Factors associated with multidrug-resistant organism (MDRO) mortality: An analysis from the National Surveillance of Multidrug-Resistant Organism, 2018-2022

doi:10.21203/rs.3.rs-5028553/v1

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Research Article

Factors associated with multidrug-resistant organism (MDRO) mortality: An analysis from the National Surveillance of Multidrug-Resistant Organism, 2018-2022

https://doi.org/10.21203/rs.3.rs-5028553/v1

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Introduction:

Antimicrobial resistance is a global issue, with the World Health Organization identifying it as one of the greatest threats to public health, with an estimated 4.95 million deaths linked to bacterial AMR in 2019. Our study aimed to determine the prevalence of mortality among MDRO-infected patients in state hospitals and major specialist hospitals and to identify risk factors that could be associated with mortality outcomes.

Methods

This is a cross-sectional study performed at 28 hospitals under the Ministry of Health, Malaysia, involved in the National Surveillance of Multidrug-Resistant Organism, which surveys 6 MDROs.

Result

In terms of mortality, 9.6% (n = 951) of the patients died overall, whereas 90.4% (n = 8931) of the patients survived. Healthcare acquired infection (HCAI) poses a high risk of mortality (adjusted OR: 2.91, 95% CI: 2.15–3.94). The presence of sterile specimens was significantly associated with increased mortality risk (adjusted OR: 2.33, 95% CI: 2.02–2.68). Gram-negative bacteria had a greater mortality risk (adjusted OR 1.63 95% CI: 1.37–1.93), whereas Acinetobacter baumanii had the highest prevalence of 30.7% (3033) among the 6 MDRO organisms isolated. Patients in medical-based departments had a greater mortality risk (aOR: 1.47, 95% CI: 1.22–1.75).

Conclusion

HCAIs, gram-negative bacteria, sterile specimens, medical-based departments and state hospitals have been shown to be associated with increased mortality risk in patients with MDRO infections. Improved surveillance and reporting mechanisms are necessary to better understand the burden of MDRO infections and guide research funding allocation.

healthcare-acquired infections

antimicrobial resistance

bacteraemia

hospital mortality

Antimicrobial resistance is a global issue, with the World Health Organization identifying it as one of the greatest threats to public health (1). An estimated 4.95 million deaths were linked to bacterial AMR in 2019, of which 1.27 million were directly related to the disease (2, 3). In 2019, more than 1.5 million deaths were caused by resistance-related lower respiratory infections, making it the most burdensome infectious condition (2). The improper use of antibiotics results in the development and preferential survival of microorganisms that are resistant to these drugs (4). Studies have revealed that a tremendous clinical and economic burden is caused by multidrug-resistant organism (MDRO) bacteraemia compared with antibiotic-susceptible and noninfected groups, suggesting that substantial investment and efforts by related government agencies and medical staff are needed (5, 6).

According to the Key Health Indicator Report 2023 by the Ministry of Health, Malaysia, the death rate of bacterial agents resistant to antibiotics (MDROs) in Malaysia is 0.03 per 100 000 people (7). A report published by the Institute for Health Metrics and Evaluation (IHME) in 2019 reported that Malaysia had 3,500 deaths caused by antimicrobial resistance (AMR) and an additional 14,000 deaths associated with AMR. The number of AMR deaths in Malaysia is greater than the number of deaths from digestive diseases, diabetes and kidney diseases, transport injuries, chronic respiratory diseases, and neurological disorders (8).

MDRO infections have been shown to increase the risk of hospital mortality by 1.5-4.0 times and can lead to longer stays in the hospital, higher costs, and increased morbidity (9, 10). Bloodstream infections (BSIs) caused by multidrug-resistant organisms (MDROs) are associated with high morbidity and mortality (9, 11). Healthcare-associated infections (HCAIs) are a serious threat to healthcare safety (12). Patients with healthcare-associated infections are more likely to develop BSIs caused by MDROs and have higher mortality rates (9, 13). Other factors that increase the risk of MDRO acquisition include long-term institutionalization, older age, functional dependency, the presence of invasive devices, recent procedures, and recent antibiotic use (14, 15). Preventing infections is crucial for reducing the burden of MDROs in healthcare settings (16).

Many studies have focused on a single tertiary hospital with a smaller sample size and therefore may not be fully representative of other hospitals (17, 18). Other studies focused only on single MDROs, such as Acinetobacter baumannii (19, 20). To our knowledge, this is the first study that analysed 6 MDROs that were monitored under National MDRO surveillance in which all 28 hospitals were involved. Thus, this study aimed to determine the prevalence of commonly isolated MDROs in state hospitals and major specialist hospitals and to determine the risk factors that could be associated with mortality outcomes among MDRO-infected patients.

2.1 Study design and settings

This cross-sectional study was performed at 28 hospitals under the Results and Analysis Ministry of Health, Malaysia, which are involved in the National Surveillance of Multidrug Resistant Organism. The hospitals involved in the surveillance were from 14 state hospitals and 14 major hospitals. Data were collected from 2018 to 2022.

2.2 Study sample and data collection

The data were collected from the National Surveillance of Multidrug Resistant Organism by the Infection Control Unit, Ministry of Health, Malaysia. This surveillance includes all inpatients in the hospital except for cases from emergency or outpatient services, cases previously identified at other healthcare facilities, patients who were admitted with the same MDRO within a year, and cases from a screening culture. The infection control nurse (ICN)/infection control personnel (ICP) collected data on MDROs and MRSA strains isolated from blood cultures daily from the laboratory. The MDROs that were monitored included Acinetobacter baumanii, extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli, extended-spectrum beta-lactamase (ESBL)-producing Klebsiella pneumoniae, carbapenem-resistant Entrobacterales (CRE), methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE).

The sample size was calculated via the single proportion formula in OpenEpi software version 3.0, which is based on a previous study reporting an MDRO mortality rate of 37.3% (17). The minimum required sample size was determined to be 360, with a precision of 5% and a 95% confidence interval. The selection of the study population is described in Fig. 1.

2.3 Definition of Variables, Inclusion Criteria, and Exclusion Criteria

The definitions of MDRO cases must fulfil all three criteria: isolation of the MDRO from any site of the body (including the colonizer), the case must be an inpatient, and the case must be “Newly identified.” “Newly identified” includes MDROs identified for the first time during current hospital admission and cases identified at the hospital site but acquired ‘new infection’ with different MDROs (21). For the exclusion criteria, incomplete or missing data were not included in this study to assist in further analysis.

The variables included in this study were year, department, previous encounter to healthcare facility, history of surgical intervention within 1 month, history of surgical implant within 1 year, type of specimen, isolated organism, isolation status, type of infection, healthcare acquired infection (HCAI) status, antibiotics (1) and (2), hospitals, and category. The outcome of the study was mortality, which was further defined as “living” or “dead”. The definitions of the variables are as per Table 1.

Table 1

Operational definitions of the variables
Variable	Operative Definition
Year	This variable is further divided into pre covid era (2018–2019) and post covid era (2020–2022)
Department	This variable was categorized into (21) i. Surgical-based department (Orthopaedic, O&G, Surgical, Urology) ii.Medical-based Department (Anaesthesia, Medical, Nephrology, Oncology, Paediatric) iii. Others
Previous Encounter to Healthcare Facilty	This variable is categorized as “Yes” or “No” (21)
History of Surgical Intervention Within 1 Month	This variable is categorized as “Yes” or “No” (21)
History Of Surgical Implant Within 1 Year	This variable is categorized as “Yes” or “No” (21)
Type Of Specimen	This variable is categorized into (21) i. Sterile site (blood, Cerebrospinal fluid (CSF), pleural fluid, peritoneal fluid) ii. Nonsterile site (Bronchoalveolar Lavage (BAL), Rectal, Sputum, Tissue, Tracheal Aspirate, Urine) iii. Others
Isolated Organism	This variable is categorized as (22) i. Gram Negative Bacteria • Acinetobacter baumanii • Extended spectrum beta lactamases (ESBL) producing Escherichia coli, • Extended spectrum beta lactamases (ESBL) producing Klebsiella pneumoniae, • Carbapenem resistant Entrobacterales (CRE) ii. Gram Positive Bacteria • Methicillin resistant Staphylococcus aureus (MRSA) • Vancomycin resistant Enterococcus (VRE) iii. Others
Type Of Infection	This variable is divided into (21) i. Bloodstream Infection (BSI) and ii. “Non-Bloodstream Infection” such as • Hospital Acquired Pneumonia (HAP) (non-VAP) • Intra-Abdominal • Surgical Site Infection (SSI) • Skin and Soft Tissue Infection (SSTI) • Urinary Tract Infection (UTI) • Others
Healthcare Acquired Infection (HCAI) Status	This variable is divided into (21) i. Healthcare Acquired Infection (HCAI) and • Hospital Acquired (HA)-MDRO, other MOH Facility • HA-MDRO, Own Facility • Healthcare Acquired Infection (HCAI), non MOH Facility • HCAI, other MOH Facility • HCAI, Own Facility ii. Non-Healthcare Acquired Infection (HCAI) • Community-Associated MRSA • Not Healthcare Associated MDRO
Antibiotic 1	This variable is divided into (23) i. beta lactam antibiotic • beta lactamase • Aminoglycosides • Carbapenems • Cephalosporin • penicillin ii. non beta lactam antibiotic • Colistin • Fluoroquinolones • Glycopeptides • Others
Antibiotic 2	This variable is divided into beta lactam or non-beta lactam(23) This variable is divided into i. beta lactam antibiotic • beta lactamase • Aminoglycosides • Carbapenems • Cephalosporin • Penicillin ii. non beta lactam antibiotic • Colistin • Fluoroquinolones • Glycopeptides • Others
Mortality Outcome	This variable was categorized as outcome of patient either “Dead” or “Alive” (21)
Hospitals Category	This variable is categorized as “State Hospital” or “Major Hospital” (21)

2.4. Statistical analysis

All the data were retrieved via an Excel sheet. SPSS® version 26.0 (IBM, New York, USA) for Windows® was used for the data analysis, descriptive analysis (percentages and frequencies), and categorical analysis. The level of significance was set at p < 0.05. The chi-square test was used to compare all variables that were categorical data mortality-related MDROs. Simple logistic regression and multivariate regression were used to analyse the risk factors for mortality via backwards and forward methods on the basis of goodness-of-fit principles. The Hosmer–Lemeshow test was used to assess the model.

2.5. Ethical Approval and Consent to Participate

This manuscript was written for the purpose of the Module Student Research Project of the Master Public Health Program. Ethical approval for this study will be obtained later from the Research Ethics Committee (REC), Medical Research and Ethics Committee (MREC) and Ministry of Health (MOH) via the National Medical Research Register (NMRR). The confidentiality of the patients’ data was ensured, and no intervention was taken for patient management. Only the researcher had access to the online patient records/data anonymously on the basis of the inclusion and exclusion criteria; no patients were involved during this study, and unnecessary informed consent was obtained from patients according to MREC and MOH approval. All the methods were carried out in accordance with the relevant guidelines and regulations/declaration of Helsinki.

A total of 9882 cases with MDROs from 2018–2022 were included in this study according to the eligibility criteria. The mortality outcome among MDRO-infected patients was 9.6% (n = 951), whereas 90.4% (n = 8931) of patients survived. The most common isolated organisms in state and major specialist hospitals were Acinetobacter baumanii (30.7%; n = 3033). The distributions of MDROs by type in the state and major hospitals are shown in Table 2. The majority of MDRO cases occurred in 2021 (47.9%, n = 4732), followed by 2022 (36.2%, n = 3577). The most common departments involved were medical departments (34.5%, n = 3411), followed by anaesthesia departments (28.2%, 2789) and surgical departments (10.3%, n = 1018). A total of 65.7% (n = 6489) of patients had no previous encounter with a healthcare facility, and 85.2% (n = 8423) of patients had no history of surgical intervention within the past month before admission. Blood samples were the most common type of sample (40.8%, 4029), followed by tracheal samples (27.5%, n = 2719). There were 2 types of isolation statuses: infection or colonizer. However, in this study, all the isolates were infections. The most commonly used antibiotics are beta-lactamases, carbapenems and cephalosporins. The characteristics of the MDRO cases are shown in Table 3.

Table 2

Distributions of MDROs by state and major specialist hospital type
Variable	State Hospital (n,%)	Major Specialist Hospital (n,%)
Isolated Organism
• Acinetobacter baumanii	1714 (26.7)	1319 (38)
• ESBL - Klebsiella pneumoniae	1347 (21.0)	599 (17.3)
• MRSA	1072 (16.7)	454 (13.1)
• ESBL - E. Coli	843 (13.1)	289 (8.3)
• CRE	802 (12.5)	450 (13.0)
• VRE	40 (0.6)	80 (0.2)
• Others	597 (9.3)	348 (10.0)

Table 3

Descriptive analysis of MDRO case characteristics
Variables	MDRO-infected patients
Variables	n	%
Isolated Organism
• Acinetobacter baumanii • ESBL - Klebsiella pneumoniae • MRSA	3033 1946 1526	30.7 19.7 15.4
• CRE	1252	12.7
• ESBL - E. Coli	1132	11.5
• Others	945	9.6
• VRE	48	0.5
Mortality outcome
• Alive	8931	90.4
• Dead	951	9.6
Year
• 2018	632	6.4
• 2019	931	9.4
• 2020	10	0.1
• 2021	4732	47.9
• 2022	3577	36.2
Department
• Medical • Anaesthesia • Surgical	3411 2789 1018	34.5 28.2 10.3
• Orthopaedic • Others • Paediatric • Urology	771 688 679 108	7.8 7.0 6.9 1.1
• Nephrology	201	2.0
• Obstetrics and Gynaecology (O&G)	158	1.6
• Oncology	59	0.6
Previous encounter to healthcare facility
• No	6489	65.7
• Yes	3393	34.3
History of Surgical Intervention within 1 month
• No	8423	85.2
• Yes	1459	14.8
History of Surgical Implant Within 1 Year
• No	9612	97.3
• Yes	270	2.7
Type Of Specimen
• Blood	4029	40.8
• Tracheal aspirate	2719	27.5
• Urine	783	7.9
• Tissue	654	6.6
• Sputum	398	4.0
• Wound	323	3.3
• Bronchoalveolar Lavage (BAL)	112	1.1
• CSF	48	0.5
• Peritoneal Dialysis (PD) fluid	49	0.5
• Rectal swab	36	0.4
• Others	731	7.4
Isolate Status
• Infection • Colonizers	9882 0	100 0
Type of Infection
• Bloodstream Infection (BSI)	3960	40.1
• Hospital-Acquired Pneumonia (HAP) non-Ventilator Acquired Pneumonia (VAP)	3199	32.4
• Others	883	8.9
• UTI (Urinary Tract Infection) • SSTI (Skin and Soft Tissue Infection)	782 519	7.9 5.3
• Surgical Site Infection (SSI)	432	4.4
• Intraabdominal	107	1.1
Healthcare Associated Infection (HCAI) status
• HCAI, own facility • Not Healthcare Associated MDRO	7800 1223	78.9 12.4
• Hospital Acquired Multidrug Resistant Organism (HA-MDRO), Own Facility	530	5.4
• HCAI, other MOH Facility	160	1.6
• Community MDRO • HCAI, non MOH Facility	93 70	0.9 0.7
• HA-MDRO, other MOH Facility	6	0.1
Antibiotic 1
• B-lactamase	2475	25.0
• Carbapenems	2057	20.8
• penicillin	989	10.0
• Glycopeptides	552	5.6
• Colistin	444	4.5
• Others • Aminoglycosides • Fluoroquinolones	285 115 49	2.9 1.2 0.5
Antibiotic 2
• Carbapenems • Cephalosporins • B-lactamase	2441 2147 2035	24.7 21.7 20.6
• Others	876	8.9
• penicillin	844	8.5
• Glycopeptides	754	7.6
• Colistin	491	5.0
• Aminoglycosides	226	2.3
• Fluoroquinolones	68	0.7
Zone
• Northern • Central • Southern • Eastern	582 404 404 354	33.0 22.9 22.9 20.1
• East Malaysia	19	1.1
Hospital category
• State Hospital	6415	64.9
• Major Specialist Hospital	3467	35.1

Table 4 presents the results of the chi-square analysis used to identify associations between the independent variables and mortality outcomes among MDRO patients. Chi-square analysis revealed significant associations between Year, Department, Previous Encounter to Healthcare Facility, History of Surgical Intervention, History of Surgical Implant within 1 year, Type of Specimen, Isolated Organism, Type of infection, HCAI status, Antibiotic, and Hospital Category with Mortality outcomes among MDRO patients.

Table 4

Bivariate analysis of independent variables associated with MDRO mortality
Variable	N (9882)	Outcome		X² (df)*	p Value
Variable		Dead (n, %)	Alive (n, %)
Year
Post Covid (2020–2022) Pre Covid (2018–2019)	8319 1563	725 (8.7%) 226 (14.5%)	7594(91.3%) 1337 (85.5%)	49.92(1)	< 0.001
Department
Medical	7139	777 (10.9%)	6362(71.2%)	46.97(1)	< 0.001
Non-Medical	2743	174(6.3%)	2569(93.7%)
Previous Encounter to Healthcare Facilty
Yes	3393	291 (8.6%)	3102 (91.4%)	6.51 (1)	0.011
No	6489	660 (10.2%)	5829 (89.8%)
History of Surgical Intervention Within 1 Month
Yes	1459	76 (5.2%)	1383 (94.8%	38.35 (1)	< 0.001
No	8423	875 (10.4%)	7548 (89.6%)
History of Surgical Implant Within 1 Year
Yes	270	6 (2.2%)	264 (97.8%)	17.48(1)	< 0.001
No	9612	945 (9.8%)	8667 (90.2%)
Type of Specimen
Sterile	4126	591 (14.3%)	3535 (85.7%)	179.93 (1)	< 0.001
Non-Sterile	5756	360 (6.3%)	5396 (93.7%)
Isolated Organism
Gram Negative	7363	760 (10.3%)	6603(89.7%)	16.20 (1)	< 0.001
Non-Gram Negative	2519	191(7.6)	2328(92.4%)
Isolate Status
Infection	9882	951	8931	-	-
Type of Infection
Bloodstream Infection (BSI)	3960	570 (14.4%)	3390(85.6%)	172.90 (1)	< 0.001
Non-Bloodstream Infection	5922	381 (6.4%)	5541 (93.6%)
HCAI Status
HCAI	8566	904 (10.6%)	7662 (89.4%)	63.93(1)	< 0.001
Non HCAI	1316	47 (3.6%)	1269 (96.4%)
Antibiotic 1
Beta Lactam	8552	797 (9.3%)	7755 (90.7%)	6.75 (1)	0.001
Non-Beta Lactam	1330	154(11.6%)	1176 (88.4%)
Antibiotic 2
Beta Lactam	8552	797(9.3%)	7755 (90.7%)	6.756(1)	0.001
Non-Beta Lactam	1330	154 (11.6%)	1176 (88.4%)
Category
Major Specialist Hospital	3467	279(8.0%)	3188 (92.0%)	15.257 (1)	< 0.001
State Hospital	6415	672 (10.5%)	5743(89.5%)
Note: p < 0.05 is a significant determinant.
* Chi-square analysis

Table 5 presents the results of simple logistic regression and multiple logistic regression analyses of mortality outcomes and their independent variables. The simple logistic regression analysis revealed that all 13 variables were significant at p < 0.05. After controlling for the selected variables in the multiple logistic regression analyses, four (4) independent variables were associated with a higher risk of mortality. HCAI seemed to be the most significant predictor of the mortality outcome of a patient (aOR: 2.91, 95% CI: 2.15–3.94). This was followed by sterile specimens (aOR 2.33 95% CI: 2.02–2.68), gram-negative organisms (aOR: 1.63, 95% CI: 1.37–1.93), medical-based departments (aOR 1.47 95% CI: 1.22–1.75), and state hospitals (adjusted OR 1.22 95% CI: 1.05–1.42). There was no multicollinearity among these independent variables. Hosmer and Lemeshow goodness-of-fit tests demonstrated that our dataset fit well with the logistic model. This model was able to correctly predict 90.4% of mortality outcomes among MDRO cases and explained 9.9% of the variation in the outcome variable.

Table 5

Simple logistic regression and multivariate regression analyses of the independent variable and the mortality outcome.
Variable	Regression Coefficient	Crude OR (95% CI)	Wald statistic (df)	p value ^a	Adj OR (95% CI)	Wald Statistic	p value^b
Year
Post Covid (2020–2022) Pre Covid (2018–2019)*	-0.57	0.57(0.48–0.66) 1	48.83 (1)	< 0.001	0.59 (0.50–0.69)	38.91	< 0.001
Department
Medical	0.59	1.80 (1.52–2.14)	45.85 (1)	< 0.001	1.47(1.22–1.75)	17.34	< 0.001
Non-Medical		1
Previous Encounter to Healthcare Facility
Yes	-0.19	0.83 (0.72–0.96)	6.50(1)	< 0.001	-	-	-
No		1
History of Surgical Intervention Within 1 Month
Yes	-0.746	0.47 (0.37–0.60)	36.76 (1)	< 0.001	0.66 (0.51–0.85)	10.55	0.001
No		1
History of Surgical Implant Within 1 Year
Yes	-2.24	4.80 (2.13–10.81)	14.33	< 0.001	0.32(0.14–0.73)	7.31	0.007
No		1
Type of Specimen
Sterile	0.92	2.51(2.18–2.88)	170.90	< 0.001	2.33(2.02–2.68)	134.51	< 0.001
Non-Sterile		1
Isolated Organism
Gram Negative	0.34	3.19(2.36–4.30)	57.61	< 0.001	1.63(1.37–1.93)	29.93	< 0.001
Non-Gram Negative		1
Isolate Status
Infection	-2.24	0.11	4311.64	< 0.001	-	-	-
Type of Infection					-	-	-
Bloodstream Infection (BSI)	0.89	2.45(2.13–2.80)	164.71	< 0.001
Non-Bloodstream Infection		1
HCAI Status
HCAI	1.16	3.19(2.36–4.30)	57.61	< 0.001	2.91(2.15–3.94)	47.70	< 0.001
Non HCAI		1
Antibiotic 1
Beta Lactam	-0.24	0.79(0.65–0.94)	6.73	0.009	-	-	-
Non-Beta Lactam		1
Antibiotic 2
Beta Lactam	-0.24	0.79(0.65–0.94)	6.73	0.009	-	-	-
Non-Beta Lactam		1
Category
State Hospital	0.29	1.34(1.16–1.55)	15.17	< 0.001	1.21(1.05–1.42)	6.519	0.011
Major Specialist Hospital		1
^a Simple logistic regression analysis
^b Multiple logistic Regression Analysis

The model is based on forward LR. Nagelkerker R2 = 0.099

There was no multicollinearity (VIF < 10). No outliers. The model assumption was met

The Hosmer–Lemmeshow test was not significant (p = 0.123).

The sensitivity is 100.0, the specificity is 0.0, and the accuracy is 90.4

The mortality outcomes of 90.4% of the patients were predicted to be either alive or dead.

The model fits well

Mortality is significantly greater in healthcare-acquired infections (HCAIs) (p < 0.05) than in non-HCAIs. Studies have shown that MDRO infections are associated with increased mortality in HAIs in which an MDRO is involved (HAI-MDRO), which is 1.7 times greater (HR, 1.7; 95% confidence interval [CI], 1.25–2.32) than in infections caused by susceptible microorganisms(9). In the National Surveillance of Antibiotic Report of 2022, HCAI had the highest prevalence in state hospitals (5.07%), followed by major specialist hospitals (5.06%) and university hospitals (3.08%) (22). In healthcare settings, especially critical care, compliance with hand hygiene is crucial to prevent the transmission of infection from healthcare personnel to patients or vice versa. The national surveillance of hand hygiene compliance has improved over the years, with rates ranging from 79.6% in 2016 to 87.2% in 2020. However, the trend of HCAI from 2018 until 2021 has plateaued within the range of 4–5 per 100 admissions (24)

In our study, sterile samples were significantly associated with increased mortality risk (p < 0.05) among MDRO-infected patients, where 40.8% (n = 4029) of the blood was collected from sterile samples. This might be due to bloodstream infections (BSIs), which are commonly found in 40.1% (n = 3960) of MDROs. According to the chi-square analysis, the BSI was significantly associated with MDRO mortality (p < 0.05). According to a report by the Ministry of Health, Malaysia, in the Point Prevalence Survey HCAI findings, BSI was one of the most common types of HCAI (22). Few studies have revealed that risk factors for mortality in patients with BSI caused by MDROs include an ICU stay, where patients admitted to the intensive care unit (ICU) have a higher risk of mortality due to BSI caused by MDROs (9, 25, 26). Patients with severe clinical conditions are at increased risk of death (25).

Gram-negative bacteria (A. baumannii, ESBL - Klebsiella pneumoniae and MRSA) were associated with a greater risk of mortality among patients with MDRO infections (p < 0.05). Among gram-negative bacteria, the greatest concern that has been repeatedly highlighted is the presence of A. baumannii (19, 27, 28). Recent research has also indicated that infection with A. baumannii is a contributing factor to mortality in the ICU (17). The prevalence of commonly isolated MDROs among state hospitals and major specialist hospitals was A. baumannii. Other researchers reported the same findings for their hospital settings (19, 27). A. baumannii is an opportunistic bacterial pathogen primarily associated with hospital-acquired infections (27). The lack of adequate infection control measures and overuse of antimicrobial drugs have contributed to the increase in multidrug-resistant A. baumannii (20).

In our study, patients with MDRO infections who were admitted during the post-COVID-19 period (2020–2022) were at lower risk for mortality outcomes among MDRO patients than were patients who were admitted before the pandemic (2020–2022) (p < 0.05). However, this is the opposite, as the presence of MDRO infection is strongly associated with increased mortality in individuals with COVID-19. In a recent study, patients with MDRO infections had a four-fold greater risk of death than did those without MDRO infections, where MDRO infections can precipitate the deterioration of patients' health, resulting in sepsis and multiple organ failure, ultimately leading to mortality (18).

MDRO patients who were admitted to medical-based departments had a greater risk of mortality (p < 0.05). This might also be influenced by the fact that, in this study, medical departments and anaesthesia departments had a greater number of patients with MDRO infection than did nonmedical-based departments, such as surgical, orthopaedic or O&G departments. A previous study revealed that ICU patients had a greater risk of MDRO mortality than surgical wards did (9).

In our study, patients with a history of surgical intervention within the past month and patients who had a history of surgical implantation within 1 year had a lower mortality outcome (p < 0.05). This finding is in line with a previous study showing that there was an association between a history of previous surgery and MDRO mortality, and the number of deaths recorded was 13.4% lower (n = 76) in groups with a previous history of surgery than in those with no previous history of surgery (24.4%, n = 106) (9). However, other studies have consistently shown that patients who have undergone surgery are more likely to develop MDRO infections than are those who have not undergone surgery (14, 15, 17, 29)

Among the hospital categories, state hospitals had a greater mortality risk than major hospitals did (p < 0.05). One study revealed that the overall in-hospital mortality rate for patients admitted to tertiary care hospitals was greater than that for patients admitted to secondary care hospitals (median in-hospital death rates of 3.7% vs. 2.9%, respectively, p = 0.05) (30). A study in Brazil revealed that MDRO infection increased hospital mortality (31)

Limitations

Owing to the retrospective design of this study, there were incomplete data or missing data during the retrieval of information. The final diagnoses were incomplete, as they could help to further understand the aetiology that leads to mortality among MDRO patients. Length of stay and sociodemographic data were also not available. The availability of these data would be very valuable to demonstrate the association between this variable and mortality outcome.

MDRO infections are a significant public health concern because of their high mortality rates and potential for widespread transmission. In our study, HCAI, sterile specimens, gram-negative-negative bacteria, state hospitals and medical-based departments were associated with increased mortality risk in patients with MDRO infections. Prevention strategies include appropriate use of antimicrobials and proper infection control practices. Improved surveillance and reporting mechanisms, such as including final diagnoses, are necessary to better understand the burden of MDRO infections and guide research funding allocation.

Ethics approval

Ethics clearance and approval were obtained from the Medical Research and Ethics Committee (MREC) of the Ministry of Health Malaysia [NMRR ID-23-01759-ZOY (IIR)] and Research Ethics Committee from the National University of Malaysia [UKM PPI/111/8/JEP-2023-201] prior to the conduct of this study. Patient’s names were kept on a password-protected database and were linked only with a study identification number. All the data involved in this study is only restricted to the use by the investigator.

Consent for publication

We wish to thank the Director General of Health, Malaysia for his permission to publish this article.

Availability of data and materials

The data that support the study findings are available from the Ministry of Health Malaysia. Restrictions apply to the data availability, which was used under license for the current article, so it is not publicly available. Nevertheless, data are available from the authors upon reasonable request together with the permission of the Ministry of Health Malaysia.

Competing interests

None declared.

Funding

This research did not receive any external funding.

Authors’ contributions

SE designed the project and data collection tools. MNA provide the data. All the authors cleaned, analysed and interpreted the data. NM drafted the paper. SE reviewed and gave technical advisory towards the manuscript as well as contributed important revisions. All authors read and approved the manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Acknowledgements

Our deepest gratitude to the Infection Control Unit, Ministry of Health Malaysia, for sharing the data and information.

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No competing interests reported.

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Factors associated with multidrug-resistant organism (MDRO) mortality: An analysis from the National Surveillance of Multidrug-Resistant Organism, 2018-2022

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Abstract

Introduction:

Methods

Result

Conclusion

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Introduction

Materials and methods

2.1 Study design and settings

2.2 Study sample and data collection

2.3 Definition of Variables, Inclusion Criteria, and Exclusion Criteria

2.4. Statistical analysis

Results and Analysis

Discussion

Limitations

Conclusion

Declarations

References

Additional Declarations

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Version 1