A Meta-Analysis on Evaluation of Nosocomial Infections Amongst Patients in a Tertiary Care Hospital - Hindawi.com
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Hindawi
Journal of Healthcare Engineering
Volume 2021, Article ID 4386423, 6 pages
https://doi.org/10.1155/2021/4386423
Research Article
A Meta-Analysis on Evaluation of Nosocomial Infections Amongst
Patients in a Tertiary Care Hospital
Baozhi Zhang, Xiao Ling Wu, and Ruiping Li
The Second Affiliated Hospital Of Guangdong Medical University, Zhanjiang, Guangdong, China
Correspondence should be addressed to Ruiping Li; apzljld@163.com
Received 26 July 2021; Revised 22 August 2021; Accepted 13 September 2021; Published 1 October 2021
Academic Editor: Malik Alazzam
Copyright © 2021 Baozhi Zhang et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background. Hospital-acquired infections, also known as nosocomial infections, are one of the many severe outcomes amongst
patients in tertiary care hospitals. Hospital-acquired influenza is amongst the most common infection which has affected huge
population. Objective. We have performed a meta-analysis in order to summarize the effects of epidemiology and clinical
characteristics in HAI. Methods. We performed literature review with help of PubMed, Cochrane Library, Embase, Scopus, Web of
Science, China National Knowledge Infrastructure (CNKI), The Global Index Medicus (GIM), and other clinical databases till
2021. Many random models were used in order to obtain pooled proportions, mean difference, odds ratio, and CI. Results. A total
of six studies were analyzed, where a total of 491 nosocomial and 4030 nonnosocomial infection cases were reported. The odds
ratio of mortality was 0.02 with 95% CI and the risk ration for males was 1.08 with 95% CI. Conclusion. The proportion of
nosocomial infections in cases of influenza was higher in patients admitted in tertiary care hospitals. Thus, a surveillance system
for vaccination for all the high-risk patients must be made mandatory.
1. Introduction Around 8.7% of the patients in the hospitals fall under
the risk of exposure to the nosocomial infections which
Nosocomial infections are one of the extensive problems multiply the complicated conditions such as cancer, surgery,
faced by the hospitals at a global level. These nosocomial or any cases of organ transplant, thereby surging the
infections, often termed as hospital-acquired infections mortality rate [8]. In an epidemiological study conducted by
(HAIs) or even healthcare-associated infections (HCAI), are WHO in 14 countries across the world, 8.7% cases of
a major challenge as it affects large number of patients who nosocomial infection cases were reported. This data ranged
are in need of intensive care [1, 2]. The majority of cases of from 5.0% cases in North American region to 40% in the
distress and mortality are caused because of the nosocomial Asian subcontinent, Latin America, and Sahara regions of
infections, where environmental contamination plays a Africa [9].
crucial role in the transmission. Human influenza is among There is a high range of pathogens which cause noso-
the transmissible critical respiratory illness which is spread comial infections such as Acinetobacter baumannii, meth-
by influenza A and B virus [3]. The nosocomial infection icillin-resistant Staphylococcus aureus (MRSA),
cases usually occur during the annual pinnacle of the col- vancomycin-resistant enterococci (VRE), Clostridium diffi-
lective influenza activity where the healthcare workforce and cile, and Pseudomonas aeruginosa that dwell in the envi-
the patient visitors (family, relatives, and friends) were ronment for a longer duration [10–12]. There are multiple
identified as the most frequent sources [4]. The most environmental conditions which influence the presence of
common hospital-acquired infections include the ventilator- microorganisms, where number of people present plays the
associated pneumonia, blood-borne infections, surgical site major role, followed by the level of moisture and material
infections, and urinary tract infections [5–7]. supporting microbial growth [13]. Therefore, for a2 Journal of Healthcare Engineering
comprehensive understanding, we have performed meta- nosocomial (number of patients suffering from nosocomial
analysis on the origin and spread of nosocomial infections in infection per 100 patients).
a tertiary care hospital. Cumulative incidence (CI) was defined in the analysis as
new cases per 100 patients over a duration of time. Data were
2. Methodology collected on the basis of prevalence of nosocomial infection,
devices linked with infections, ventilator days, incidences of
2.1. Search Strategy. The protocols’ preparation was done on nosocomial infections in ICUs, and CI of SSI, surgical site
the basis of Preferred Reporting Items for Systematic Re- infection. Random meta-analysis was conducted on all the
views and Meta-analysis (PRISMA). The outcomes will be data’s pooled. Forest plot and funnel plot were plotted
outlined on how the articles were filtered and selected for corresponding with 95% confidence intervals (CIs).
inclusion. The exploration of data was performed using
PubMed/MEDLINE (studies from 1997 to May 2021), Web 3. Results
of Science (studies from 2001 to May 2021), The Global
Index Medicus (GIM) (studies from 2004 to May 2021), We analyzed five studies on basis of characteristics of study
Embase (studies from 1999 to April 2021), Cochrane and as mentioned in Table 1.
China National Knowledge Infrastructure (CNKI), Scopus 95% CI was 0.35 (0.29–0.42) which was found for
(studies from 1995–2021), and MeSH library terms and mortality and survival of hospital-acquired influenza, nos-
proper usage of keywords. ocomial infections.
The combination of keywords used for search were Odds ratio with 95% CI (0.01–0.08) have emphasized
“nosocomial infections,” “hospital-acquired infections that hospital-acquired cases were relatively higher as com-
(HAIs),” “healthcare-associated infections (HCAI),” “mul- pared to the CAI in influenza infections of patients in
tidrug resistant organism (MDROs),” nosocomial patho- tertiary care hospitals.
gens, environmental contamination, healthcare-acquired HAI cases were higher in comparison to the CAI cases.
infections, and nosocomial bacterial infections. The Risk ratio was analyzed with 95% CI (0.93–1.26) for
screening of title and abstract and the entire text review was identifying the prevalence of nosocomial and non-
performed on the prospective studies that were found nosocomial infections in males.
eligible. The factor for gender was ruled out for nosocomial
infections and males were more prevalent to nonnosocomial
infections.
2.2. Inclusion Criteria. The inconsistency associated with the
Risk of bias: there was no risk of bias in publication of the
inclusion of research works was concluded through dis-
studies.
cussion. The effort was put in to establish communication
with the authors of the papers which were included in the
study after filtering. The trials incorporated in the study were 4. Discussion and Conclusion
based on the types of multiple units with which reported Six studies were involved in the study of evaluating the cases
patient data from the entire hospital, discrete clinical wards, of nosocomial infections in patients admitted in tertiary care
or subgroups without sorting a specific disease. The pop- hospitals (Figure 1). Influenza cases were studied in this meta-
ulation-related inspection studies which recorded the reg- analysis where the hospital-acquired infections (nosocomial)
ularity nosocomial infections and the retrospective or case- were compared with the community acquired infections
control studies with clear and detailed data were also (nonnosocomial). An odds ratio (OR) of 0.02 with 95% CI
considered. The characteristics of included studies are was noted for mortality in cases of nosocomial versus non-
shown in Table 1. nosocomial infections. Risk ratio for cases in males was found
to be 1.08 with 95% CI. 95% CI was 0.35 (0.29–0.42) was
2.3. Exclusion Criteria. Different studies with design found for mortality and survival of hospital-acquired influ-
structure such as reviews, letters, conference abstracts, case enza, nosocomial infections, as shown in Figure 2 (forest
studies, and duplicate publications and the studies missing plot), and the funnel plot for the same is shown in Figure 3.
the crucial data or original data were excluded. Some articles Characteristics of study for the patients are shown in Table 2.
were also removed as they were not accessible even after Total number of cases reported of nosocomial and
contacting the authors. The studies which were not written nonnosocomial influenza infections of patients in tertiary
in English were also excluded along with the single reports care hospitals for each study are reported in Table 3. Odds
that consisted of incomplete datasets or guidelines. ratio with 95% CI (0.01–0.08) have emphasized that hos-
pital-acquired cases were relatively higher as compared to
the CAI in influenza infections of patients in tertiary care
2.4. Data Analysis and Statistical Assessment. Pooling of data hospitals; the forest plot is shown in Figure 4, and the funnel
was done by reporting same outcomes and occurrence plot showed HAI cases were higher in comparison to the
measures (cumulative incidence and prevalence). Prevalence CAI cases are shown in Figure 5.
was here defined as the number of incidences (infections) Number of males reporting influenza cases in noso-
reported every 100 patient who spent time in hospital for a comial and nonnosocomial category in tertiary care
duration of time and ratio of patients suffering from hospitals are shown in Table 4; the risk ratio was analyzedJournal of Healthcare Engineering 3
Table 1: Characteristics of included studies.
Characteristics [14] [15] [16] [17] [18] [19]
Cross Cross Cross
Study design Case control Case Cross sectional
sectional sectional sectional
Sample size 382 1722 208 292 860 2421
Mean age of patients (HAI)
62 N/A 79.1 79 82 53.47
nosocomial
Mean age of patients (CAI) 60.4 N/A 64.8 76 47 48.86
46.5% 54.38%
Gender 43.1% female 50% female 35.7% female 42.88% female
female female
2010/2011–2015/ 2016/12–2017/
Duration of study 2017-2018 2017 2020 2009–2015
2016 02
United
Country Spain France Australia France Spain
States
Study quality 7 8 7 6 6 7
Prospective related articles that were recognized and Other additional records
filtered using the following MeSH terms: “nosocomial recognized through other
Identification
infections”, “HAIs” “HCAI”, “MDROs” “nosocomial platforms
pathogens” “environmental contamination” “healthcare (n = 3)
acquired infections” “nosocomial bacterial infections”,
“Tertiary care hospital”, “hospital”, “intensive care”
utilizing (clinical databases and other databases)
n = 223
Possibly appropriate papers as per searches
n = 226
Screening
Applicable to the objective of the paper = 174
Removal of redundant records
= 52
Articles that were rejected on the basis of
Full text titles obtained for eligibility = 6 exclusion criteria: inappropriate conclusions
Eligibility
or results, no clinical characteristics data,
abstract failure to comply with retrieval
criteria, non-English articles = 168
Studies included for acceptance which were
Systematic Review and Meta-analysis based on
inclusion criteria (n = 6)
Included
Final Studies Included
n=6
Figure 1: PRISMA study for the learning process.4 Journal of Healthcare Engineering
Mortality Survival Risk Ratio Risk Ratio
Study or Subgroup Weight (%)
Events Total Events Total M–H, Fixed, 95% CI M–H, Fixed, 95% CI
F. A'lvarez–Lerm 2017 76 224 148 224 51.9 0.51 [0.42, 0 63]
Nikita Parkash 2019 2 28 26 28 9.1 0.08 [0.02, 0 29]
P. Godoy 18 96 78 96 27.4 0.23 [0 15, 0 35]
Werner Bischof 2019 4 37 33 37 11.6 0.12 [0.05, 0.31]
Total (95% CI) 385 385 100.0 0.35 [0.29, 0.42]
Total events 100 285
Heterogeneity: Chi = 26.82, df = 3 (P < 0.00001); I2 = 89%
2
Test for overall effect: Z = 11.31 (P < 0.00001)
0.01 0.1 1 10 100
Mortality Survival
Figure 2: Forest plot on mortality and survival rates in nosocomial infections and the risk difference with 95% CI was noted.
0 SE (log[RR])
0.2
0.4
0.6
0.8
RR
1
0.01 0.1 1 10 100
Figure 3: Funnel plot on mortality and survival rates in nosocomial infections was analyzed in both survival cases and mortality.
Table 2: Cases of mortality and survival in hospital-acquired influenza, nosocomial infections.
S. No. Characteristics [15] [16] [16] [17] [18] [19]
1. Mortality 4 18 N/A 2 N/A 76
2. Survived 33 78 N/A 26 N/A 148
3. Total nosocomial 37 96 49 28 57 224
Table 3: Total number of cases reported of nosocomial and nonnosocomial influenza infections of patients in tertiary care hospitals.
Characteristics [14] [15] [16] [17] [18] [19]
HAI 37 96 49 28 57 224
CAI 75 1626 159 264 803 1103
Total 112 1722 208 292 860 1327
HAI, hospital-acquired infection; CAI, community-acquired infection. The above table mentions the events recorded for both nosocomial and non-
nosocomial influenza infection cases.
with 95% CI (0.93–1.26) for identifying the prevalence of As the ratio of hospital-acquired infections (nosocomial)
nosocomial and nonnosocomial infections in males, and is increasing in patients admitted in tertiary care hospitals,
its forest plot is shown in Figure 6, while the funnel plot on hence, a strict surveillance must be enforced for higher risk
the risk ratio of the number of males affected by noso- patients. In cases of diseases such as influenza which has
comial infections in tertiary care hospital, and its preva- high affinity in nosocomial infections, a system of vacci-
lence in Figure 7. nation must be implied for admissions.Journal of Healthcare Engineering 5
HAI CAI Odds Ratio Odds Ratio
Study or Subgroup Weight (%)
Events Total Events Total M–H, Random, 95% CI M–H, Random, 95% CI
BischoffW 37 112 75 112 16.4 0.24 [0.14, 0.42]
F. A'lvarez–Lerm 224 1327 1103 1327 16.9 0.04 [0.03, 0.05]
Godoy P 96 1722 1626 1722 16.8 0.00 [0.00, 0.00]
Luque–Paz D 57 860 803 860 16.7 0.01 [0.00, 0.01]
Parkash N 28 292 264 292 16.4 0.01 [0.01, 0.02]
Pauline N 49 208 159 208 16.6 0.09 [0.06, 0.15]
Total (95% CI) 4521 4521 100.0 0.02 [0.01, 0.08]
Total events 491 4030
2 2 2
Heterogeneity: Tau = 2.38, Chi = 364.59, df = 5 (P < 0.00001); I = 99%
Test for overall effect: Z = 5.88 (P < 0.00001)
0.01 0.1 1 10 100
HAI CAI
Figure 4: Forest plot of nosocomial versus nonnosocomial infections (for both HAI and CAI cases).
SE (log[OR])
0
0.1
0.2
0.3
0.4
OR
0.5
0.01 0.1 1 10 100
Figure 5: Funnel plot on the odds ratio of incidences of nosocomial versus no-nosocomial infections (for both HAI and CAI cases).
Table 4: Gender-based analysis; number of males reporting influenza cases in nosocomial and nonnosocomial category in tertiary care
hospitals.
Characteristics [14] [15] [16] [17] [18] [19]
HAI 23 53 17 18 31 142
N (HAI) 37 96 49 28 57 224
COI 35 926 87 122 392 626
N (CAI) 74 1626 159 264 803 1103
HAI, hospital-acquired infection; CAI, community-acquired infection; N � number.
Nosocomial Non–nosocomial Risk Ratio Risk Ratio
Study or Subgroup Weight (%)
Events Total Events Total M–H, Fixed, 95% CI M–H, Random, 95% CI
BischoffW 23 37 35 74 11.8 1.31 [0.93, 1.86]
F. A'lvarez–Lerm 142 224 626 1103 26.6 1.12 [1.00, 1.25]
Godoy P 53 96 926 1626 21.3 0.97 [0.81, 1.17]
Luque–Paz D 31 57 392 803 17.0 1.11 [0.87, 1.43]
Parkash N 18 28 122 264 13.8 1.39 [1.03, 1.89]
Pauline N 17 49 87 159 9.5 0.63 [0.42, 0.95]
Total (95% CI) 491 4029 100.0 1.08 [0.93, 1.26]
Total events 284 2188
Heterogeneity: Tau2 = 0.02, Chi2 = 12.35, df = 5 (P = 0.03); I2 = 60%
Test for overall effect: Z = 0.97 (P = 0.33) 0.2 0.5 1 2 5
Nosocomial Non–nosocomial
Figure 6: Forest plot on risk ratio of gender-based effect of nosocomial infections in tertiary care hospitals.6 Journal of Healthcare Engineering
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