Prevalence of health care associated infections and antibiotic use among adult patients: Results of a cross-sectional survey at a tertiary university hospital in Tunisia

Mariem Nouira; Mohamed Maatouk; Sarra Ben Youssef; Samir Ennigrou

doi:10.12688/f1000research.139631.1

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Research Article

Prevalence of health care associated infections and antibiotic use among adult patients: Results of a cross-sectional survey at a tertiary university hospital in Tunisia

[version 1; peer review: awaiting peer review]

Mariem Nouira¹, Mohamed Maatouk², Sarra Ben Youssef¹, Samir Ennigrou¹

PUBLISHED 11 Sep 2023

Author details Author details

¹ Epidemiology and Community medicine department, Charles Nicolle Hospital of Tunis- Faculty of Medicine of Tunis- University Tunis El Manar -Tunisia, Tunis, Tunisia
² Department of General Surgery A, Charles Nicolle Hospital of Tunis- Faculty of Medicine of Tunis- University Tunis El Manar -Tunisia, Tunis, Tunisia

Mariem Nouira
Roles: Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Mohamed Maatouk
Roles: Writing – Original Draft Preparation, Writing – Review & Editing

Sarra Ben Youssef
Roles: Data Curation, Investigation, Resources

Samir Ennigrou
Roles: Conceptualization, Data Curation, Methodology, Supervision, Validation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS AWAITING PEER REVIEW

Abstract

Background: Healthcare-associated infections (HAIs) represent a major public health problem concern with a high attributable morbidity and mortality. This study aimed to estimate the prevalence of HAIs among adult patients at the Charles Nicolle Hospital (CNH) of Tunis and to identify the main associated factors as well as to estimate the frequency of antibiotic use.
Methods: This was a cross sectional study at the CNH with a unique passage per department (October-December 2018). All patients present at the wards for more than 48 hours were included. The site definitions of infections proposed by the Centers for Disease Control and Prevention were used.
Results: A total of 261 patients were included with a mean age of 52.4 years SD (±16.1) and a sex ratio (Female/Male) of 1.25. Overall, 34 patients having at least one active HAI were identified which represent a prevalence of 13% (95% CI [9.2 %–17.0 %]). The most common type of reported infections were urinary tract infections (33.3%) followed by surgical site infections (19.4%) and pneumonia (19.4%). Independent risk factors of high prevalence of HAIs among adults above 18 years old were: having hypertension (OR_adjusted=3.3;p=0.008), alcohol use (OR_adjusted=5.2; p=.01), being infected at admission (OR_adjusted=2.8;p=0.01), having at least one invasive device inserted during last 7 days prior to the survey date (OR_adjusted=3.5;p=0.004) and undergoing a surgery 30 days prior to the study date (OR_adjusted=2.6;p=0.03). The antibiotic use prevalence was 32.2%.
Conclusions:
An infection prevention and control committee, as well as the development of an Antibiotic stewardship program with continuous monitoring using repeated prevalence surveys, must be implemented to limit the frequency of these infections effectively.

Keywords

Prevalence, Healthcare Associated infection, Antibiotic

Corresponding author: Mariem Nouira

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2023 Nouira M et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Nouira M, Maatouk M, Ben Youssef S and Ennigrou S. Prevalence of health care associated infections and antibiotic use among adult patients: Results of a cross-sectional survey at a tertiary university hospital in Tunisia [version 1; peer review: awaiting peer review]. F1000Research 2023, 12:1132 (https://doi.org/10.12688/f1000research.139631.1) First published: 11 Sep 2023, 12:1132 (https://doi.org/10.12688/f1000research.139631.1) Latest published: 11 Sep 2023, 12:1132 (https://doi.org/10.12688/f1000research.139631.1)

Introduction

Healthcare-associated infections (HAIs) constitute a major global public health concern worldwide with a high attributable morbidity and mortality.¹

They lead to a heavy economic burden on health systems by extending the length of patient’s hospital stay in healthcare settings, increasing medical care costs and prescribing supplementary antibiotics, thus increasing the risk of antimicrobial resistance problem.²

This concern represents a real health threat, especially in the developing countries with a higher morbidity and mortality compared to developed countries. The risk of contracting a HAI during hospital stay is multiplied by 2 to 20 times in developing countries with a prevalence that can exceed 25% in some countries.³

This problem is still largely underestimated in these countries because of the lack of surveillance data and epidemiological studies.⁴

There are limited data on HAIs available in Tunisia. According to the latest published results of the national nosocomial infection prevalence survey conducted in 2005 “NosoTun-2005”, the prevalence of HAIs was of 13.2%.⁵

Conducting regular cross-sectional point prevalence surveys to have punctual and rapid baseline information about HAIs is recommended and constitutes a good alternative to overcome the problem of unavailable continuous prospective surveillance system in hospital settings.⁶

Before instauration of a prevention strategy program at a healthcare institution we need to assess the magnitude of the HAIs problem and to identify the high-risk population to establish priorities of infection prevention and control.

This study aimed to estimate the prevalence of HAI among adult patients at the Charles Nicolle Hospital (CNH) of Tunis and to identify the main associated factors as well as to estimate the frequency of antibiotic use.

Methods

Study design and settings

We conducted an observational cross-sectional (point prevalence) survey in all the adult wards (medical and surgical specialities) in the tertiary university CNH of Tunis from October to December 2018. Data collection was finalized within the same day for each ward, with a single passage per ward.

Inclusion criteria and case definitions (study population)

All patients hospitalized for 48 hours or more and having an age >18 years were included in the survey. All patients which were effectively present (including any patient absent from bed for further examinations, surgery, or specialized consultation) at the day of the survey were included. Patients consulting at outpatient departments, outpatient dialysis, and emergency rooms were not included.

The Centers for Disease Control and Prevention (CDC) Point Prevalence Survey (PPS) protocol was used as a methodological guideline. HAI was retained if the patient had a clinically active (having symptoms of infection present on the survey date, or if signs and symptoms were present previously and the patient was receiving treatment on the survey date) and/or microbiologically confirmed infection at the survey day (based on results of microbiological exams requested by the medical staff from the patient's file). We adopted the definition of different anatomic HAI sites proposed by the CDC.⁷

Data collection

Data collection was carried out using the medical records and by interviewing the nurse and the medical staff if necessary. The identification and the affirmation of the nosocomial source of any type of infection was confirmed by the medical staff with reference to the CDC definitions criteria.

The information was collected using a standard data collection form per patient. It consisted of two main parts:

• A part for the identification characteristics of the patient; the reason for hospital admission, medical and surgical risk factors such as tobacco and alcohol consumption, immunosuppression, neutropenia, diagnostic category (medical or surgical), infection on admission, diabetes, hypertension, history of a surgery act during the 30 days before the survey, inserted invasive devices and ATB use. Factors related to the surgical interventions such as the context of the surgery (in emergency or programmed), and the American Society of Anesthesiologists (ASA) physical status score¹ (The ASA classification and peri-operative risk⁸) and the surgical wound classification (class I: Clean; class II: Clean-Contaminated; class III: Contaminated; class IV: Dirty-Infected) were also collected. This first part was filled for all included patients.
• A second part that has been filled only for patients with one (or more) HAI(s) with information regarding the site of infection and microorganism(s) isolated.

Study process

Training sessions for all investigators were organized before the start of data collection. The training was done to explain the aim of the study, the practical modalities of study conduction and to represent the data collection form.

Heads of the different adult wards have been officially contacted by the hospital management to inform them about the study. A referent staff (medical or paramedical) has been appointed in each ward to ensure the smooth running of the study and to facilitate data collection and access to information for investigators.

A list of all eligible patients aged > 18 years and who are hospitalized for at least 48 hours in each ward was prepared in advance (at the day of the survey) by the referent staff before starting data collection by the investigators team.

Statistical analysis

Our study follows the SAGER guidelines for reporting sex and gender information. Sex and gender differences were not taken into consideration for the design of the study. Adequate representation of males and females was not possible because it was a cross sectional study without sampling and all eligible patients were included in the study regardless of sex. The information regarding the sex of participants was collected from records. Sex-based analyses was reported.

All statistical analysis were performed using SPSS Statistics software version 23 (IBM Corporation, Armonk, NY).

The statistical unit of analysis was the infected patient with one or more site of HAI.

Qualitative variables were presented as simple frequencies and relative frequencies (expressed into percentages). The mean (± the standard deviation) or the median with the interquartile range, as well as the extreme values were estimated to summarize quantitative variables.

The prevalence of HAIs was estimated with presentation of the 95% CI.

Proportions and means were compared using Chi square test (Fisher's exact test if not applicable) and Student’s t-test for independent groups, respectively.

Independent risk factors of HAIs were identified by multivariate analysis using binary logistic backward stepwise regression (adjusted OR [AOR]; 95% CI; p).

In the univariate logistic regression, measures of association were expressed as brut odds ratios (ORb) with 95% confidence intervals (CIs).

The selection of the explanatory variables to be introduced into the initial model of the multivariate analysis was made by taking into consideration the significance level p ≤ 0.20 at the stage of the univariate analysis and by introducing variables having a clinical relevance (not significant in the univariate analysis) in the initial model and which are known as confounding factors. The significance level was fixed to p ≤ 0.05.

Ethical considerations

All included participants were informed about the purpose of the study and have given their verbal consent to be included in the study. All medical and paramedical staff who were interviewed to have access to patients’ information were informed about the aim of the study and have given their verbal consent to collaborate with the investigators team. They were also informed about their right to refuse participation or drop out at any moment of the study collection. All collected information and data analysis was confidential and anonymous during and after data collection.

No blood samples were taken or procedures performed on the participants for research purposes. This survey was carried out as part of activities to limit HAI in the CNH. The study protocol was presented to the medical committee of the hospital and was approved in September 2018 before the start of the investigation. Considering that the data collection had to be completed in a single day during a single visit to each ward, since it was a point prevalence survey, and given the small number of investigators and most of the hospital departments are very large with several units, we preferred to obtain verbal consent to facilitate data collection in the field. The verbal consent was discussed and approved by the committee.

Results

Patients’ characteristics

Table 1 summarizes patients’ baseline characteristics. Overall, 261 patients were included, with 145 women (55.6%) and a sex ratio (F/M) = 1.25. The median age was 53 years (IQR = [39-65 years]), with extremes varying between 19 and 90 years old. In total, 69 patients were aged above (≥) 65 years (26.4%). Antibiotic treatment was used in 84 (32.2%) cases. 13 (5.0%) patients resided in an intensive care unit (ICU) unit on the day of the survey. 52 (19.9%) underwent a surgery during the last 30 days before the survey date. 76 (29.1%) patients had at least one invasive device (ID) inserted during the last 7 days prior the investigation date.

Table 1. Patients’ baseline characteristics (N = 261).

Characteristics	Number	Percentage (%)
Sex
Female	145	54.6
Male	116	44.4
Age categories (years)
18-65	192	73.6
≥65	69	26.4
Diabetes
Yes	57	21.9
No	203	78.1
Hypertension
Yes	66	25.4
No	194	74.3
Immunosuppression
Yes	50	19.5
No	207	80.5
Neutropenia
Yes	3	1.2
No	253	98.8
Obesity
Yes	25	12.4
No	176	87.6
Tobacco use
Yes	59	23
No	198	77
Alcohol use
Yes	15	5.8
No	242	94.2
Antibiotic treatment
Yes	84	32.2
No	177	67.8
Transfer from another department
Yes	20	7.7
No	234	89.7
Surgery 30 days prior to the study date
Yes	52	19.9
No	209	80.1
Intensive care unit (ICU)
Yes	13	5
No	248	95
Invasive medical device during last 7 days
Yes	76	29.1
No	185	70.9

HAI prevalence

A total of 34 patients having at least one active HAI were identified among eligible patients, which represents a rate of infected patients of 13% (95% CI [9.2%–17.0%]). The frequency of HAI was not significantly associated with sex (16.4% (n = 19) among males vs. 10.3% (n = 15) among females; p = 0.15). The characteristics of these patients are summarized in Table 2.

Table 2. Baseline characteristics of infected patients disaggregated by sex (N = 34).

Characteristics	Male	Female	Total
Characteristics	Number	Number	Number	Percentage (%)
Total (n (%))	19 (55.9)	15 (44.1)	34	100
Age categories (years)
18-65	13	8	21	61.8
≥65	6	7	13	38.2
Diabetes
Yes	2	3	5	14.7
No	17	12	29	85.3
Hypertension
Yes	4	9	13	38.2
No	15	6	21	61.8
Immunosuppression
Yes	4	4	8	23.5
No	15	11	26	76.5
Neutropenia
Yes	0	1	1	2.9
No	19	4	33	97.1
Obesity
Yes	0	1	1	4.3
No	15	7	22	95.7
Tobacco use
Yes	6	0	6	18.2
No	12	15	27	81.8
Alcohol use
Yes	5	0	5	10.0
No	13	15	28	90.0
Antibiotic treatment
Yes	17	13	30	88.2
No	2	2	4	11.8
Transfer from another department
Yes	5	1	6	17.6
No	14	14	28	82.4
Surgery 30 days prior to the study date
Yes	8	4	12	35.3
No	11	11	22	64.7
diagnostic category at admission
Medical	13	12	25	73.5
Surgical	6	3	9	26.5
Infection at admission
Yes	11	5	16	47.1
No	8	10	18	52.9
Intensive care unit (ICU)
Yes	4	0	4	11.8
No	15	15	30	88.2
Invasive medical device during last 7 days
Yes	14	8	22	64.7
No	5	7	12	35.3
Number of HAIs
One	18	14	32	94.1
Two	1	1	2	5.2

A total of 36 sites of HAIs was identified which represents a rate of HAI site prevalence of 13.8% (95% CI [10.13%–18.5%]). 2 patients were identified with 2 active HAIs.

The most frequent types of reported HAI were urinary tract infections (n = 12, 33.3%) followed by surgical site infections (n = 7, 19.4%) and pneumonia (n = 7, 19.4%).

Of all HAIs, 15 infections were microbiologically documented (15/36 = 41.6%). Pseudomonas aeruginosa and Escherichia coli were the most frequently documented microorganisms with equivalent frequency of 26.6% for each one.

HAI risk factors

Univariate analysis revealed that alcohol use (OR_brut = 3.8; p = 0.03), having community infection at admission (OR_brut = 3.3; p = 0.001), having at least one invasive device during last 7 days prior to the survey date (OR_brut = 5.9; p < 0.001), surgery during last 30 days prior to the study date (OR_brut = 2.5; p = 0.01) were found to be significantly associated with HAIs.

Risk factors found to be independently associated with HAIs in multivariate analysis, were: having hypertension (OR_adjusted = 3.3; p = 0.008), alcohol use (OR_adjusted = 5.2; p = 0.01), being infected at admission (OR_adjusted = 2.8; p = 0.01), having at least one invasive device during last 7 days prior to the survey date (OR_adjusted = 3.5; p = 0.004) and undergoing surgery 30 days prior to the study date (OR_adjusted = 2.6; p = 0.03) (Table 3).

Table 3. Univariate and multivariate analysis results of associated risk factors for HAIs.

Risk factors	Prevalence of infected patients n (%)	OR _brut [IC à 95%]	P	OR _adjusted [IC à 95%]	P
Sex			0.15
Male	19 (16.4)	1.7 [0.8 – 3.5]
Female	15 (10.3)	Ref.
Age ≥ 65 years			0.09
Yes	13 (18.8)	1.9 [0.9 – 4.0]
No	21 (10.9)	Ref.
Tobacco use			0.48
Yes	6 (10.2)	0.7 [0.3-1.8]
No	27 (13.6)	Ref.
Alcohol use			0.03		0.01
Yes	5 (33.3)	3.8 [1.2-11.9]		5.2 [1.3-20.3]
No	28 (11.6)	Ref.
Diabetes			0.27
Yes	5 (8.8)	0.6 [0.2-1.6]
No	29 (14.3)	Ref.
Hypertension			0.06		0.008
Yes	13 (19.7)	2.0 [0.9-4.3]		3.3 [1.3-8.2]
No	21 (10.8)	Ref.
Infection at admission			0.001		0.01
Yes	16 (25)	3.3 [1.5-6.9]		2.8 [1.2-6.6]
No	18 (9.2)	Ref.
Immunosuppression			0.51
Yes	8 (16)	1.3 [0.6-3.1]
No	26 (12.6)	Ref.
Surgery during last 30 days			0.01		0.03
Yes	12 (23.1)	2.5 [1.2-5.6]		2.6 [1.1-6.7]
No	22 (10.5)	Ref.
Having at least one invasive device inserted during last 7 days			<10^-3		0.004
Yes	22 (28.9)	5.9 [2.7-12.6]		3.5 [1.5-8.1]
No	12 (6.5)	Ref
Intensive care unit
Yes	4 (30.8)	3.2 [0.9-11.1]	0.07
No	30 (12.1)

Antibiotic use

The prevalence of antibiotic use was 32.2% (IC 95% [26.3, 37.9], n = 84/261) cases at the survey date. There was a significant difference of antibiotic use by sex (38.8% (n = 45) among males vs. 26.9% (n = 39) among females; p = 0.046). There was no significant association between antibiotic use and age categories (30.7% (n = 59) among]18-65[years vs. 36.2% (n = 25) among patients ≥65 years); and diagnostic category at admission (33.9% (n = 64) for medical patients vs. 28.6% (n = 20) for surgical patients). 35 patients (41.7%) were under one agent, 30 patients (35.7%) were under two agents and 19 patients (22.6%) were under 3 or more agents. In most cases (81.7%, n = 58/71), antibiotic agents were prescribed for a curative indication (see Figure 1).

Figure 1. Distribution of patients under antibiotic according to the type of indication and the number of antibiotics received (n = 71).

Cefotaxime (Claforan^®) (17.6%, 27/153), Amoxicillin/clavulanate (Augmentin^®) (9.1%, 14/153) and Carbapenem (Tienam^®) (8.5%, 13/153) were the most frequently prescribed antibiotic agents.

Case of operated patients

A total of 52 patients (19.9%) had been operated on during the last 30 days before the survey with a mean age of 54.1 (±17.8) years, of which 26 were female (50.0%). ASA score was specified for only 36 patients, of which 55.6% were classified ASA 1, 33.3% ASA 2 and 11.1 % ASA 3. According to the surgical wound classification, 67.3% (n = 33) were class 1 (clean) and 12.2 % (n = 6) were class 4 (dirty-infected).

Among all the operated patients, the use of antibiotic prophylaxis was specified for only 45 patients. Among these patients, 20 (44.4%) have received antibiotic prophylaxis before ongoing the surgery intervention. Half of them (n = 10) have received antibiotic prophylaxis for a duration ≥ 24 H. Monotherapy was prescribed for most of these patients (n = 16/18, 88.9%) and a bitherapy (2 antibiotics) was prescribed for 2 patients (n = 2/18, 11.1%). Results disaggregated by sex are represented in Table 4.

Table 4. Characteristics of operated patients disaggregated by sex (N=52).

Characteristics	Male		Female		TOTAL
Characteristics	Number	Percentage (%)	Number	Percentage (%)	Number (%)
Age categories (years)
18-65	21	60.0	14	40.0	35 (67.3)
≥65	5	29.4	12	70.6	17 (32.7)
Context of the surgery
In emergency	9	60.0	6	40.0	15 (28.8)
Programmed	17	45.9	20	54.1	37 (71.2)
Surgical approach
Laparatomic	12	52.2	11	47.8	23 (50.0)
Laparoscopic	1	25.0	3	75.0	4 (8.7)
Other	9	47.4	10	52.6	19 (41.3)
ASA score
Class 1	7	35.0	13	65.0	20 (55.6)
Class 2	6	50.0	6	50.0	12 (33.3)
Class 3	2	50.0	2	50.0	4 (11.1)
Surgical wound classification
I: Clean	13	39.4	20	60.6	33 (67.3)
II: Clean-Contaminated	2	40.0	3	60.0	5 (10.2)
III: Contaminated	3	60.0	2	40.0	5 (10.2)
IV: Dirty-Infected	6	100.0	0	0.0	6 (12.2)
Post-operative follow-up
Simple	16	43.2	21	56.8	37 (74.0)
Complicated	9	69.2	4	30.8	13 (26.0)
Antibiotic prophylaxis
Yes	10	50.0	10	50.0	20 (44.4)
No	14	56.0	11	44.0	25 (55.6)
HAI
Yes	8	66.7	4	33.3	12 (23.1)
No	18	45.0	22	55.0	40 (76.9)
Number of HAIs per patient (N = 12 patient)
1	7	-	4	-	11 (91.7)
2	1	-	0	-	1 (8.3)
Type of site infections (N = 13 HAIs)
Surgical site	4	-	2	-	6 (46.1)
Pneumonia	3	-	0	-	3 (23.1)
Cardiovascular	1	-	1	-	2 (15.4)
Bacteremia	0	-	1	-	1 (7.7)
Urinary	1	-	0	-	1 (7.7)

The prevalence of HAI among the operated patients was 23.1% (n = 12).

The prevalence of infected operated patients did not differ significantly according to the sex distribution (p = 0.32), to the operating context (urgent or programmed) (20.0% versus 24.3%; p = 0.73), to the surgical approach (p = 0.6, to the ASA score (p = 0.5 and to the use of antibiotic prophylaxis (p = 0.5). Only the surgical wound classification was significantly associated with HAI (p = 0.03).

A total of 13 infection sites were documented. Superficial surgical site infections were the most common (n = 6, 46.1%) (Figure 2).

Figure 2. Distribution of infection sites among infected operated patients (N = 13 HAIs).

A total of 7 microorganisms were isolated among 7 bacteriological samples done (see Table 5).

Table 5. Distribution of isolated microorganisms according to the site of infection among infected operated patients.

Microorganisms	N	Sites of infection
*Acinetobacter*
	1	Surgical site infection
	1	Pneumonia
*P.aeruginosa*
	1	Surgical site infection
	1	Pneumonia
*S. aureus*
*S. aureus*	1	Pneumonia
*Streptocoque*
*Streptocoque*	1	Pneumonia
*Enterococcus Feacalis*
*Enterococcus Feacalis*	1	Cardiovascular infection

Discussion

The control of the infectious risk is considered as an indicator of quality of care. HAIs represent one of the serious healthcare-associated adverse events at health care structures that threaten patient safety.⁹

The principal findings of our point prevalence survey were that approximatively one patient out of eight had at least one active HAI, and one among three patients was under at least one antibiotic agent on the survey day. The most frequently reported site infections were urinary tract infections followed by surgical site infections and pneumonia.

Comparing to other studies conducted in Tunisian hospitals, a similar prevalence was found at Farhat Hachad Hospital in 2012 with a prevalence of HAIs of 12.5%.¹⁰ Lower prevalences of 10.9% and 9.1% was reported in two university hospitals in Sfax in 2017 and 2019, respectively.¹¹^,¹²

Another study carried out in Sahloul Hospital based on data collected from prevalence surveys conducted between 2012 and 2020 revealed a total prevalence of 10.8%.¹³

The higher prevalence found in our study can be explained by the relatively higher number of wards specialized in interventional procedures (2 large general surgery departments, 2 adult intensive care units, a gastroenterology department), which may increase the infectious risk.

Our results were close to those estimated in other studies carried out in low- and intermediate-income countries with an estimated overall HAI prevalence of 15.5%, according to a meta-analysis conducted in 2011.¹ It reached 28% in some Saharan African countries.¹⁴^,¹⁵ Our prevalence was considerably higher compared to developed countries, in particular European countries with a global prevalence of 7.5%.¹⁶

Theses discrepancies may be due to the inexistence of a monitoring system and control of these infections in health structures, especially in developing countries. Such systems ensure the application and the respect of hygiene rules by all health care staff, and the availability of all the necessary materials for hand hygiene. All these conditions are not always available in hospitals in developing countries, which may explain the higher prevalence of HAI in these countries compared to other developed countries.

In our study, independent risk factors identified as associated with increased HAI risk were having hypertension, consuming alcohol, being infected at admission, having at least one invasive device during last 7 days prior to the survey date and undergoing surgery 30 days prior to the study date.

Indeed, hypertension is a predisposing factor to atherosclerosis, which in turn leads to a stimulation of the immune system with its two cellular and humoral components.¹⁷

On the other hand, alcohol causes a secondary immune deficiency by a molecular mechanism, which increases the risk of infections in general and HAIs in particular.¹⁸^,¹⁹

Like our fundings, several studies have shown that a history of surgery during the 30 days prior to admission and recent exposure to invasive medical devices are risk factors for HAIs.¹²^,¹³^,²⁰^,²¹

In general, a special attention should be given to immunocompromised and infected patients who constitute a population with a very high risk of contracting this type of infections.

The most important avoidable risk factor identified in our study was the exposure to invasive devices.

The risk of contracting device-associated HAIs is known as preventable.²² It depends essentially on the degree of respect of hygiene rules, the quality of their daily care and their insertion time before remove. Thus, their indication, their number and their insertion time must be limited as possible.

Implementing evidence-based practices using bundles in infection prevention can improve patient safety and reduce HAIs related to invasive devices.²²^,²³

The most frequently identified sites of infection in our study, were urinary tract infections, pneumonia and superficial surgical site infections. This result joins that found in several other studies in Europe,²⁴^–²⁶ Asia and Africa.⁴ Similarly, a study conducted in Sfax in the two university hospitals, Hedi Chaker and Habib Bourguiba, Tunisia, in 2017¹¹ found similar results.

Escherchia coli and Pseudomonas aeroginosa were the most frequently isolated germs with a frequency of 27.8% respectively for each germ, and in third place Acinetobacter baumannii. These Gram-negative bacteria are the most frequently isolated type according to the literature. In fact, this result is in line with a systematic review study conducted in 2019 that included European, Asian and African studies, which found the same results.⁴ These two types of germs have also been identified in other Tunisian surveys.¹⁰^,¹¹^,²⁷

Gram-negative bacteria have a great capacity of acquisition of genes coding for antibiotic resistance, which may explain their frequent incrimination in HAIs.²⁸

Otherwise, health care workers represent a main component in the transmission process of these infections. The main axis of prevention that can be targeted is improving hand hygiene compliance among health care workers which have been demonstrated being significantly effective in reducing the nosocomial infection risk.²⁹

Providing regular training and reminders using posters at the workplace settings can be very useful. Raising the degree of awareness about the importance of the problem and the necessity of their implication as a principal actor on prevention strategy, is needed to reduce the occurrence of these infections. Continuous availability of alcohol-based hand rubs at point of care is also a very important component to motivate hand hygiene practice.³⁰

The prevalence of antibiotic use, in our study, was alarming. Almost one patient out of three was under antibiotic therapy on the day of the survey and third generation Cephalospoins (Claforan) were the most frequently prescribed antibiotics. This prevalence was comparable to that estimated in some developed countries (overall prevalence of 35%, ranging from 21% in some countries to 55%).²⁴^,³¹ More than half of patients receiving antibiotics were under two or more agents. Rational use of antibiotic combinations and reduction of unnecessary antibiotic prescribing is needed. Creating an antibiotic stewardship program is very important to limit the development of antibiotic resistance in health care facilities.

In the other hand, our survey enabled us to estimate in a simple and inexpensive way the frequency of HAIs and antibiotic use among adult wards at the Chrales Nicolle Hospital.

Point prevalence survey is considered as a useful, rapid, and cost-effective method to quantify the magnitude of HAI problem and target interventions priorities, particularly in hospitals with limited resources.³²^,³³

It was an opportunity to raise awareness and remind health care workers about the importance of the nosocomial infectious risk and to increase their motivation and their adherence to the prevention programs.

Incidence surveys are the gold standard tool used in HAIs surveillance, but they require much more time, resources, and costs. Repeated point prevalence surveys are a good alternative method for measuring HAIs trends over time and to assess the impact of interventions and control programs and actions.³⁴

Controlling HAIs is a long-term process that requires the implication of multidisciplinary staff (clinicians, microbiologists, epidemiologists, hygienists, pharmacists, and administrative agents), and needs a good coordination of their interventions with a clear definition of each one tasks and responsibilities. But it supposes a minimum of local possibilities, in relation to the premises, materials, organization of care and a certain degree of agreement about behaviors and practices.

Conclusions

The prevalence rates of HAIs and antimicrobial use in adult wards at CNH were relatively high. Hospital infection prevention and control measures need to be strengthened to reduce the burden of HAI at the institutional level. Infection control priorities must essentially target urinary tract infections, surgical site infections and pneumonia.

An infection prevention and control committee, as well as the development of an antibiotic stewardship program with continuous monitoring using repeated prevalence surveys, must be implemented to limit the frequency of these infections effectively.

While further research is necessary by estimating the incidence of these infections prospectively over time to understand the principal risk factors and evaluating their real economic impact by estimating the direct cost of HAIs.

Data availability

Underlying data

Harvard Dataverse: Healthcare associated infection-Tunisia, https://doi.org/10.7910/DVN/00BSW9.³⁵

This project contains the following underlying data:

• Dataset-HAI-Adultes-Tunisia.sav (anonymised underlying data collected from 261 included patients)

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).

References

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2. Manoukian S, Stewart S, Dancer S, et al.: Estimating excess length of stay due to healthcare-associated infections: a systematic review and meta-analysis of statistical methodology. J. Hosp. Infect. 2018 Oct 1; 100(2): 222–235. PubMed Abstract | Publisher Full Text
3. Global report on infection prevention and control.[cited 2023 Mar 10]. Reference Source
4. Saleem Z, Godman B, Hassali MA, et al.: Point prevalence surveys of health-care-associated infections: a systematic review. Pathog. Glob. Health. 2019 May 19; 113(4): 191–205. PubMed Abstract | Publisher Full Text | Free Full Text
5. Prévalence des infections nosocomiales dans 27 hôpitaux de la région méditerranéenne/Prevalence of nosocomial infections in 27 hospitals in the Mediterranean region - ProQuest.[cited 2023 Mar 10]. Reference Source
6. Magill SS, Edwards JR, Bamberg W, et al.: Emerging Infections Program Healthcare-Associated Infections and Antimicrobial Use Prevalence Survey Team. Multistate point-prevalence survey of health care-associated infections. N. Engl. J. Med. 2014 Mar 27; 370(13): 1198–1208. PubMed Abstract | Publisher Full Text | Free Full Text
7. Horan TC, Andrus M, Dudeck MA: CDC/NHSN surveillance definition of health care-associated infection and criteria for specific types of infections in the acute care setting. Am. J. Infect. Control. 2008 Jun; 36(5): 309–332. PubMed Abstract | Publisher Full Text
8. Fitz-Henry J: The ASA classification and peri-operative risk. Ann. R .Coll. Surg. Engl. 2011 April; 93(3): 185–187. PubMed Abstract | Publisher Full Text | Free Full Text
9. Haque M, Sartelli M, McKimm J, et al.: Health care-associated infections - an overview. Infect Drug Resist. 2018; 11: 2321–2333. PubMed Abstract | Publisher Full Text | Free Full Text
10. Mahjoub M, Bouafia N, Bannour W, et al.: Healthcare-associated infections in a tunisian university hospital: from analysis to action. Pan Afr. Med. J. 2015 Mar 3; 20: 197. Publisher Full Text
11. Ayed HB, Yaich S, Trigui M, et al.: Prevalence and risk factors of health care-associated infections in a limited resources country: A cross-sectional study. Am. J. Infect. Control. 2019 Aug; 47(8): 945–950. PubMed Abstract | Publisher Full Text
12. Ketata N, Ayed HB, Hmida MB, et al.: Point prevalence survey of health-care associated infections and their risk factors in the tertiary-care referral hospitals of Southern Tunisia. Infect. Dis. Health. 2021 Nov 1; 26(4): 284–291. PubMed Abstract | Publisher Full Text
13. Ghali H, Ben Cheikh A, Bhiri S, et al.: Trends of Healthcare-associated Infections in a Tuinisian University Hospital and Impact of COVID-19 Pandemic. Inquiry. 2021; 58: 469580211067930.
14. Greco D, Magombe I: Hospital acquired infections in a large north Ugandan hospital. J. Prev. Med. Hyg. 2011 Jun; 52(2): 55–58. PubMed Abstract
15. Newman MJ: Nosocomial and community acquired infections in Korle Bu Teaching Hospital, Accra. West Afr. J. Med. 2009; 28(5): 300–303. PubMed Abstract | Publisher Full Text
16. Zarb P, Coignard B, Griskeviciene J, et al.: National Contact Points for the ECDC pilot point prevalence survey, Hospital Contact Points for the ECDC pilot point prevalence survey. The European Centre for Disease Prevention and Control (ECDC) pilot point prevalence survey of healthcare-associated infections and antimicrobial use. Euro Surveill. 2012 Nov 15; 17(46): 20316. Publisher Full Text
17. Hansson GK, Hermansson A: The immune system in atherosclerosis. Nat. Immunol. 2011 Mar; 12(3): 204–212. Publisher Full Text
18. Barr T, Helms C, Grant K, et al.: Opposing effects of alcohol on the immune system. Prog. Neuro-Psychopharmacol. Biol. Psychiatry. 2016 Feb 4; 65: 242–251. PubMed Abstract | Publisher Full Text | Free Full Text
19. Romeo J, Wärnberg J, Nova E, et al.: Moderate alcohol consumption and the immune system: a review. Br. J. Nutr. 2007 Oct; 98 Suppl 1: S111–S115. PubMed Abstract | Publisher Full Text
20. Kakupa DK, Muenze PK, Byl B, et al.: Study of the prevalence of nosocomial infections and associated factors in the two university hospitals of Lubumbashi, Democratic Republic of Congo. Pan. Afr. Med. J. 2016; 24: 275.
21. Cai Y, Venkatachalam I, Tee NW, et al.: Prevalence of Healthcare-Associated Infections and Antimicrobial Use Among Adult Inpatients in Singapore Acute-Care Hospitals: Results From the First National Point Prevalence Survey. Clin. Infect. Dis. 2017 May 15; 64(suppl_2): S61–S67. PubMed Abstract | Publisher Full Text
22. Cardo D, Dennehy PH, Halverson P, et al.: Moving toward elimination of healthcare-associated infections: a call to action. Am. J. Infect. Control. 2010 Nov; 38(9): 671–675. PubMed Abstract | Publisher Full Text
23. Padoveze MC, Nogueira-Jr C, Tanner J, et al.: What are the main drivers for public policies to prevent healthcare-associated infections? J. Hosp. Infect. 2019 Mar; 101(3): 292–294. PubMed Abstract | Publisher Full Text | Free Full Text
24. Gravel D, Taylor G, Ofner M, et al.: Point prevalence survey for healthcare-associated infections within Canadian adult acute-care hospitals. J. Hosp. Infect. 2007 Jul; 66(3): 243–248. PubMed Abstract | Publisher Full Text
25. Sax H, Hugonnet S, Harbarth S, et al.: Variation in nosocomial infection prevalence according to patient care setting:a hospital-wide survey. J. Hosp. Infect. 2001 May; 48(1): 27–32. PubMed Abstract | Publisher Full Text
26. Klavs I, Kolman J, Lejko Zupanc T, et al.: The prevalence of and risk factors for healthcare-associated infections in Slovenia: results of the second national survey. Zdr. Varst. 2016 Dec 1; 55(4): 239–247. PubMed Abstract | Publisher Full Text
27. Ben Salem K, El Mhamdi S, Letaief M, et al.: Epidemiological profile of health-care-associated infections in the central-east area of Tunisia. East Mediterr. Health J. 2011 Jun; 17(6): 485–489. PubMed Abstract | Publisher Full Text
28. Peleg AY, Hooper DC: Hospital-acquired infections due to gram-negative bacteria. N. Engl. J. Med. 2010 May 13; 362(19): 1804–1813. PubMed Abstract | Publisher Full Text | Free Full Text
29. Siegel JD, Rhinehart E, Jackson M, et al.: Health Care Infection Control Practices Advisory Committee. 2007 Guideline for Isolation Precautions: Preventing Transmission of Infectious Agents in Health Care Settings. Am. J. Infect. Control. 2007 Dec; 35(10 Suppl 2): S65–S164. PubMed Abstract | Publisher Full Text | Free Full Text
30. Mathai E, Allegranzi B, Kilpatrick C, et al.: Promoting hand hygiene in healthcare through national/subnational campaigns. J. Hosp. Infect. 2011 Apr; 77(4): 294–298. PubMed Abstract | Publisher Full Text
31. Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals 2011-2012.2013 [cited 2023 Mar 11]. Reference Source
32. Nogueira Junior C, de Mello DS , Padoveze MC, et al.: Characterization of epidemiological surveillance systems for healthcare-associated infections (HAI) in the world and challenges for Brazil. Cad Saude Publica. 2014 Jan; 30(1): 11–20. PubMed Abstract | Publisher Full Text
33. Zingg W, Huttner BD, Sax H, et al.: Assessing the burden of healthcare-associated infections through prevalence studies: what is the best method? Infect. Control Hosp. Epidemiol. 2014 Jun; 35(6): 674–684. PubMed Abstract | Publisher Full Text
34. Carlet J, Tran B, Salomon V, et al.: Surveillance et prévention.2002.
35. Nouira M: Healthcare associated infection-Tunisia. [Dataset]. Harvard Dataverse. 2023; V3. UNF:6:nAPbQYHe/msy1vuClx9sJQ== [fileUNF]. Publisher Full Text

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Author details Author details

¹ Epidemiology and Community medicine department, Charles Nicolle Hospital of Tunis- Faculty of Medicine of Tunis- University Tunis El Manar -Tunisia, Tunis, Tunisia
² Department of General Surgery A, Charles Nicolle Hospital of Tunis- Faculty of Medicine of Tunis- University Tunis El Manar -Tunisia, Tunis, Tunisia

Mariem Nouira
Roles: Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing

Mohamed Maatouk
Roles: Writing – Original Draft Preparation, Writing – Review & Editing

Sarra Ben Youssef
Roles: Data Curation, Investigation, Resources

Samir Ennigrou
Roles: Conceptualization, Data Curation, Methodology, Supervision, Validation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

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Nouira M, Maatouk M, Ben Youssef S and Ennigrou S. Prevalence of health care associated infections and antibiotic use among adult patients: Results of a cross-sectional survey at a tertiary university hospital in Tunisia [version 1; peer review: awaiting peer review]. F1000Research 2023, 12:1132 (https://doi.org/10.12688/f1000research.139631.1)

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[1] 1. Allegranzi B, Bagheri Nejad S, Combescure C, et al.: Burden of endemic health-care-associated infection in developing countries: systematic review and meta-analysis. Lancet. 2011 Jan 15; 377(9761): 228–241. PubMed Abstract | Publisher Full Text

[2] 2. Manoukian S, Stewart S, Dancer S, et al.: Estimating excess length of stay due to healthcare-associated infections: a systematic review and meta-analysis of statistical methodology. J. Hosp. Infect. 2018 Oct 1; 100(2): 222–235. PubMed Abstract | Publisher Full Text

[3] 3. Global report on infection prevention and control.[cited 2023 Mar 10]. Reference Source

[4] 4. Saleem Z, Godman B, Hassali MA, et al.: Point prevalence surveys of health-care-associated infections: a systematic review. Pathog. Glob. Health. 2019 May 19; 113(4): 191–205. PubMed Abstract | Publisher Full Text | Free Full Text

[5] 5. Prévalence des infections nosocomiales dans 27 hôpitaux de la région méditerranéenne/Prevalence of nosocomial infections in 27 hospitals in the Mediterranean region - ProQuest.[cited 2023 Mar 10]. Reference Source

[6] 6. Magill SS, Edwards JR, Bamberg W, et al.: Emerging Infections Program Healthcare-Associated Infections and Antimicrobial Use Prevalence Survey Team. Multistate point-prevalence survey of health care-associated infections. N. Engl. J. Med. 2014 Mar 27; 370(13): 1198–1208. PubMed Abstract | Publisher Full Text | Free Full Text

[7] 7. Horan TC, Andrus M, Dudeck MA: CDC/NHSN surveillance definition of health care-associated infection and criteria for specific types of infections in the acute care setting. Am. J. Infect. Control. 2008 Jun; 36(5): 309–332. PubMed Abstract | Publisher Full Text

[8] 8. Fitz-Henry J: The ASA classification and peri-operative risk. Ann. R .Coll. Surg. Engl. 2011 April; 93(3): 185–187. PubMed Abstract | Publisher Full Text | Free Full Text

[9] 9. Haque M, Sartelli M, McKimm J, et al.: Health care-associated infections - an overview. Infect Drug Resist. 2018; 11: 2321–2333. PubMed Abstract | Publisher Full Text | Free Full Text

[10] 10. Mahjoub M, Bouafia N, Bannour W, et al.: Healthcare-associated infections in a tunisian university hospital: from analysis to action. Pan Afr. Med. J. 2015 Mar 3; 20: 197. Publisher Full Text

[11] 11. Ayed HB, Yaich S, Trigui M, et al.: Prevalence and risk factors of health care-associated infections in a limited resources country: A cross-sectional study. Am. J. Infect. Control. 2019 Aug; 47(8): 945–950. PubMed Abstract | Publisher Full Text

[12] 12. Ketata N, Ayed HB, Hmida MB, et al.: Point prevalence survey of health-care associated infections and their risk factors in the tertiary-care referral hospitals of Southern Tunisia. Infect. Dis. Health. 2021 Nov 1; 26(4): 284–291. PubMed Abstract | Publisher Full Text

[13] 13. Ghali H, Ben Cheikh A, Bhiri S, et al.: Trends of Healthcare-associated Infections in a Tuinisian University Hospital and Impact of COVID-19 Pandemic. Inquiry. 2021; 58: 469580211067930.

[14] 14. Greco D, Magombe I: Hospital acquired infections in a large north Ugandan hospital. J. Prev. Med. Hyg. 2011 Jun; 52(2): 55–58. PubMed Abstract

[15] 15. Newman MJ: Nosocomial and community acquired infections in Korle Bu Teaching Hospital, Accra. West Afr. J. Med. 2009; 28(5): 300–303. PubMed Abstract | Publisher Full Text

[16] 16. Zarb P, Coignard B, Griskeviciene J, et al.: National Contact Points for the ECDC pilot point prevalence survey, Hospital Contact Points for the ECDC pilot point prevalence survey. The European Centre for Disease Prevention and Control (ECDC) pilot point prevalence survey of healthcare-associated infections and antimicrobial use. Euro Surveill. 2012 Nov 15; 17(46): 20316. Publisher Full Text

[17] 17. Hansson GK, Hermansson A: The immune system in atherosclerosis. Nat. Immunol. 2011 Mar; 12(3): 204–212. Publisher Full Text

[18] 18. Barr T, Helms C, Grant K, et al.: Opposing effects of alcohol on the immune system. Prog. Neuro-Psychopharmacol. Biol. Psychiatry. 2016 Feb 4; 65: 242–251. PubMed Abstract | Publisher Full Text | Free Full Text

[19] 19. Romeo J, Wärnberg J, Nova E, et al.: Moderate alcohol consumption and the immune system: a review. Br. J. Nutr. 2007 Oct; 98 Suppl 1: S111–S115. PubMed Abstract | Publisher Full Text

[20] 20. Kakupa DK, Muenze PK, Byl B, et al.: Study of the prevalence of nosocomial infections and associated factors in the two university hospitals of Lubumbashi, Democratic Republic of Congo. Pan. Afr. Med. J. 2016; 24: 275.

[21] 21. Cai Y, Venkatachalam I, Tee NW, et al.: Prevalence of Healthcare-Associated Infections and Antimicrobial Use Among Adult Inpatients in Singapore Acute-Care Hospitals: Results From the First National Point Prevalence Survey. Clin. Infect. Dis. 2017 May 15; 64(suppl_2): S61–S67. PubMed Abstract | Publisher Full Text

[22] 22. Cardo D, Dennehy PH, Halverson P, et al.: Moving toward elimination of healthcare-associated infections: a call to action. Am. J. Infect. Control. 2010 Nov; 38(9): 671–675. PubMed Abstract | Publisher Full Text

[23] 23. Padoveze MC, Nogueira-Jr C, Tanner J, et al.: What are the main drivers for public policies to prevent healthcare-associated infections? J. Hosp. Infect. 2019 Mar; 101(3): 292–294. PubMed Abstract | Publisher Full Text | Free Full Text

[24] 24. Gravel D, Taylor G, Ofner M, et al.: Point prevalence survey for healthcare-associated infections within Canadian adult acute-care hospitals. J. Hosp. Infect. 2007 Jul; 66(3): 243–248. PubMed Abstract | Publisher Full Text

[25] 25. Sax H, Hugonnet S, Harbarth S, et al.: Variation in nosocomial infection prevalence according to patient care setting:a hospital-wide survey. J. Hosp. Infect. 2001 May; 48(1): 27–32. PubMed Abstract | Publisher Full Text

[26] 26. Klavs I, Kolman J, Lejko Zupanc T, et al.: The prevalence of and risk factors for healthcare-associated infections in Slovenia: results of the second national survey. Zdr. Varst. 2016 Dec 1; 55(4): 239–247. PubMed Abstract | Publisher Full Text

[27] 27. Ben Salem K, El Mhamdi S, Letaief M, et al.: Epidemiological profile of health-care-associated infections in the central-east area of Tunisia. East Mediterr. Health J. 2011 Jun; 17(6): 485–489. PubMed Abstract | Publisher Full Text

[28] 28. Peleg AY, Hooper DC: Hospital-acquired infections due to gram-negative bacteria. N. Engl. J. Med. 2010 May 13; 362(19): 1804–1813. PubMed Abstract | Publisher Full Text | Free Full Text

[29] 29. Siegel JD, Rhinehart E, Jackson M, et al.: Health Care Infection Control Practices Advisory Committee. 2007 Guideline for Isolation Precautions: Preventing Transmission of Infectious Agents in Health Care Settings. Am. J. Infect. Control. 2007 Dec; 35(10 Suppl 2): S65–S164. PubMed Abstract | Publisher Full Text | Free Full Text

[30] 30. Mathai E, Allegranzi B, Kilpatrick C, et al.: Promoting hand hygiene in healthcare through national/subnational campaigns. J. Hosp. Infect. 2011 Apr; 77(4): 294–298. PubMed Abstract | Publisher Full Text

[31] 31. Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals 2011-2012.2013 [cited 2023 Mar 11]. Reference Source

[32] 32. Nogueira Junior C, de Mello DS , Padoveze MC, et al.: Characterization of epidemiological surveillance systems for healthcare-associated infections (HAI) in the world and challenges for Brazil. Cad Saude Publica. 2014 Jan; 30(1): 11–20. PubMed Abstract | Publisher Full Text

[33] 33. Zingg W, Huttner BD, Sax H, et al.: Assessing the burden of healthcare-associated infections through prevalence studies: what is the best method? Infect. Control Hosp. Epidemiol. 2014 Jun; 35(6): 674–684. PubMed Abstract | Publisher Full Text

[34] 34. Carlet J, Tran B, Salomon V, et al.: Surveillance et prévention.2002.

[35] 35. Nouira M: Healthcare associated infection-Tunisia. [Dataset]. Harvard Dataverse. 2023; V3. UNF:6:nAPbQYHe/msy1vuClx9sJQ== [fileUNF]. Publisher Full Text

Prevalence of health care associated infections and antibiotic use among adult patients: Results of a cross-sectional survey at a tertiary university hospital in Tunisia

Abstract

Keywords

Introduction

Methods

Study design and settings

Inclusion criteria and case definitions (study population)

Data collection

Study process

Statistical analysis

Ethical considerations

Results

Patients’ characteristics

Table 1. Patients’ baseline characteristics (N = 261).

HAI prevalence

Table 2. Baseline characteristics of infected patients disaggregated by sex (N = 34).

HAI risk factors

Table 3. Univariate and multivariate analysis results of associated risk factors for HAIs.

Antibiotic use

Figure 1. Distribution of patients under antibiotic according to the type of indication and the number of antibiotics received (n = 71).

Case of operated patients

Table 4. Characteristics of operated patients disaggregated by sex (N=52).

Figure 2. Distribution of infection sites among infected operated patients (N = 13 HAIs).

Table 5. Distribution of isolated microorganisms according to the site of infection among infected operated patients.

Discussion

Conclusions

Data availability

Underlying data

References

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