LRTIs are a leading cause of morbidity and mortality around the world. According to the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2017, nearly 2.56 million deaths resulted from LRTIs in 2017, making LRTI the fifth leading cause of mortality for all ages [
Previous studies have found that many risk factors might be associated with the development of MDR bacteria, including prior antibiotic use [
We conducted the study following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines [
PubMed, EMBASE (via Ovid), and Cochrane Library were searched systematically for studies on the risk factors for MDR bacteria in LRTIs up to November 30, 2019. The free text words such as “Gram-Negative Bacteria,” “Acinetobacter baumannii,” “Pseudomonas aeruginosa,” “Escherichia coli,” “Klebsiella pneumoniae,” “Methicillin-Resistant Staphylococcus aureus,” “MRSA,” “Enterobacteriaceae,” “Carbapenem-Resistant Enterobacteriaceae,” “Multiple Drug Resistance,” “Respiratory Tract Infections,” “Pneumonia,” “Hospital-acquired pneumonia,” “Ventilator-associated pneumonia,” “Community-acquired pneumonia (CAP),” and “Bronchopneumonia” and Medical Subject Headings (MeSH) were combined with the Boolean operators “AND” or “OR.” We listed the detailed retrieval strategies in Tables
We had access to all published articles that evaluated the risk factors for MDR bacteria in LRTIs and included prospective or retrospective cohorts that included adult patients with LRTIs and were published in English. We excluded studies if they were case reports, case series, animal studies, or review; if they included nonrespiratory tract infection patients or pediatric patients; if they reported MDR organisms less than ten cases; if they merely reported the results of unadjusted analysis; and if the full texts of them were unavailable. For articles that covered the same population as other articles, if the articles provided new information, we considered them were qualified, and if not, we chose the article with better homogeneity when it was synthesized with other studies.
The literature selection was performed independently by two researchers (G. C and KL. X), and any disagreements were resolved by consensus. We accepted MDR organisms as defined by individual studies, even if the definitions were inconsistent across studies. One definition of MDR is the development of resistance to more than three antibiotic classes known to be active against these pathogens [
Two researchers (G.C and KL.X) independently extracted the following information: author, year of publication, countries, type of study, setting, sample sizes, the definition of MDR, age, and all reported risk factors. If no consensus can be reached on the disagreement, another reviewer would participate in the decision-making. We used standardized data extraction sheets made by Microsoft Excel 2019 for data extraction.
We conducted the risk of bias assessment of eligible studies based on Quality in Prognosis Studies (QUIPS) tool [
We calculated the pooled odds ratio (OR) with a 95% confidence interval (CI). The
A total of 3, 607 articles were retrieved, and 21 articles [
PRISMA 2009 flow diagram in literature screening; nontarget population refers to nonrespiratory tract infection patients or pediatric patients; no interesting outcomes refer to no adjusted analysis results for risk factors were reported in eligible studies.
Among the 21 eligible articles, nine were prospective studies [
The baseline characteristics of included studies.
Study ID | Year | Study type | Countries | No. of centers | Setting | Population | No. of patients | No. of MDROs | MDR strains | Age (years)a | Male (%) |
---|---|---|---|---|---|---|---|---|---|---|---|
Villafuerte and Aliberti [ | 2019 | Prospective | 54 countries | 222 | Internal and emergency medicine, infectious diseases, critical care and pulmonary medicine | CAP | 3193 | 38 | EB | 68.0 (54.0, 80.0) | 58.8 |
Restrepo et al. [ | 2017 | Prospective | 54 countries | 222 | Internal and emergency medicine, infectious diseases, critical care and pulmonary medicine | CAP | 133 | 33 | PA | 64.4 (52.5, 78.5) | 59.4 |
Feng et al. [ | 2019 | Retrospective | China | Single | Pulmonary and critical care medicine, surgical ICU | HAP | 313 | 193 | EB, SA | NA | 72.5 |
VAP | 106 | 78 | EB, SA | NA | 67.0 | ||||||
Zhou et al. [ | 2018 | Retrospective | China | Single | Institute of Respiratory Diseases, Division of Respiratory Diseases of Department of Internal Medicine, Department of Pediatrics | HAP | 157 | 69 | PA | 57.8 ± 17.8 | 71.3 |
Luan et al. [ | 2018 | Retrospective | China | Single | Department of Infectious Diseases | CAP | 176 | 29 | EB, SA, SP | 68.3 ± 4.3 | 53.4 |
Lewis et al. [ | 2018 | Retrospective | USA | Single | Trauma ICU | VAP | 397 | 135 | AB, PA | 45.0 (16.0, 85.0) | 78.0 |
Gao et al. [ | 2018 | Retrospective | China | Single | Department of Respiratory and Critical Care Medicine, Department of Emergency Medicine | Bronchiectasis | 88 | 34 | PA | 59.7 ± 18.2 | 52.3 |
Song et al. [ | 2017 | Retrospective | Korea | 3 | NA | HDAP | 105 | 24 | GPB & GNB | 71.0 (61.0, 76.0) | 64.8 |
Fernandez-Barat et al. [ | 2017 | Prospective | Spain | Single | Medical and surgical ICUs | ICUAP | 64 | 22 | PA | 66.0 ± 15.0 | 73.4 |
Huang et al. [ | 2016 | Retrospective | China | Single | Medical ICU | Pneumonia | 263 | 154 | GPB & GNB | 72.9 ± 14.1 | 62.3 |
Cillóniz et al. [ | 2016 | Prospective | Spain | Single | Hospital clinic | CAP | 77 | 22 | PA | 71.4 ± 14.6 | 84.4 |
Tedja et al. [ | 2014 | Retrospective | USA | Single | Medical, surgical, cardiovascular, coronary, and neurologic ICU | VAP | 107 | 49 | GPB & GNB | 62.0 ± 14.0 | 55.0 |
Özgür et al. [ | 2014 | Retrospective | Turkey | Single | Medical, surgical, adult ICU | VAP | 134 | 34 | AB | 53.2 ± 21.0 | 59.0 |
Gross et al. [ | 2014 | Retrospective | USA | Single | Academic medical center | CAP or HCAP | 521 | 20 | GPB & GNB | 65.0 (52.0, 79.0) | 44.5 |
Wang et al. [ | 2013 | Prospective | China | Single | Tertiary teaching hospital | HAP | 102 | 24 | MRSA | 74.9 ± 12.4 | 64.7 |
Zheng et al. [ | 2013 | Retrospective | China | Single | Hospital affiliated to a university | Pneumonia | 242 | 97 | AB | 61.4 ± 9.8 | 54.9 |
Seligman et al. [ | 2013 | Retrospective | Brazil | Single | Tertiary care teaching hospital | HAP | 140 | 59 | GPB & GNB | 63.0 ± 14.4 | 70.0 |
Hamet et al. [ | 2012 | Prospective | France | Single | ICU | VAP | 323 | 90 | GPB & GNB | 63.4 ± 15.2 | 66.9 |
Shi et al. [ | 2010 | Prospective | China | Single | Hospital affiliated to a university | Pneumonia | 475 | 57 | GNB | 42.6 ± 11.3 | 89.7 |
Depuydt et al. [ | 2008 | Prospective | Belgium | Single | Medical and surgical ICU | VAP | 192 | 52 | GPB & GNB | 59.4 ± 16.1 | 71.9 |
Nseir and Ader [ | 2006 | Prospective | France | Single | ICU | AECOPD | 788 | 69 | GPB & GNB | 66.2 ± 11.9 | 76.8 |
aMean ± SD or median (IQR); MDR: multidrug resistance; MDROs: multidrug-resistant organisms; no.: number; ICU: intensive care unit; CAP: community-acquired pneumonia; HAP: hospital-acquired pneumonia; VAP: ventilator-associated pneumonia; HDAP: hemodialysis-associated pneumonia; ICUAP: intensive care unit-acquired pneumonia; HCAP: healthcare-associated pneumonia; AECOPD: acute exacerbation of chronic obstructive pulmonary disease; GNB: Gram-negative bacteria; GPB and GNB: Gram-negative bacteria and Gram-positive bacteria; EB: Enterobacteriaceae; PA:
The risk of bias of the included articles is listed in Table
Risk of bias assessment of eligible studies based on QUIPS tool.
Study ID | Study participation | Study attrition | Prognostic factor measurement | Outcome measurement | Study confounding | Statistical analysis and reporting | Overall risk of bias |
---|---|---|---|---|---|---|---|
Vilafuerte and Aliberti [ | Low | Low | Low | Low | Low | Low | Low |
Restrepo et al. [ | Low | Low | Low | Low | Low | Low | Low |
Feng et al. [ | Low | Low | Moderate | Low | Moderate | Low | Moderate |
Zhou et al. [ | Low | Low | Low | Low | Low | Low | Low |
Luan et al. [ | Low | Low | High | High | Low | Low | High |
Lewis et al. [ | Low | Low | Low | Low | Low | Low | Low |
Gao et al. [ | Low | Low | Low | Low | Low | Low | Low |
Song et al. [ | Low | Low | Low | Low | Low | Low | Low |
Fernandez-Barat et al. [ | Low | Low | High | High | Low | Low | High |
Huang et al. [ | Low | Low | Low | Low | Low | Low | Low |
Cillóniz et al. [ | Low | Low | Low | Moderate | Low | Low | Low |
Tedja et al. [ | Low | Low | Moderate | Moderate | Moderate | Low | Moderate |
Özgüret al. [ | Low | Low | Low | Low | Low | Low | Low |
Grosset al. [ | Low | Low | Low | Low | Low | Low | Low |
Wang et al. [ | Moderate | Low | Moderate | Low | Moderate | Low | Moderate |
Zheng et al. [ | Moderate | Low | Low | Low | Low | Low | Low |
Seligman et al. [ | Moderate | Low | Low | Low | Low | Low | Low |
Hamet et al. [ | Low | Low | Low | Low | Low | Low | Low |
Shi et al. [ | Moderate | Low | Low | Low | Moderate | Low | Moderate |
Depuydt et al. [ | Low | Low | Low | Low | Low | Low | Low |
Nseir and Ader [ | Low | Low | Low | Low | Low | Low | Low |
In the meta-analysis, the risk factors significantly associated with the acquisition of MDR bacteria are described in the Results section. Additionally, other risk factors that are statistically significantly associated with the acquisition of MDR bacteria but are not suitable for meta-analysis are listed in Table
Prior antibiotic treatment is the most frequently reported risk factor that is correlated with the acquisition of MDR bacteria [
Forest plot of the meta-analysis regarding the MDR bacterial infection due to prior antibiotic treatment in the random-effects model. OR: odds ratio; CI: confidence interval.
In patients, chronic lung disease [
Risk factors of MDR bacteria in terms of comorbidities
Risk factors | No. of included studies | No. of included MDROs | Heterogeneity | Synthesized results |
---|---|---|---|---|
Chronic lung disease [ | 5 | 420 | OR: 2.19; 95% CI: 1.51 to 3.19 | |
Chronic liver disease [ | 2 | 60 | OR: 3.41; 95% CI: 1.55 to 7.51 | |
Cardiac disease [ | 2 | 97 | OR: 0.67; 95% CI: 0.25 to 1.86 | |
Cerebral disease [ | 3 | 308 | OR: 2.98; 95% CI: 1.37 to 6.50 | |
Renal replacement therapy [ | 3 | 131 | OR: 0.78; 95% CI: 0.41 to 1.48 |
MDROs: multidrug-resistant organisms.
Three studies [
For recent hospitalization, two of the included studies [
In the random-effects model, recent hospitalization [
Previous or present endotracheal intubation increased the risk of MDR bacteria obviously (OR: 6.56; 95% CI: 1.03 to 41.94;
Furthermore, the higher the disease severity scores, the higher the risk of the infection with MDR bacteria (OR: 2.29; 95% CI: 1.41 to 3.74;
For studies included in the meta-analysis which assessed prior antibiotic treatment [
We subdivided studies reporting prior antibiotic treatment into different groups, from which we obtained similar results to the overall results when the eligible studies were divided by kinds of organisms or definitions of MDR. Meanwhile, the subgroup analysis divided by diagnosis showed that prior antibiotic treatment was a risk factor for the acquisition of MDR bacteria in patients with HAP [
Subgroup analysis of studies reporting prior antibiotic treatment as a risk factor.
Subgroups | No. of included studies | Heterogeneity | Synthesized results |
---|---|---|---|
Divided by diagnosis | |||
CAP [ | 3 | OR: 1.92; 95% CI: 0.65 to 5.70 | |
HAP [ | 3 | OR: 2.40; 95% CI: 1.52 to 3.80 | |
VAP [ | 2 | OR: 2.63; 95% CI: 1.24 to 5.55 | |
Pneumonia [ | 2 | OR: 3.87; 95% CI: 1.97 to 7.59 | |
Bronchiectasis [ | 1 | NA | OR: 4.28; 95% CI: 1.43 to 12.80 |
AECOPD [ | 1 | NA | OR: 2.40; 95% CI: 1.21 to 4.75 |
Divided by kinds of organisms | |||
GNB [ | 4 | OR: 2.65; 95% CI: 1.01 to 6.92 | |
GNB and GPB [ | 7 | OR: 2.44; 95% CI: 1.81 to 3.30 | |
GPB [ | 1 | NA | OR: 3.81; 95% CI: 1.01 to 14.39 |
Divided by definitions of MDR | |||
Definition A [ | 9 | OR: 2.57; 95% CI: 1.72 to 3.82 | |
Definition B [ | 2 | OR: 2.56; 95% CI: 1.47 to 4.45 | |
No definition [ | 1 | NA | OR: 3.54; 95% CI: 0.98 to 12.77 |
Compared with the use of the random-effects model (DL method), when we performed data synthesis using the fixed-effects model, the pooled adjusted ORs for all risk factors did not change significantly. Nine risk factors obtained no significant result in the HKSJ method for meta-analysis, while results were statistically significant using the DL method. The results of sensitivity analysis using the fixed-effects model and HKSJ random-effects model are presented in Tables
LRTIs are highly prevalent and variable and confer considerable morbidity and mortality [
For antibiotic treatment, the present study found that prior antibiotic treatment was a significant risk factor for MDR bacterial infection in LRTIs. This finding is similar to that of the previous studies, which identified the risk factors for MDR PA infection in hospitalized patients [
The IDSA/ATS Guidelines 2016 [
Patients with comorbidities, such as chronic respiratory disease (COPD, asthma, and bronchiectasis), chronic liver disease, and cerebral disease are associated with the development of MDR bacteria, as they are particularly susceptible to bacterial infections and usually require repeated hospitalizations, antibiotic treatment, and invasive procedures [
Consistent with previous meta-analysis [
The sensitivity analysis suggested that the results of the HKSJ method did not fully agree with those of the DL method. Nine significant risk factors including inappropriate antibiotic therapy, chronic liver disease, cerebral disease, prior MDR infection, prior PA infection, endotracheal intubation, mechanical ventilation, tube feeding, and disease severity scores did not obtain significant results when using the HKSJ method, although the studies included in the meta-analysis were statistically significant with effects pointing into the same direction. This might be because the risk factors only reported by very few (i.e., 2 or 3) studies, and the HKSJ method had very low power and leads to a statistically not significant pooled effect estimate [
To the best of our knowledge, this review is the first one that conducts a meta-analysis by focusing on risk factors for MDR bacteria in LRTIs, but there are also some limitations. Firstly, due to the limited number of included studies, subgroup analyses based on diagnosis, kinds of organisms, or definitions of MDR bacteria were not conducted for most risk factors. Thus, it might limit the generalizability of the results. Secondly, the different definitions of MDR bacteria used in the original literature may introduce deviations in the results, even though most studies had the same definition that the MDR bacteria were not sensitive to at least one agent in three or more antimicrobial categories. Thirdly, some factors including previous antibiotic treatment, recent hospitalization, and previous tracheostomy were not defined consistently across studies and even were not defined clearly in some studies, leading to the reduction in the precision of the results. Fourthly, limited evidence exists to inform which method performs best for a random-effects meta-analysis, especially when studies are few in number (<5). Therefore, we applied the commonly used random-effects model (DL method) for our primary analysis. The DL method might generate too many statistically significant results when the number of studies is small and there is moderate or substantial heterogeneity [
This meta-analysis indicates that prior antibiotic treatment in the past 90 days, inappropriate antibiotic therapy, chronic lung disease, chronic liver disease, cerebral disease, prior MDR infection/colonization in the past 12 months, hospitalization in the past 90 days, longer hospitalization stay, previous endotracheal intubation or mechanical ventilation in the past 6 months, tube feeding, and higher the disease severity scores were risk factors for the acquisition of MDR bacteria. Clinicians could take into account these factors when selecting antibiotics for patients and determine whether coverage for MDR is required in clinical practice. More well-designed studies are needed to confirm the various risk factors for MDR bacteria in the future.
Gang Chen and Kailiang Xu should be considered co-first authors.
The authors declare that they have no conflicts of interest.
Gang Chen and Kailiang Xu contributed equally to this work.
Table S1: search strategies in PubMed. Table S2: search strategies in EMBASE. Table S3: search strategies in Cochrane Library. Table S4: studies excluded in the full-text screening process. Table S5: additional risk factors that had a statistically significant association with the acquisition of MDR bacteria. Table S6: results of sensitivity analysis using the fixed-effects models. Table S7: results of sensitivity analysis using the HKSJ random-effects model.