, R. Bruyndonckx, S. Coenen et al., “Helicobacter pylori resistance to antibiotics in Europe in 2018 and its relationship to antibiotic consumption in the community,” Gut, vol. 70, no. 10, pp. 1815–1822, 2021.
View at: Publisher Site | Google Scholar
W. A. Hayajneh, S. Al-Azzam, D. Yusef et al., “Identification of thresholds in relationships between specific antibiotic use and carbapenem-resistant Acinetobacter baumannii (CRAb) incidence rates in hospitalized patients in Jordan,” Journal of Antimicrobial Chemotherapy, vol. 76, no. 2, pp. 524–530, 2021.
View at: Publisher Site | Google Scholar
W. Gong, W. Tang, L. Luo et al., “Trends and correlation between antimicrobial resistance and antibiotics consumption in a specialist children’s hospital from 2016 to 2021,” Infection and Drug Resistance, vol. 15, pp. 5679–5689, 2022.
View at: Publisher Site | Google Scholar
G. V. Asokan, T. Ramadhan, E. Ahmed, and H. Sanad, “WHO global priority pathogens list: a bibliometric analysis of medline PubMed for knowledge mobilization to infection prevention and control practices in Bahrain,” Oman Medical Journal, vol. 34, no. 3, pp. 184–193, 2019.
View at: Publisher Site | Google Scholar
R. Balasubramanian, T. P. Van Boeckel, Y. Carmeli, S. Cosgrove, and R. Laxminarayan, “Global incidence in hospital-associated infections resistant to antibiotics: an analysis of point prevalence surveys from 99 countries,” PLoS Medicine, vol. 20, no. 6, Article ID e1004178, 2023.
View at: Publisher Site | Google Scholar
R. Pandey, S. K. Mishra, and A. Shrestha, “Characterisation of ESKAPE pathogens with special reference to multidrug resistance and biofilm production in a Nepalese hospital,” Infection and Drug Resistance, vol. 14, pp. 2201–2212, 2021.
View at: Publisher Site | Google Scholar
Y. Cai, G. S. R. Hoo, W. Lee et al., “Estimating the economic cost of carbapenem resistant Enterobacterales healthcare associated infections in Singapore acute-care hospitals,” PLOS Global Public Health, vol. 2, no. 12, Article ID e0001311, 2022.
View at: Publisher Site | Google Scholar
Global, “Global point prevalence survey: impact and Value,” 2023, https://www.global-pps.com/wp-content/uploads/2023/03/2023-GLOBAL-PPS-Selection-of-Publications-FINAL-INTERACTIVE-LINKS-V2-1.pdf.
View at: Google Scholar
J. O’Neill, in Review on Abr: Antibiotic Resistance: Tackling A Crisis for the Health and Wealth of Nations, Antimicrobial Resistance, Oxford, UK, 2016.
T. P. Van Boeckel, S. Gandra, A. Ashok et al., “Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data,” The Lancet Infectious Diseases, vol. 14, no. 8, pp. 742–750, 2014.
View at: Publisher Site | Google Scholar
A. J. Browne, M. G. Chipeta, G. Haines-Woodhouse et al., “Global antibiotic consumption and usage in humans, 2000–18: a spatial modelling study,” The Lancet Planetary Health, vol. 5, no. 12, pp. e893–e904, 2021.
View at: Publisher Site | Google Scholar
S. Y. Tan, R. A. Khan, K. E. Khalid, C. W. Chong, and A. Bakhtiar, “Correlation between antibiotic consumption and the occurrence of multidrug-resistant organisms in a Malaysian tertiary hospital: a 3-year observational study,” Scientific Reports, vol. 12, no. 1, p. 3106, 2022.
View at: Publisher Site | Google Scholar
G. Gebreyohannes, A. Nyerere, C. Bii, and D. B. Sbhatu, “Challenges of intervention, treatment, and antibiotic resistance of biofilm-forming microorganisms,” Heliyon, vol. 5, 2019.
View at: Google Scholar
A. V. Sabrot, A. A. Mohamed, E. Faradjeva et al., “Mechanisms and impact of biofilms and targeting of biofilms using bioactive compounds—a review,” Medicine, vol. 57, p. 839, 2021.
View at: Publisher Site | Google Scholar
B. G. Bell, F. Schellevis, E. Stobberingh, H. Goossens, and M. Pringle, “A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance,” BMC Infectious Diseases, vol. 14, p. 13, 2014.
View at: Google Scholar
C.-T. Wu, C.-L. Chen, H.-Y. Lee et al., “Decreased antibiotic resistance and defined daily doses after implementation of a clinical culture-guided antibiotic stewardship program in a local hospital,” Journal of Microbiology, Immunology, and Infection, vol. 50, 2017.
View at: Google Scholar
B. Cunha, “Strategies to control antibiotic resistance,” Seminars in Respiratory Infections, vol. 17, no. 3, pp. 250–258, 2002.
View at: Publisher Site | Google Scholar
P. D. Tamma, E. Avdic, J. F. Keenan et al., “What is the more effective antibiotic stewardship Intervention: pre-prescription Authorization or Post-prescription review with Feedback?” Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America, vol. 64, no. 5, pp. 537–543, 2017.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2024 Asrat Agalu Abejew et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

265

Downloads

220

Citations