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Prevalence and Predictive Factors for Nosocomial Infection in the Military Hospitals: A Systematic Review and Meta-Analysis

Background: To assess prevalence and predictive factors for Nosocomial Infection (NI) in the military hospitals. Methods: PubMed, Scopus, Cochrane and PreQuest databases were systematically searched for studies published between Jan 1991 and Oct 2017 that reported the prevalence of NI and predictive factors among military hospitals. We performed the meta-analysis using a random effects model. Subgroup analysis was done for heterogeneity and the Egger test to funnel plots was used to assess publication bias. Results: Twenty-eight studies with 250,374 patients were evaluated in meta-analysis. The overall pooled estimate of the prevalence of NI was 8% (95% 6.0–9.0). The pooled prevalence was 2% (95% CI: 2.0–3.0) when we did sensitivity analysis and excluding a study. The prevalence was highest in burn unit (32%) and ICU (15%). Reported risk factors for NI included gender (male vs female, OR: 1.45), age (Age≥65, OR: 2.4), diabetes mellitus (OR: 2.32), inappropriate use of antibiotics (OR: 2.35), received mechanical support (OR: 2.81), co-morbidities (OR: 2.97), admitted into the ICU (OR: 2.26), smoking (OR: 1.36) and BMI (OR: 1.09). Conclusion: The review revealed a difference of prevalence in military hospitals with other hospitals and shows a high prevalence of NI in burn units. Therefore careful disinfection and strict procedures of infection control are necessary in places that serve immunosuppressed individuals such as burn patient. Moreover, a vision for the improvement of reports and studies in military hospitals to report the rate of these infections are necessary.


Introduction
Nosocomial infections (NI) are straightly related to hospitalization of patients and considered a critical menace to patients' health (1,2). About 8.7% of hospitalized patients worldwide develop it (3,4). This phenomenon increases the cost of health services and reduces access to hospital care due to the prolongation of treatment and, on the other hand, causes mental and psychological problems for the patient and their families (2). Despite many efforts to control NIs, are estimated that these infections to be responsible for about 80,000 deaths in the US every year (5).
Military hospitals not only have a critical role in providing medical services to special patients such as militaries and their families, heads of state and governors but also play an important role in crisis management. Therefore, the people's and authority's expectance from military hospitals is highquality and safe care production. Moreover, the most common features among the patients are lower extremity amputation and receipt of massive blood transfusions following blast injuries incurred, in essence, the war affected the workload and productivity of military. This profile is consistent with a previous American military report while on foot patrol in southern Afghanistan or British military report in the "green zone" of Helmand province in Afghanistan (6,7). Various Meta-analyze of NI have been carried out among developing and developed countries and between different types of infections and risk factors (2,8,9), while no a comprehensive study on hospital infections among military hospitals has not been done on the prevalence of infections. Considering different of military hospitals management with non-military hospitals and in different countries, therefore it implies that the different results can be expected. The aim of this systematic review and meta-analysis was to assess prevalence and predictive factors for NI in the military hospitals.

Data extraction and quality assessment
Data were extracted by two investigators independently with disagreement resolved by consensus. Extracted data included: authors; year(s) conducted; year of publication; country where the study was done; study methods; number of hospitals studied; type of infection including most frequent infections; study methods; total number of subjects recruited; number of subjects with; risk factors of NI. We evaluated the methodological quality of the articles using a checklist (Quality assessment checklist for prevalence studies) adapted from Hoy et al (10). The checklist consists of nine questions that assesses the representativeness of sample, sampling technique, response rate, data collection method, measurement tools, case definitions, and statistical reporting. Each checked question was scored either as "1" or "0". The total score ranged from 0 to 9 with the overall score categorised as follows: 7 to 9: "low risk of bias", 4 to 6: "moderate risk", and 0 to 3: "high risk".

Statistical analysis
We used StataCorp version 14.2 to calculate pooled prevalence of NI and subgroups analysis in various variables was also performed. Predictive factors for NIs were estimated through estimating pooled ORs and 95% CIs. The predictive factors were considered significantly associated with NI when P<0.05 and 95% CI did not span 1. The I 2 statistic with a cutoff of 50% (11) was used to determine Heterogeneity between studies. Randomeffects model was done for pooled effect size for I 2 > 50%, a fixed-effects model was implemented in low degree of heterogeneity. Also the StataCorp was utilized to generate Forest plots of pooled prevalences. In this study Egger's test to funnel plots was applied to check the evidence of publication bias and subgroup analysis was done for heterogeneity. To assess the dependency of overall estimate on a single study sensitivity analysis was done.

Study selection
The search identified 87 from 1108 studies were included by excluding duplicate articles (n=210), and scanning titles and abstracts that met the requirements for inclusion in the Meta analysis. Then 59 studies excluded because of prevalence of NI not reported (n=17), not related to hospital (n=8), not related to Military (n=6), data of military hospital not extractable (n=6), and 18 article that were not in English by full-text screening. Overall, 28 articles were selected for prevalence and finally, of 28 included studies, 10 studies identified for risk factor of NI ( Fig. 1).

Characteristics of enrolled articles
The selected information about included articles are shown in Table 1. Twenty-eight studies with 250,374 patients (range from 63-56,644 per study) were evaluated in this meta-analysis.

Overall prevalence
After combining 7 prevalence from seven studies (12)(13)(14)(15)(16)(17)(18) with total population of 227,526, we found that 8% (95% 6.0-9.0) of participants were effected (Fig. 2). In addition, overall prevalence depended on study done by Liu when we did sensitivity analysis. After excluding mentioned study, the prevalence becomes 2% (95% CI: 2.0-3.0) (Fig.2). Potential sources of heterogeneity (I2= 99.7%, P<0.001) by random effects multivariate and univariate meta-regression were conducted with several assessed covariates, including geographical location, year of survey, sample size, number of hospital, study method, and quality score of bias risk. All of them may be the sources of heterogeneity. No publica-tion bias was found according to the results of Egger's test (P>0.05) and no evidence of funnel plot asymmetry was seen.

Discussion
The first systematic review and meta-analysis of studies performed to examining global prevalence of NI and predictive factors of NI among military hospitals. Information of more than 250 thousands patients is extracted and pooled by metaanalysis. It was strengthened by our precise methodology in data extraction and data pooled through Metaprop and Metan packages. Use of a random effects model according to the method (39) to collect data, a more conservative estimate of NI prevalence is provided and sensitivity analysis and publication bias were assessed at each stage. We were careful in each study to use only general patient data which were representative of the hospitalized patients to generalization of our results. The overall prevalence was shown a very low prevalence of 2% and represents a minor burden on military hospitals, with an even smaller epidemiological relevance than in developed countries (40,41). Pooled prevalence was showed in developing countries were 10.6% (CI: 8.1-13.9) which was substantially higher than the pooled prevalence in military hospitals (2). Similarly, the pooled prevalence in this meta-analysis is lower than the pooled prevalence (7.1%) in Europe (42) and USA (4.5 per 100 patients) (43). Various reasons, such as the sampling procedures, infection prevention protocols, during the study period, may have caused these varieties due to difference local conditions (44). In particular, regarding military hospitals, limiting access to patients' confidential information will also affect the results of studies. As well as one of the important factors was accessibility and use of a microbiology laboratory (27). However, this fact had an influence on report of the rate and prognosis of NI. Therefore, the hospital management can play an important role in report of NIs prevalence. Even the different of results among countries implies that the different management styles of military hospitals in different countries. The difference between our meta-analysis and mentioned studies is even more striking, when considering prevalence of ward-acquired infection with rates higher among patients admitted to burn units. In our review, pooled densities of infection in burn patients with prevalence of 32% compare to other patients were two to sixteen times higher than ICU (15%), surgical (7%) and other wards (2%). Since the burn wound is highly susceptible to colonization with all species of microorganisms, colonized microorganisms can be easily multiplied to achieve a high density on the wound. Therefore, large areas of open wounds make burn patients susceptible to infectious diseases. Moreover, the use of ventilator, blood and urine catheter, especially for people with severe burns, increases the basis for bacterial colonization and infection, on the other hand the use of broad-spectrum antibiotics also causes the loss of normal fluorine of patients and make them susceptible to invasion by pathogen bacteria. Therefore, in this study the rate of hospital infection among these patients were observed more (45,46). However, studies showed the prevalence was highest in ICUs, followed by surgery, etc. (47)(48)(49).
Substantially proportion of infection in military hospitals and others are different. In military hospitals high rates of NIs were seen in patients of burn unit. Thus, another factor contributing to the difference in the prevalence of kinds of infections among military hospitals with other hospitals was the difference in the combination of persons referring to military hospitals. These persons are mostly soldiers and survivors of war with their families, which seems to have different requirements than those who come to other hospitals. What are the important predictive factors of NI among military hospitals? The results identified several risk factors associated with NI in the pooled studies. Studies performed on military hospitals have suggested that obesity is associated with an increased risk of infection in these hospitals. Similarly a meta-analysis confirmed that obesity increases SSIs about twofold (50). Newell established a relationship between obesity and increased risk of UTIs (51). Despite these findings, in some studies there was no association between BMI and NI (20,52). Moreover, in present study showed BMI had less effect on NI. Additional research is necessary to find out the relationship between obesity and increased NI rates. The current analysis of risk factors identified the factors of smoking, male and age as independently associated with an increased risk of NI. However Suljagic did not support the relationship between smoking and its risk for SSI in a military hospital (20), Watanabe showed that a preoperative smoking habit is a significant risk factor for SSI (53). Previous studies dealing with smoking and its risk for NI in military hospitals are difficult to interpret, because the definition of smoking was not standardized or active smokers was not clearly defined. About sex and age different studies conducted and indicated that the relationship between this factors and the rate of NI varied related to the underlying acute reason for hospitalization (54,55).
Our pooled data shown that diabetes mellitus and other co-morbidities were the factors most strongly associated with NIs. Patients with diabetes mellitus are considered to be immunocompromised and therefore more susceptible to NI (56)). Diabetes mellitus was reported to be a risk factor for development of NI in many studies (57,58).
Contrary to the current studies, some studies showed that diabetes mellitus was not a risk factor for development of NI (59,60). Perhaps further research is needed to help determine the impact of diabetes mellitus on the incidence of NI. Other co-morbidity such as chronic obstructive pulmonary disease, neurological diseases, solid tumors, rheumatoid arthritis, prostate hypertrophy, atherosclerosis are the disease have been implicated as predisposing factors for infection (61). This type of diseases such as diabetes mellitus, impair leukocyte functions and increased the risk of NI. Chronic diseases in study by Erika were at a substantially greater risk (with a 3.6-fold increased risk) for developing a NI compared with other hospitalized patients (62) that exactly are in agreement with present study. In addition to above mentioned factors, risk factors of received mechanical support, inappropriate use of antibiotics and admitted into the ICU were strong predictors for NI conformed in many studies. For instance a study indicated received mechanical support is the most important factors in infection's speed. VAP is seen in 10 to 20% of patients receiving mechanical ventilatory support (63). Totally, there was no difference between military hospitals and other hospitals regarding predictors of NIs, and all the identified risk factors in previous studies also were observed in other hospitals. This study had some limitations include countries study (most of these countries were part of the Middle East) and even finding accuracy which they can affect on the results of NIs in military hospitals.

Conclusion
In military hospitals the general infections of hospital were reported to be less than common. Of course, one of the study limitations should be mentioned that most of these countries were part of the Middle East and it is likely that the diagnosis of NIs and their use in future decisions of the organization are not priorities of military hospital or these countries do not have advanced knowledge and tools to identify the infectious agents, therefore, less hospital infections is reported. The rate of infection in the burn unit was significantly higher than other units. Maybe, heavy workload, health workforce shortage, lock of access to desirable hygiene products and skin irritation by hand hygiene products in military hospital have been the major reasons for the rate of infection in the burn unit. Considering that the predictors of NIs detected in military hospitals are common in other studies. To reduce the risk of NIs, the available protocols be used, focusing on these risk factors.

Ethical considerations
Ethical issues (Including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, etc.) have been completely observed by the authors.