A systematic review and meta-analysis for risk factor profiles in patients with resistant Acinetobacter baumannii infection relative to control patients

Abstract

BACKGROUND:

Acinetobacter baumannii is a major cause of nosocomial infections and high mortality rates. Evaluation of risk factors for such resistant infections may aid surveillance and diagnostic initiatives, as well as, can be crucial in early and appropriate antibiotic therapy.

OBJECTIVE:

To identify the risk factors in patients with resistant A. baumannii infection with respect to controls.

METHODS:

Prospective or retrospective cohort and case-control studies reporting the risk factors for resistant A. baumannii infection were collected through two data sources, MEDLINE/PubMed and OVID/Embase. Studies published in the English language were included while animal studies were excluded. The Newcastle-Ottawa Scale was used to assess the quality of studies. The odds ratio of developing antibiotic resistance in patients with A. baumannii infection was pooled using a random-effect model.

RESULTS:

The results are based on 38 studies with 60878 participants (6394 cases and 54484 controls). A total of 28, 14, 25, and 11 risk factors were identified for multi-drug resistant (MDRAB), extensive-drug resistant (XDRAB), carbapenem-resistant (CRAB) and imipenem resistant A. baumannii infection (IRAB), respectively. In the MDRAB infection group, exposure to carbapenem (OR 5.51; 95% CI: 3.88–7.81) and tracheostomy (OR 5.01; 95% CI: 2.12–11.84) were identified with maximal pool odd’s ratio. While previous use of amikacin (OR 4.94; 95% CI: 1.89–12.90) and exposure to carbapenem (OR 4.91; 95% CI: 2.65–9.10) were the foremost factors associated with developing CRAB infection. Further analysis revealed, mechanical ventilation (OR 7.21; 95% CI: 3.79–13.71) and ICU stay (OR 5.88; 95% CI: 3.27–10.57) as the most significant factors for XDRAB infection.

CONCLUSION:

The exposure of carbapenem, amikacin (previous) and mechanical ventilation were the most significant risk factors for multidrug, extensive-drug, and carbapenem resistance in patients with A. baumannii infection respectively. These findings may guide to control and prevent resistant infections by identifying the patients at higher risk of developing resistance.

Keywords

Multidrug resistance extensive-drug resistance carbapenem resistance risk factors

1. Introduction

Acinetobacter baumannii is an aerobic non-fermenting gram-negative coccobacillus that has been reported as a prominent nosocomial pathogen with enhanced environmental resilience and a propensity to develop resistance to commonly prescribed antimicrobials [1]. Of all Acinetobacter species, A. baumannii is the most important member associated with infections in clinical practice and causes most of the reported outbreaks [2]. A. baumannii can cause infections in the blood, urinary tract, and lungs (pneumonia), as well as infections in other body wounds. It can also “colonise” or live in a patient without infecting them or creating symptoms, especially in respiratory secretions (sputum) or open wounds [3].

A. baumannii infection does not always act as an infecting pathogen due to its extensive distribution and colonisation capabilities [4,5]. Furthermore, the epidemiologic pattern of AB acquisition and dissemination appears to be distinct from that of other non-fermentative, gram-negative bacteria [5].

The emergence and spread of Acinetobacter species and its high resistance to most antibiotics available in clinical practice is an area of great concern [6]. A number of resistance mechanisms to many classes of antibiotics are known to exist in A. baumannii, including β-lactamases, multidrug efflux pumps, aminoglycoside-modifying enzymes, permeability defects, and the alteration of target sites [7–10]. In the case of carbapenem resistance, the mechanisms like beta-lactamases along with the carbapenem-hydrolysing activity including carbapenem-hydrolysing class D beta lactamases (CHDLs) and metallo-beta-lactamases (MBLs) are considered as major mechanisms [11]. Furthermore, A. baumannii appears to have a high propensity for developing antibiotic resistance [12]. The number of imipenem resistant A. baumannii strains has been continuously increasing in recent years, and these isolates are frequently multidrug-resistant [13–15].

These resistant infections often occur in older patients, many of whom have chronic underlying diseases and have previously received antimicrobial treatment [16]. In places with endemic colonization or epidemic outbreaks of infection, risk factors may differ [5,17].

Multiple studies have examined the risk variables for a resistant A. baumannii infection; however, the results have varied. Therefore, pooling of the data through meta-analysis is expected to provide concrete evidence in order to prevent infection and to optimize therapy, as well as identifying sources of diversity across various types of studies. Therefore, this study aimed to identify the risk factors in patients with resistant Acinetobacter baumannii infection with respect to controls.

2. Materials and methods

This systematic review and meta-analysis was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) checklist [18–20]. A protocol for this review was developed and registered in the PROSPERO database (CRD42022299349) [21].

2.1. Literature search

A systematic electronic search was conducted in PubMed/MEDLINE and OVID databases for citations indexed from the year 2000 to 2021. The search strategy was developed as per the Cochrane checklist of developing a search strategy [22,23]. The MeSH terms used were “Risk Factors”, “Acinetobacter baumannii”, “Drug Resistance”, “Drug Resistance, Bacterial”, “Acinetobacter baumannii infections”, “Hospitals, public”, “Hospitals, private”, “Hospitals, teaching”, “Intensive Care Units”, “Hospital units”. The full PubMed/MEDLINE search strategy is listed in Supplementary Material S1. Filters as observational studies, humans, English, and journal articles were used. In order to maximise the inclusion of relevant data, these searches were expanded by reviewing the reference lists of qualifying studies in an iterative process.

2.2. Eligibility criteria

This systematic review and meta-analysis explores the potential risk factors for developing resistant A. baumannii infection in hospitalized patients. Prospective or retrospective observational, cohort and case-control studies were eligible for inclusion which reported the data on risk factors associated with the acquisition of resistant A. baumannii infection. This research excluded interventional study designs and non-comparative observational studies, case reports, and case series.

Studies examining patients with either hospital-acquired or community-acquired infections were included, provided that those patients were evaluated in a hospital/inpatient setting. The studies of mixed infections and studies that involving animal models were excluded. Studies published as full texts in the English language since the year 2000 was considered.

2.3. Study definitions

The primary objective of this study was to examine studies evaluating risk factors/predictors in patients with resistant A. baumannii infection evaluated in the hospital setting. In this study, the hospital setting comprises all types of units, including intensive care units (ICUs), casualties, or other wards in which patients were admitted at the time of collection of resistant A. baumannii microbiological specimen and undergone further treatment in a hospital setting. For a pathogen to be considered multidrug-resistant (MDR), it must be resistant to at least one agent across at least three classes of antimicrobials. The term “extensively drug-resistant” (XDR) refers to infections that are resistant to many drugs yet still susceptible to only two or fewer classes of antibiotics. If a drug susceptibility test shows negative for at least one antibiotic, then the microorganism is considered drug sensitive (DS). However, this study accepted certain considerable variation in the definitions of the individual studies. This study considered cases as multidrug-resistant, extensive drug-resistant, or carbapenem/imipenem-resistant Acinetobacter baumannii and controls as susceptible to A. baumannii infection or no infection.

2.4. Study selection

Papers were managed using EndNote software and all citations identified by literature searches were independently screened by two researchers. In primary screening titles and abstracts were screened and full-text articles were screened in secondary screening. During the screening, conflicts were adjudicated through group discussions.

2.5. Data extraction

A single reviewer performed data extraction and risk of bias assessment. The extraction was reviewed and confirmed by at least one other reviewer. Any disagreements were resolved by a group discussion among the study team. All data was extracted into a customized Microsoft Excel sheet.

General study characteristics were extracted, including first author, study design, enrolment period, countries, and setting. The sample size of the case and control, male and female, mean/median age along with standard deviation/range were extracted in population characteristics. Potential risk factors along with their odds ratio were extracted only if at least three studies examined them and those studies reported the numbers of individuals in each comparison group.

2.6. Quality assessment

This study assessed the methodological quality of each study on predefined criteria using the New-castle Ottawa risk of bias tool which probes the risk of selection, performance, detection, attrition, reporting, and other potential biases. The NOS (Newcastle-Ottawa Scale) assessed the quality of each study based on three-dimensional criteria and included (i) selection of population (4 points), (ii) comparability of groups (2 points), and (iii) outcome/exposure of interest (3 points). The quality of studies was identified with the scores in which a score from 7–9 indicated high quality, 4–6 indicated intermediate quality and 0–3 a very high risk of bias [24].

2.7. Statistical analysis

The meta-analysis were performed using RevMan 5.4 software provided by the Cochrane collaborations [25]. The odds ratio and associated 95% confidence interval of developing antibiotic resistance in patients with A. baumannii infection were pooled. Statistical heterogeneity among studies was assessed using the I ² value in which I ² > 50% was considered the evidence of heterogeneity [26]. Depending upon the I ² value, the Mantel–Haenszel fixed or random effect models were used to pool the final evidence. Forest plots of each risk factor were synthesized to summarize the evidence.

Possible publication bias was quantitatively ruled out using Egger’s test and funnel plots which were produced in Comprehensive Meta-Analysis (CMA) software. Further the results were considered statistically significant if P-value was less than 0.05 [27]. The sensitivity analysis was performed by omitting studies one by one on each risk factor to identify the source of heterogeneity [26,28].

3. Results

3.1. Study selection

The literature search identified 1325 citations from electronic databases. After removing duplicates, 996 titles and abstracts were eligible for primary screening. Using a low threshold of eligibility criteria for review of titles and abstracts, 87 full-text articles were retrieved. Following a full-text review, 38 [12,14,29–64] articles were included for meta-analysis based on the eligibility criteria. The PRISMA diagram of this study is presented in Fig. 1. Out of the 38 eligible articles, 19 articles examined multi-drug resitant A. baumannii infection (MDRAB), and the remaining 19 articles examined carbapenem/imipenem (CRAB/IRAB) and extensive drug resistant A. baumannii infection (XDRAB).

Fig. 1.

PRISMA flow diagram.

3.2. Study characteristics

The main characteristics of included studies are represented in Table 1. The studies published from 2000-2021 included 60878 participants, of whom 6394 had resistant A. baumannii infection and 54484 were the control group with susceptible A. baumannii infections or no infections. 13 studies were conducted in China followed by 6 from the USA. The study designs in 38 articles were case-control [13], retrospective study [12], prospective cohort [8], and retrospective cohort [5]. The case and control groups were matched in 4 studies. In 31 studies the samples were selected from a single setting while in 7 studies samples were selected from multi-centre settings.

Table 1
Population characteristics of the studies

# Study Study design Enrollment period Country Setting Sample size Case Control Male (case) Female (case) Male (control) Female (control) Mean age (case) SD (Case) Mean age (Control) SD (Control)

1 Abbo 2005 Matched case control January 1, 2001, to June 30, 2001 Israel Single 236 118 118 71 47 59 59 67.7 16.42 64.4 19.15

2 Blanco 2018 Retrospective cohort May 2005 to September 2009 USA Single 7925 320 7605 184 136 4158 3447 na na na na

3 Cai 2012 Retrospective study January 2009 to August 2011 China Single 160 115 45 91 24 36 9 6.08 3.7 5.59 3.17

4 Chen 2014 Case control January 1, 2009 to June 30, 2011 China Single 150 73 77 40 33 43 34 70.8 na 71.1 na

5 Chopra 2013 Retrospective cohort January 2006 to April 2009 USA Single 274 68 206 39 29 94 112 62.5 16.4 52 25

6 Chusri 2015 Case control 1 January 2010 and 31 December 2011 Thailand Single 336 139 197 78 61 120 77 59.67 21.5 60.33 22.24

7 Cisneros 2005 Cohort During November 2000 Spain Multiple 203 88 115 62 26 84 31 54.7 na 54 na

8 Delamar 2005 Case control October 2001 and August 2002 Spain Single 61 30 31 24 6 23 8 57.1 15.7 na na

9 Dent 2010 Retrospective review 2006–2008 USA Single 164 122 42 90 32 27 15 na na na na

10 Dizbay 2010 Retrospective study 2003–2007 Turkey Single 925 524 401 na na na na na na na na

11 Fierobe 2001 Case control May 1, 1996, to March 31, 1998 France Single 30 11 19 3 8 5 14 54.4 18.8 69.6 11

12 Freire 2016 Cohort October 2009 and October 2011 Brazil Single 194 56 138 39 17 87 51 45.83 40.03 47.33 42.25

13 Fukuta 2013 Case control 2008 and 2011 USA Single 93 31 62 23 8 39 23 65 na 63 na

14 Gulen 2015 Retrospective cohort January 2007 and December 2010 Turkey Single 86 41 45 18 23 29 16 58.3 21.9 60.6 20.5

15 Guo 2016 Retrospective study June 2012–June 2015 China Single 87 64 23 na na na na 60.61 20.63 55.83 19.31

16 Henig 2015 Matched case control 2007 and 2012 Israel Multiple 2380 1190 1190 662 528 593 597 73 14 73 13.5

17 Hosoglu 2018 Matched case control April 2011 and April 2012 Turkey Single 190 95 95 48 47 46 49 38.1 25.7 43.9 26.9

18 Huang 2012 Retrospective cohort study June 2002 and December 2007 China Single 226 62 164 47 15 127 37 69.63 15.83 68.51 17.61

19 Huang 2018 Retrospective study January to December, 2015 China Multiple 489 195 294 165 30 225 69 na na na na

20 Huang 2019 Retrospective study January 2016 to December 2018 China Single 110 46 64 26 20 38 26 na na na na

21 Katragkou 2006 Case control July 2001 and December 2003 Greece Single 78 26 52 15 11 35 17 7.6 0.9 5.4 0.6

#	Study	Study design	Enrollment period	Country	Setting	Sample size	Case	Control	Male (case)	Female (case)	Male (control)	Female (control)	Mean age (case)	SD (Case)	Mean age (Control)	SD (Control)
1	Abbo 2005	Matched case control	January 1, 2001, to June 30, 2001	Israel	Single	236	118	118	71	47	59	59	67.7	16.42	64.4	19.15
2	Blanco 2018	Retrospective cohort	May 2005 to September 2009	USA	Single	7925	320	7605	184	136	4158	3447	na	na	na	na
3	Cai 2012	Retrospective study	January 2009 to August 2011	China	Single	160	115	45	91	24	36	9	6.08	3.7	5.59	3.17
4	Chen 2014	Case control	January 1, 2009 to June 30, 2011	China	Single	150	73	77	40	33	43	34	70.8	na	71.1	na
5	Chopra 2013	Retrospective cohort	January 2006 to April 2009	USA	Single	274	68	206	39	29	94	112	62.5	16.4	52	25
6	Chusri 2015	Case control	1 January 2010 and 31 December 2011	Thailand	Single	336	139	197	78	61	120	77	59.67	21.5	60.33	22.24
7	Cisneros 2005	Cohort	During November 2000	Spain	Multiple	203	88	115	62	26	84	31	54.7	na	54	na
8	Delamar 2005	Case control	October 2001 and August 2002	Spain	Single	61	30	31	24	6	23	8	57.1	15.7	na	na
9	Dent 2010	Retrospective review	2006–2008	USA	Single	164	122	42	90	32	27	15	na	na	na	na
10	Dizbay 2010	Retrospective study	2003–2007	Turkey	Single	925	524	401	na	na	na	na	na	na	na	na
11	Fierobe 2001	Case control	May 1, 1996, to March 31, 1998	France	Single	30	11	19	3	8	5	14	54.4	18.8	69.6	11
12	Freire 2016	Cohort	October 2009 and October 2011	Brazil	Single	194	56	138	39	17	87	51	45.83	40.03	47.33	42.25
13	Fukuta 2013	Case control	2008 and 2011	USA	Single	93	31	62	23	8	39	23	65	na	63	na
14	Gulen 2015	Retrospective cohort	January 2007 and December 2010	Turkey	Single	86	41	45	18	23	29	16	58.3	21.9	60.6	20.5
15	Guo 2016	Retrospective study	June 2012–June 2015	China	Single	87	64	23	na	na	na	na	60.61	20.63	55.83	19.31
16	Henig 2015	Matched case control	2007 and 2012	Israel	Multiple	2380	1190	1190	662	528	593	597	73	14	73	13.5
17	Hosoglu 2018	Matched case control	April 2011 and April 2012	Turkey	Single	190	95	95	48	47	46	49	38.1	25.7	43.9	26.9
18	Huang 2012	Retrospective cohort study	June 2002 and December 2007	China	Single	226	62	164	47	15	127	37	69.63	15.83	68.51	17.61
19	Huang 2018	Retrospective study	January to December, 2015	China	Multiple	489	195	294	165	30	225	69	na	na	na	na
20	Huang 2019	Retrospective study	January 2016 to December 2018	China	Single	110	46	64	26	20	38	26	na	na	na	na
21	Katragkou 2006	Case control	July 2001 and December 2003	Greece	Single	78	26	52	15	11	35	17	7.6	0.9	5.4	0.6

Table 1 (Continued)

#	Study	Study design	Enrollment period	Country	Setting	Sample size	Case	Control	Male (case)	Female (case)	Male (control)	Female (control)	Mean age (case)	SD (Case)	Mean age (Control)	SD (Control)
22	Katsaragakis 2008	Prospective study	June 1, 2003 to May 31, 2005	Greece	Single	52	23	29	12	11	15	14	63.9	8.6	68.2	12.1
23	Lautenbach 2009	Case control	January 1, 2001, through December 31, 2006,	USA	Multiple	386	89	297	na	na	na	na	63.22	1.31	56.3	0.9
24	Liu 2020	Prospective study	Surveillance year: 2007, 2009, 2011, 2013 and 2016	China	Multiple	317	229	88	169	60	49	39	58	4.58	59	5.49
25	Munier 2019	Prospective study	April 14 to November 4, 2014	France	Single	86	15	71	10	5	43	28	51.16	5.3	46.12	6.16
26	Prata 2012	Prospective study	August 2009 and October 2010	Brazil	Single	73	49	24	31	18	17	7	57.67	17	43.67	18.81
27	Ray 2010	Case control	January 2008 through June 2008	USA	Single	40	13	27	9	4	16	11	70.4	na	69.7	na
28	Romanelli 2009 (2007 study)	Case control	January 2007 to June 2008	Brazil	Single	153	51	102	23	28	53	49	na	na	na	na
	*Romanelli 2009 (2008 study)	Case control	January 2007 to June 2008	Brazil	Single	105	35	70	19	16	29	41	na	na	na	na
29	Routsi 2010	Prospective, observational study	September 2004 through January 2006	Greece	Single	96	30	66	21	9	43	23	58.7	19.5	56.4	18.7
30	Said 2021	Retrospective observational study	2014 and 2018	Germany	Multiple	43948	1856	42092	1187	224	18775	7878	na	na	na	na
31	Sharaf 2016	Cohort	January 2014 to December 2015	Egypt	Single	146	11	135	6	5	68	67	49	11.2	46	10.1
32	Wang 2017	Retrospective study	January 2014 to June 2015	China	Multiple	36	13	23	8	5	13	10	42.7	19.8	54.6	19.6
33	Nakwan 2010	Retrospective study	January 2005 to December 2010	Thailand	Single	22	13	9	8	5	6	3	na	na	na	na
34	Wu 2020	Retrospective study	January 2018 to December 2018	China	Single	159	100	59	78	22	43	16	73.1	13.5	69.6	17.4
35	Ye 2010	Case control	August 2001 and March 2005	China	Single	209	49	160	35	14	103	57	72.18	3.75	64.6	6.21
	*Ye 2010	Matched case control	August 2001 and March 2005	China	Single	40	20	20	12	8	14	6	na	na	na	na
36	Yeong 2019	Retrospective study	June 28, 2015 to July 31, 2015	China	Single	33	13	20	3	10	8	12	20.9	2.5	21.8	2.9
37	Zheng 2013	Retrospective cohort study	January 2006 to December 2011	China	Single	242	97	145	52	45	81	64	62.2	9.7	60.9	9.8
38	Zhou 2019	Retrospective study	January, 2013 and December, 2017	China	Single	338	274	64	190	84	45	19	62	na	62.5	na

^∗Sub-studies with different group of participants.

3.3. Quality assessment, publication bias and sensitivity analysis

The quality of all included studies was determined by NOS assessment. Out of total studies, 25 studies were of high quality and 13 were of moderate quality. None of the studies had a high risk of bias (Table 1). Sensitivity analysis by the exclusion of one study at a time showed that there were only minor changes in the quantitative pooled odd’s ratio and 95% confidence interval. No evidence of publication bias was detected according to Egger’s test and funnel plot. Sensitivity analysis and funnel plots are presented in Supplementary Materials S2–S5.

3.4. Main results

3.4.1. Risk factors for Multi-drug resitant A. baumannii infection (MDRAB) infection relative to control patients

In the case of MDRAB infection, a total of 28 risk factors were identified (Table 2). All identified risk factors were dichotomous variables. The maximal pooled odd’s ratio was seen in exposure of carbapenems [OR 5.51, 95% CI 3.88–7.80, p < 0.001], followed by tracheostomy [OR 5.01, 95% CI 2.12–11.84, p < 0.001] and urinary catheter [OR 4.57, 95% CI 2.49–8.41, p < 0.001].

Table 2
Risk factors for MDR A. baumannii infection relative to control patients

S. no Risk factor Studies Total participants Exposure of case to risk factor Total case Exposure of control to risk factor Total control Heterogeneity Model Effect estimate Z value P value Egger’s test

Chi square P value I square Intercept P-value (2 tailed)

1 Mechanical ventilation 12 2229 840 1209 486 1020 65.68 <0.00001 83 Random 3.66 [2.07, 6.48] 4.45 <0.00001 0.36751 0.86986

2 Urinary catheter 11 2031 822 1046 639 985 34.66 0.0001 71 Random 4.57 [2.49, 8.41] 4.89 <0.00001 0.17491 0.8864

3 Total parenteral nutrition 4 410 117 215 94 195 4.07 0.25 26 Fixed 1.51 [0.99, 2.32] 1.9 0.06 −0.07466 0.96836

4 Exposure of vancomycin 3 330 43 161 28 169 12.19 0.002 84 Fixed 1.89 [1.11, 3.19] 2.36 0.02 4.85089 0.05157

5 Exposure of cephalosporins 6 1369 297 693 335 676 18.64 0.002 73 Random 1.61 [0.83, 3.12] 1.42 0.16 1.69815 0.51405

6 Exposure of third cephalosporins 7 1452 427 663 418 789 11.97 0.06 50 Random 1.69 [1.13, 2.51] 2.57 0.01 1.73419 0.41031

7 Exposure of fourth cephalosporins 3 429 123 246 62 183 3.08 0.21 35 Random 1.29 [0.64, 2.63] 0.71 0.48 3.4329 0.26673

8 Exposure of piperacillin tazobactam 5 868 291 561 122 307 21.96 0.0002 82 Fixed 1.51 [1.08, 2.10] 2.43 0.02 0.4783 0.88172

9 Exposure of aminoglycosides 3 584 74 430 16 154 0.27 0.87 0 Random 3.84 [2.03, 7.26] 4.14 0.0001 −0.37964 0.75673

10 Exposure of carbapenem 6 1139 373 664 92 475 22.62 0.0004 78 Fixed 5.51 [3.88, 7.80] 9.58 0.00001 1.9456 0.55997

11 Exposure of Fluoroquinolone 4 626 196 329 84 297 10.55 0.01 72 Random 3.22 [1.20, 8.67] 2.32 0.02 3.0701 0.07334

12 Previous use of antibiotics 5 8744 517 717 3664 8027 10.51 0.03 62 Fixed 1.51 [1.25, 1.84] 4.17 <0.0001 1.84778 0.06929

S. no	Risk factor	Studies	Total participants	Exposure of case to risk factor	Total case	Exposure of control to risk factor	Total control	Heterogeneity	Model	Effect estimate	Z value	P value	Egger’s test
1	Mechanical ventilation	12	2229	840	1209	486	1020	65.68	<0.00001	83	Random	3.66 [2.07, 6.48]	4.45	<0.00001	0.36751	0.86986
2	Urinary catheter	11	2031	822	1046	639	985	34.66	0.0001	71	Random	4.57 [2.49, 8.41]	4.89	<0.00001	0.17491	0.8864
3	Total parenteral nutrition	4	410	117	215	94	195	4.07	0.25	26	Fixed	1.51 [0.99, 2.32]	1.9	0.06	−0.07466	0.96836
4	Exposure of vancomycin	3	330	43	161	28	169	12.19	0.002	84	Fixed	1.89 [1.11, 3.19]	2.36	0.02	4.85089	0.05157
5	Exposure of cephalosporins	6	1369	297	693	335	676	18.64	0.002	73	Random	1.61 [0.83, 3.12]	1.42	0.16	1.69815	0.51405
6	Exposure of third cephalosporins	7	1452	427	663	418	789	11.97	0.06	50	Random	1.69 [1.13, 2.51]	2.57	0.01	1.73419	0.41031
7	Exposure of fourth cephalosporins	3	429	123	246	62	183	3.08	0.21	35	Random	1.29 [0.64, 2.63]	0.71	0.48	3.4329	0.26673
8	Exposure of piperacillin tazobactam	5	868	291	561	122	307	21.96	0.0002	82	Fixed	1.51 [1.08, 2.10]	2.43	0.02	0.4783	0.88172
9	Exposure of aminoglycosides	3	584	74	430	16	154	0.27	0.87	0	Random	3.84 [2.03, 7.26]	4.14	0.0001	−0.37964	0.75673
10	Exposure of carbapenem	6	1139	373	664	92	475	22.62	0.0004	78	Fixed	5.51 [3.88, 7.80]	9.58	0.00001	1.9456	0.55997
11	Exposure of Fluoroquinolone	4	626	196	329	84	297	10.55	0.01	72	Random	3.22 [1.20, 8.67]	2.32	0.02	3.0701	0.07334
12	Previous use of antibiotics	5	8744	517	717	3664	8027	10.51	0.03	62	Fixed	1.51 [1.25, 1.84]	4.17	<0.0001	1.84778	0.06929

Table 2 (Continued)

S. no	Risk factor	Studies	Total participants	Exposure of case to risk factor	Total case	Exposure of control to risk factor	Total control	Heterogeneity			Model	Effect estimate	Z value	P value	Egger’s test
								Chi square	P value	I square					Intercept	P-value (2 tailed)
13	Exposure of quinlones	3	588	104	437	18	151	0.89	0.64	0	Random	2.48 [1.40, 4.39]	3.12	0.002	2.34108	0.08367
14	Tracheostomy	6	862	345	576	72	286	16.06	0.007	69	Random	5.01 [2.12, 11.84]	3.68	0.0002	−0.5584	0.78733
15	Surgery	11	10013	434	1434	1254	8579	30.39	0.0007	67	Fixed	0.83 [0.70, 0.99]	2.07	0.04	−0.84725	0.39308
16	ICU stay	5	1243	455	682	276	561	34.93	<0.00001	89	Random	4.26 [1.66, 10.93]	3.01	0.003	5.8705	0.22332
17	Hospitalization	3	811	222	328	273	483	6.5	0.04	69	Fixed	1.66 [1.21, 2.29]	3.14	0.002	−2.80211	0.53668
18	Respiratory disease	12	1565	320	993	146	572	26.9	0.005	59	Fixed	1.69 [1.27, 2.25]	3.6	0.0003	1.09914	0.1898
19	Cardiovascular disease	7	863	172	471	107	392	3.81	0.7	0	Random	1.53 [1.10, 2.13]	2.51	0.01	−0.69565	0.45361
20	COPD	3	323	27	212	13	111	3.52	0.17	43	Random	1.22 [0.35, 4.20]	0.31	0.75	0.15796	0.96793
21	Diabetes Mellitus	10	968	133	538	352	430	11.98	0.1	42	Random	1.08 [0.61, 1.92]	0.28	0.78	0.20294	0.87082
22	Malignancy	4	463	59	228	30	235	0.54	0.91	0	Random	3.15 [1.86, 5.31]	4.29	<0.0001	−0.40712	0.50791
23	Cancer	3	650	142	262	158	388	1.88	0.39	0	Fixed	1.58 [1.12, 2.23]	2.63	0.008	−0.46457	0.73652
24	Use of immunosuppresive agents	6	956	130	630	59	326	0.76	0.98	0	Random	1.24 [0.86, 1.79]	1.14	0.25	0.14852	0.7756
25	Female gender	8	8945	281	782	3633	8163	10.2	0.18	31	Random	0.86 [0.65, 1.13]	1.08	0.28	0.39029	0.62597
26	Central venous catheter	11	2031	521	876	305	598	18.85	0.03	52	Random	2.28 [1.48, 3.49]	3.76	0.0002	1.45969	0.22188
27	Comorbidity, <2	2	653	276	317	279	336	2.91	0.09	66	Fixed	1.29 [0.83, 2.01]	1.12	0.26	NA	NA
28	Comorbidity, >2	2	564	71	246	71	318	2.26	0.13	56	Fixed	0.81 [0.50, 1.31]	0.86	0.39	NA	NA

Of the 28 risk factors, 19 statistically significant risk factors were - mechanical ventilation, exposure to carbapenem, tracheostomy, urinary catheter, ICU stay, exposure to aminoglycosides, exposure to fluoroquinolone, malignancy, exposure to quinolones, central venous catheter, exposure of vancomycin, respiratory disease, exposure of third generation cephalosporins, hospitalization, cancer, cardiovascular disease, previous use of antibiotics, exposure of piperacillin-tazobactam and surgery. The forest plots presenting the risk factors with pooled odd’s ratio are given in Supplementary Material S2.

3.4.2. Risk factors for Carbapenem-resistant A. baumannii (CRAB) infection relative to control patients

A total of 22 risk factors were identified for CRAB infection, that are represented in Table 3. Of these, the uppermost risk factors were previous use of amikacin [OR 4.94, 95% CI 1.89–12.9, p < 0.001], previous use of carbapenem [OR 4.91, 95% CI 2.65–9.1, p < 0.001] and pneumonia [OR 4.71, 95% CI 2.03–10.93, p < 0.001].

Table 3
Risk factors for Carbapenem-resistant A. baumannii infection relative to control patients

S. no Risk factor Studies Total participants Exposure of case to risk factor Total case Exposure of control to risk factor Total control Heterogeneity Model Effect estimate Z value P value Egger’s test

Chi square P value I square Intercept P-value (2 tailed)

1 Previous use of Amikacin 3 650 79 203 114 447 3.33 0.19 40 Random 4.94 [1.89, 12.90] 3.26 0.001 −4.52216 0.0467

2 Previous use of carbapenems 8 1680 360 737 196 943 41.42 <0.00001 83 Random 4.91 [2.65, 9.10] 5.06 <0.00001 0.92648 0.49936

3 Pneumonia 4 454 89 151 85 303 7.36 0.06 59 Random 4.71 [2.03, 10.93] 3.61 0.0003 2.32021 0.84188

4 Mechanical ventillation 7 1222 269 442 320 780 28.72 <0.0001 79 Random 3.46 [1.79, 6.69] 3.68 0.0002 0.562 0.74571

5 Previous use of piperacilline tazobactam 4 822 103 284 81 538 2.45 0.48 0 Random 2.92 [2.04, 4.19] 5.87 <0.00001 −3.6301 0.3847

6 Prior quinolone use 5 1306 186 614 109 692 76.06 <0.00001 95 Random 2.35 [0.56, 9.85] 1.17 0.24 −1.68944 0.07212

7 Catheter related infection 3 573 54 298 24 275 0.62 0.73 0 Random 2.09 [1.17, 3.71] 2.5 0.01 4.39196 0.09129

8 Central venous catheter 7 1447 305 583 335 864 28.87 <0.0001 79 Random 2.06 [1.10, 3.87] 2.25 0.02 0.52515 0.46318

9 Urinary catheter 8 1836 424 765 486 1071 26.07 0.0005 73 Random 1.84 [1.14, 2.99] 2.49 0.01 −1.4319 0.7066

10 Prior infection 3 376 80 129 111 247 8.76 0.01 77 Random 1.84 [0.39, 8.60] 0.78 0.44 2.17761 0.02421

11 Neurological disorder 5 1269 103 598 67 671 22.87 0.0001 83 Random 1.81 [0.67, 4.86] 1.17 0.24 0.1566 0.96773

12 ICU stay 5 3524 404 1680 388 1844 23.21 0.0001 83 Random 1.79 [1.09, 2.94] 2.28 0.02 0.50993 0.9522

13 Total parentral nutrition 3 490 37 172 42 318 3.17 0.2 37 Random 1.55 [0.76, 3.15] 1.22 0.22 2.54607 0.23602

14 Chronic kidney disease 4 900 48 328 65 572 1.47 0.69 0 Random 1.47 [0.98, 2.23] 1.85 0.06 −2.08798 0.03274

15 Neutropenia 4 673 24 332 22 341 0.42 0.94 0 Random 1.41 [0.62, 3.23] 0.81 0.42 −1.13081 0.57766

16 Diabetes 6 1366 142 629 159 737 12.19 0.03 59 Random 1.38 [0.86, 2.23] 1.34 0.18 5.03979 0.05224

17 Male 12 48417 2370 3872 20102 44545 67.59 <0.00001 84 Random 1.28 [0.97, 1.68] 1.75 0.08 1.73067 0.46593

18 Steroid use 5 3260 140 1607 142 1653 3.8 0.43 0 Random 1.24 [0.94, 1.64] 1.51 0.13 2.81886 0.14473

19 Invasive procedure 3 3032 407 1557 383 1475 3.75 0.15 47 Random 1.22 [0.89, 1.67] 1.22 0.22 −0.33375 0.90298

20 Cardiovascular disease 4 1120 117 526 114 594 13.09 0.004 77 Random 1.15 [0.60, 2.20] 0.42 0.68 1.64933 0.56592

21 Cancer 7 3604 504 1736 573 1868 23.65 0.0006 75 Random 1.09 [0.71, 1.67] 0.4 0.69 −3.60428 0.47507

22 Liver disease 5 1073 38 473 40 600 9.32 0.05 57 Random 0.94 [0.38, 2.34] 0.13 0.9 2.24497 0.5828

23 Previous use of betalactams/betalactamase inhibitor 3 814 75 415 85 399 1.35 0.51 0 Random 0.92 [0.63, 1.34] 0.44 0.66 1.65656 0.67431

24 Previous use of Aminoglycosides 3 875 82 446 107 429 4.67 0.1 57 Random 0.88 [0.50, 1.54] 0.45 0.65 2.5151 0.09376

25 Respiratory diseases 4 763 102 401 93 362 17.15 0.0007 83 Random 0.79 [0.27, 2.32] 0.42 0.67 2.32319 0.61378

S. no	Risk factor	Studies	Total participants	Exposure of case to risk factor	Total case	Exposure of control to risk factor	Total control	Heterogeneity	Model	Effect estimate	Z value	P value	Egger’s test
1	Previous use of Amikacin	3	650	79	203	114	447	3.33	0.19	40	Random	4.94 [1.89, 12.90]	3.26	0.001	−4.52216	0.0467
2	Previous use of carbapenems	8	1680	360	737	196	943	41.42	<0.00001	83	Random	4.91 [2.65, 9.10]	5.06	<0.00001	0.92648	0.49936
3	Pneumonia	4	454	89	151	85	303	7.36	0.06	59	Random	4.71 [2.03, 10.93]	3.61	0.0003	2.32021	0.84188
4	Mechanical ventillation	7	1222	269	442	320	780	28.72	<0.0001	79	Random	3.46 [1.79, 6.69]	3.68	0.0002	0.562	0.74571
5	Previous use of piperacilline tazobactam	4	822	103	284	81	538	2.45	0.48	0	Random	2.92 [2.04, 4.19]	5.87	<0.00001	−3.6301	0.3847
6	Prior quinolone use	5	1306	186	614	109	692	76.06	<0.00001	95	Random	2.35 [0.56, 9.85]	1.17	0.24	−1.68944	0.07212
7	Catheter related infection	3	573	54	298	24	275	0.62	0.73	0	Random	2.09 [1.17, 3.71]	2.5	0.01	4.39196	0.09129
8	Central venous catheter	7	1447	305	583	335	864	28.87	<0.0001	79	Random	2.06 [1.10, 3.87]	2.25	0.02	0.52515	0.46318
9	Urinary catheter	8	1836	424	765	486	1071	26.07	0.0005	73	Random	1.84 [1.14, 2.99]	2.49	0.01	−1.4319	0.7066
10	Prior infection	3	376	80	129	111	247	8.76	0.01	77	Random	1.84 [0.39, 8.60]	0.78	0.44	2.17761	0.02421
11	Neurological disorder	5	1269	103	598	67	671	22.87	0.0001	83	Random	1.81 [0.67, 4.86]	1.17	0.24	0.1566	0.96773
12	ICU stay	5	3524	404	1680	388	1844	23.21	0.0001	83	Random	1.79 [1.09, 2.94]	2.28	0.02	0.50993	0.9522
13	Total parentral nutrition	3	490	37	172	42	318	3.17	0.2	37	Random	1.55 [0.76, 3.15]	1.22	0.22	2.54607	0.23602
14	Chronic kidney disease	4	900	48	328	65	572	1.47	0.69	0	Random	1.47 [0.98, 2.23]	1.85	0.06	−2.08798	0.03274
15	Neutropenia	4	673	24	332	22	341	0.42	0.94	0	Random	1.41 [0.62, 3.23]	0.81	0.42	−1.13081	0.57766
16	Diabetes	6	1366	142	629	159	737	12.19	0.03	59	Random	1.38 [0.86, 2.23]	1.34	0.18	5.03979	0.05224
17	Male	12	48417	2370	3872	20102	44545	67.59	<0.00001	84	Random	1.28 [0.97, 1.68]	1.75	0.08	1.73067	0.46593
18	Steroid use	5	3260	140	1607	142	1653	3.8	0.43	0	Random	1.24 [0.94, 1.64]	1.51	0.13	2.81886	0.14473
19	Invasive procedure	3	3032	407	1557	383	1475	3.75	0.15	47	Random	1.22 [0.89, 1.67]	1.22	0.22	−0.33375	0.90298
20	Cardiovascular disease	4	1120	117	526	114	594	13.09	0.004	77	Random	1.15 [0.60, 2.20]	0.42	0.68	1.64933	0.56592
21	Cancer	7	3604	504	1736	573	1868	23.65	0.0006	75	Random	1.09 [0.71, 1.67]	0.4	0.69	−3.60428	0.47507
22	Liver disease	5	1073	38	473	40	600	9.32	0.05	57	Random	0.94 [0.38, 2.34]	0.13	0.9	2.24497	0.5828
23	Previous use of betalactams/betalactamase inhibitor	3	814	75	415	85	399	1.35	0.51	0	Random	0.92 [0.63, 1.34]	0.44	0.66	1.65656	0.67431
24	Previous use of Aminoglycosides	3	875	82	446	107	429	4.67	0.1	57	Random	0.88 [0.50, 1.54]	0.45	0.65	2.5151	0.09376
25	Respiratory diseases	4	763	102	401	93	362	17.15	0.0007	83	Random	0.79 [0.27, 2.32]	0.42	0.67	2.32319	0.61378

Of the 22 risk factors, 9 statistically significant were- previous use of amikacin, previous use of carbapenems, pneumonia, mechanical ventilation, previous use of piperacillin-tazobactam, catheter-related infection, central venous catheter, urinary catheter, and ICU stay. Supplementary Material S3 contains forest plots depicting risk factors with pooled odd’s ratio.

3.4.3. Risk factors for Imipenem-resistant A. baumannii (IRAB) infection relative to control patients

A total of 11 risk factors in which only male as a risk factor is statistically insignificant (Table 4). The statistically significant risk factors were exposure to aminoglycosides, arterial catheter, ICU stay, exposure to carbapenems, surgery, central venous catheter, mechanical ventilation, parenteral nutrition, nasogastric tube, and malignancy.

Table 4
Risk factors for Imipenem resistant A. baumannii infection relative to control patients

S. no Risk factor Studies Total participants Exposure of case to risk factor Total case Exposure of control to risk factor Total control Heterogeneity Model Effect estimate Z value P value Egger’s test

Chi square P value I square Intercept P-value (2 tailed)

1 Exposure of aminoglycosides 4 723 170 218 117 505 5.42 0.07 63 FIXED 1.55 [1.03–2.31] 2.13 0.03 −4.56258 0.08276

2 Arterial catheter 5 513 87 151 140 362 3.43 0.49 0 FIXED 2.39 [1.53–3.73] 3.83 0.0001 0.12966 0.91889

3 ICU stay 3 1184 473 627 326 557 12.03 0.002 83 RANDOM 3.51 [1.18–10.49] 2.25 0.02 1.90167 0.11564

4 Exposure of carbapenems 4 791 41 203 76 588 1.57 0.67 0 FIXED 2.94 [1.76–4.92] 4.11 <0.0001 1.20405 0.40044

5 Surgery 3 405 68 114 91 291 1.05 0.59 0 FIXED 2.90 [1.79–4.69] 4.34 <0.0001 1.23152 0.37019

6 Central venous catheter 5 1382 531 660 428 722 9.9 0.04 60 FIXED 2.19 [1.69–2.83] 5.99 <0.00001 0.97471 0.29878

7 Mechanical ventilation 4 1214 476 638 343 576 1.72 0.42 0 FIXED 2.01 [1.56–2.57] 5.48 <0.00001 1.30653 0.05407

8 Parentral nutrition 4 483 46 140 82 343 0.77 0.86 0 FIXED 1.83 [1.14–2.92] 2.53 0.01 0.23673 0.72077

9 Nasogastric tube 5 408 374 664 326 744 5.05 0.28 21 FIXED 1.70 [1.35–2.15] 4.55 <0.00001 3.31544 0.03176

10 Malignancy 3 1212 109 599 60 613 0.84 0.66 0 FIXED 1.63 [1.15–2.30] 2.78 0.005 0.45673 0.63876

11 Male 6 553 107 171 229 382 1.03 0.96 0 FIXED 0.88 [0.58–1.32] 0.63 0.53 −1.21175 0.46745

S. no	Risk factor	Studies	Total participants	Exposure of case to risk factor	Total case	Exposure of control to risk factor	Total control	Heterogeneity	Model	Effect estimate	Z value	P value	Egger’s test
1	Exposure of aminoglycosides	4	723	170	218	117	505	5.42	0.07	63	FIXED	1.55 [1.03–2.31]	2.13	0.03	−4.56258	0.08276
2	Arterial catheter	5	513	87	151	140	362	3.43	0.49	0	FIXED	2.39 [1.53–3.73]	3.83	0.0001	0.12966	0.91889
3	ICU stay	3	1184	473	627	326	557	12.03	0.002	83	RANDOM	3.51 [1.18–10.49]	2.25	0.02	1.90167	0.11564
4	Exposure of carbapenems	4	791	41	203	76	588	1.57	0.67	0	FIXED	2.94 [1.76–4.92]	4.11	<0.0001	1.20405	0.40044
5	Surgery	3	405	68	114	91	291	1.05	0.59	0	FIXED	2.90 [1.79–4.69]	4.34	<0.0001	1.23152	0.37019
6	Central venous catheter	5	1382	531	660	428	722	9.9	0.04	60	FIXED	2.19 [1.69–2.83]	5.99	<0.00001	0.97471	0.29878
7	Mechanical ventilation	4	1214	476	638	343	576	1.72	0.42	0	FIXED	2.01 [1.56–2.57]	5.48	<0.00001	1.30653	0.05407
8	Parentral nutrition	4	483	46	140	82	343	0.77	0.86	0	FIXED	1.83 [1.14–2.92]	2.53	0.01	0.23673	0.72077
9	Nasogastric tube	5	408	374	664	326	744	5.05	0.28	21	FIXED	1.70 [1.35–2.15]	4.55	<0.00001	3.31544	0.03176
10	Malignancy	3	1212	109	599	60	613	0.84	0.66	0	FIXED	1.63 [1.15–2.30]	2.78	0.005	0.45673	0.63876
11	Male	6	553	107	171	229	382	1.03	0.96	0	FIXED	0.88 [0.58–1.32]	0.63	0.53	−1.21175	0.46745

Table 5

Risk factors for XDR A. baumannii infection relative to control patients

S. no	Risk factor	Studies	Total participants	Exposure of case to risk factor	Total case	Exposure of control to risk factor	Total control	Heterogeneity			Model	Effect estimate	Z value	P value	Egger’s test
								Chi square	P value	I square					Intercept	P-value (2 tailed)
1	Mechanical ventilation	3	481	82	99	176	382	1.43	0.49	0	FIXED	7.21 [3.79–13.71]	6.03	<0.00001	1.85462	0.04723
2	ICU stay	3	481	12	80	29	200	0.85	0.65	0	FIXED	5.88 [3.27–10.57]	0.65	0.52	NA	NA
3	Bedridden	2	250	23	64	20	186	1.25	0.26	20	FIXED	4.18 [2.09–8.38]	4.03	<0.0001	2.76359	0.48164
4	Central venous catheter	3	481	65	99	134	382	7.11	0.03	72	FIXED	3.16 [1.89–5.26]	4.4	<0.0001	−1.0623	0.7745
5	Urinary catheter	3	481	65	85	302	396	1.84	0.4	0	FIXED	2.25 [1.11–4.58]	2.24	0.02
6	Surgery	3	576	29	108	63	468	1.15	0.56	0	FIXED	2.03 [1.19–3.47]	2.59	0.01	0.98464	0.87478
7	Liver disorders	2	155	4	41	5	114	0.01	0.94	0	FIXED	2.00 [.47–8.55]	0.93	0.35	−3.22702	0.60205
8	End stage renal disease	2	155	13	55	16	100	0	1	0	FIXED	1.86 [0.80–4.31]	1.44	0.15	NA	NA
9	Hemodialysis	3	481	13	85	48	396	4.03	0.13	50	FIXED	1.24 [0.62–2.47]	0.61	0.54	1.50678	0.55045
10	Diabetes	3	280	28	80	69	200	1.71	0.42	0	RANDOM	0.99 [0.57–1.74]	0.03	0.98	−0.32217	0.81392
11	Male	3	481	54	99	204	382	2.26	0.32	12	FIXED	0.93 [0.58–1.48]	0.3	0.76	1.6793	0.21761
12	Malignancy	3	280	65	85	302	396	1.84	0.4	0	FIXED	0.78 [0.36–1.66]	2.24	0.02	NA	NA
13	Cerebral vascular disease	2	250	31	64	93	186	1.53	0.22	35	RANDOM	0.62 [0.31–1.22]	1.05	0.29	0.12224	0.97317
14	Chemotherapy	2	155	76	99	163	382	2.65	0.27	25	FIXED	0.45 [0.12–1.69]	5.92	<0.00001	NA	NA

ICU stay [OR 3.51, 95% CI 1.18–10.49, p = 0.02], carbapenem exposure [OR 2.94, 95% CI 1.76–4.92, p < 0.001] and surgery [OR 2.9, 95% CI 1.79–4.69, p < 0.001] were the foremost factors associated with developing IRAB infection. The forest plots of risk factors with quantitative pooled odd’s ratio are included in Supplementary Material S4.

3.4.4. Risk factors for Extensive drug resistant A. baumannii (XDRAB) infection relative to control patients

Mechanical ventilation [OR 7.21, 95% CI 3.79–13.71, p < 0.001], ICU stay [OR 5.88, 95% CI 3.27–10.57, p = 0.52] and bedridden [OR 4.18, 95% CI 2.09–8.38, p < 0.001] were the highest-ranking significant risk factors for XDRAB infection (Table 5).

Seven risk factors were statistically significant from a total of 14 risk factors: Mechanical ventilation, bedridden, central venous catheter, urinary catheter, surgery, malignancy, and chemotherapy. The forest plots of all 14 risk factors for XDRAB infection are presented in Supplementary Material S5.

4. Discussion

Acinetobacter baumannii is a common cause of nosocomial infection and is being investigated as one of the leading causes of the antibiotic resistance crisis [65]. According to the World Health Organization (WHO), A. baumannii is one of the most threatening of the ESKAPE organisms (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) that are resistant to antibacterial treatments. When compared to other non-baumannii species, the resistant species is linked to a higher mortality rate among infected patients [66,67]. A. baumannii can cause a wide range of infections, the majority of which affect the respiratory tract, particularly ventilator-associated pneumonia, bacteremia, and skin wound infections [68]. The Centers for Disease Control and Prevention (CDC) also reported that the majority of clinically relevant A. baumannii strains are multidrug-resistant, accounting for up to 20% of infections in intensive care units (ICUs) and 7% of infections in patients who are physically attached to medical equipment (5). Resistant A. baumannii infections are highly prevalent in the nations, where the studies included in this review were performed. China, the United States, Turkey, Brazil, Greece, Spain, France, Thailand, Egypt, Germany, and Israel are among these countries [69]. Even though there has been research that has investigated risk factors for resistant A. baumannii infection and has come to bifurcated and conflicting conclusions. For example, a total of 83 percent of controls and 95 percent of patients exposed to the cephalosporins acquired MDRAB infection, according to Huang et al. [51] while Zhou et al. reported that patients with MDRAB infection had a higher exposure ratio of cephalosporins (21 percent controls vs. 14 percent of cases) [55]. In yet another example, Dent et al. [43] reported that 78.5% of controls and 90.9% of patients exposed to the antibiotics developed MDRAB infection. In contrast, in a similar study [51], a higher exposure ratio was observed among patients with MDRAB infection (86.6% controls vs. 89.2% of cases).

Some of the included studies [53,57,62] have published risk profiles in large sample sizes, while other studies [14,35,58] have concluded results based on small size. Therefore, this discrepancy in results could be attributed to sample size differences and a general lack of statistical power.

Furthermore, some researchers are attempting to determine the risk factor for mixed infections, which commonly include resistant A. baumannii and Pseudomonas aeruginosa or combinations of ESKAPE organisms.

In this review, total of 38 studies in eleven countries involving several thousands of patients were meta-analysed by the reviewer. Data from all studies in which risk factors for the acquisition of antibiotic resistance in A. baumannii infections were extracted. The majority of the studies were evaluating the risk factor for acquisition of MDR followed by Carbapenem/imipenem resistance, and XDRAB infection. The control group in the majority of studies was susceptible to A. baumannii infection, while a fewer number of studies included patients with no infection as a control group. Consistent with the initial idea, the risk factor profiles differed between different antibiotic-resistant species. In the case of risk factors for developing multidrug-resistant A. baumannii infection, despite considerable heterogeneity in the definition of controls, this review accepted the definition given by the individual study.

The MDRAB has been a common cause of hospital outbreaks owing to its capacity to rapidly alter its genome and its ability to persist on inanimate surfaces and medical equipment with high disinfection resistance [70]. This review identified the following risk factors for developing multidrug resistance with pooled odd’s ratio greater than one: mechanical ventilation, exposure to carbapenem, tracheostomy, urinary catheter, ICU stays, exposure to aminoglycosides, exposure to fluoroquinolone, malignancy, exposure of quinolones, central venous catheter, exposure of vancomycin, respiratory disease, exposure of third-generation cephalosporins, hospitalization, exposure of cephalosporins, cancer, cardiovascular disease, previous use of antibiotics, exposure of piperacillin-tazobactam, total parenteral nutrition, the existence of comorbidity less than 2, exposure of fourth-generation cephalosporins, use of immunosuppressive agents, chronic obstructive pulmonary disease and diabetes mellitus. Whereas other risk factors like female gender, surgery, and comorbidity >2 were having odds ratio less than one. The increased likelihood of infection with MDRAB is provoked by these risk factors, which are mainly present in patients who have severe illness and greater susceptibility to infection, which leads to exposure to greater antibiotic selection pressure.

CRAB infection is associated with high healthcare costs, and significant mortality, causing worldwide concern, yet there are limited studies on examining the risk factors for its acquisition [71].

This review explored the following risk factors: previous use of Amikacin, previous use of carbapenems, pneumonia, mechanical ventilation, previous use of piperacillin-tazobactam, catheter-related infection, central venous catheter, urinary catheter, and ICU stay. Whereas risk factors like liver disease, previous use of beta-lactams/beta-lactamase inhibitors, previous use of aminoglycosides, and respiratory diseases as underlying health conditions were statistically insignificant protective factors. All these points indicate that antimicrobial stewardship for hospitalized patients should be reinforced.

Two systematic reviews, published in 2006 [72] and 2018 [73], have examined the risk profiles for carbapenem and extreme drug resistance in A. baumannii-infected patients. However, Lim et al. [73] only investigated antibiotic use as a risk factor, while Falagas et al. [72] only published a systematic review (no meta-analysis) of possible risk variables. There are no systematic reviews and meta-analyses published specifically for the risk factors for the acquisition of imipenem resistant as well as extended drug-resistant A. baumannii infection. In this study, a total of eleven risk factors met the eligibility criteria for IRAB. Among these risk factors, only the male gender was not statistically significant and its pooled odds ratio was less than one. The statistically significant risk factors found were exposure to aminoglycosides, arterial catheter, ICU stay, exposure to carbapenems, surgery, central venous catheter, mechanical ventilation, parenteral nutrition, nasogastric tube, and malignancy. The risk factors such as ICU stay and arterial catheter shows a high risk for the development of acquisition of IRAB infection. For XDRAB, among 14 eligible risk factors, seven were statistically significant which includes use of mechanical ventilation, bedridden, central venous catheter, urinary catheter, surgery, malignancy, and chemotherapy. On the other hand, pooled odds ratio of risk factors- ICU stays, liver disorder, end-stage renal disease, haemodialysis, diabetes, male gender and cerebral vascular diseases represented insignificant results.

The installation of mechanical ventilation and central venous catheter were the two risk factors that were common in all four examined groups since the majority of hospitalized ill patients have undergone the insertion of these two medical devices. Furthermore, use of central venous catheter, urinary catheter, ICU stay, surgery, diabetes mellitus, male gender, malignancy, carbapenem exposure, and aminoglycoside exposure were customary risk factors in at least one of the three groups evaluated. Additionally, it also indicates that medical device sterilization and decontamination will play an important role in preventing the acquisition of resistant infection.

4.1. Strengths and limitations

This review does not contain any studies of high risk of bias. The sensitivity analysis confirmed that the meta-analysed results were robust. The findings of the meta-analysis were interpreted with caution given that some potential risk factors were evaluated based on data from a small number of studies. Data for some risk factors showed significant heterogeneity across the studies.

This study contains the articles obtained from only two databases and articles other than English languages were excluded. All analysed data were dichotomous variables. The risk factors in univariate analysis were only included because risk factors in multivariate analysis were less and thereby cannot be pooled. The majority of the studies included were retrospective and all were observational which can increase the risk of selection bias, outcome reporting bias, and confounding. Nonetheless, all studies acquired NOS scores indicating high quality of studies and no obvious publication bias was observed for any of the factors. Risk factor profiling of antibiotic resistance should be further analyzed in large, well-controlled observational studies.

5. Conclusion

The exposure of carbapenem, amikacin (previous), and mechanical ventilation were the most significant risk factors for multidrug, extensive-drug, and carbapenem resistance in patients with A. baumannii infection respectively. These findings may assist to control and prevent resistant infections by identifying the patients at higher risk of developing resistance.

Footnotes

Acknowledgements

The authors thank the National Institute of Pharmaceutical Education and Research (NIPER), S.A.S. Nagar for making available the library, computer laboratory facility and online access of articles and other resources.

Conflict of interest

There are no conflicts of interest.

Supplementary materials

The supplementary files are available from .

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