Rate of the incidence of hospital-acquired infections in Iran based on the data of the national nosocomial infections surveillance

Hospital-acquired infections (HAIs) lead to increased length of hospital stay, inappropriate use of broad-spectrum antibiotics and multiple antibiotic resistance. This study aimed to investigate the rate of HAIs in Iran. In this multi-centre study, the rate of HAIs was calculated based on the data collected through Iranian nosocomial infections surveillance for patients with HAIs, as well as through hospital statistics and information systems on hospital-related variables. Data were analysed using Stata software; in addition, ArcGIS was used for plotting the geographical distribution of HAIs by different provinces. The mean age of the 107 669 patients affected by HAIs was 52 ± 26.71 years. Just over half (51.55%) of the patients were male. The overall rate of HAIs was 26.57 per 1000 patients and 7.41 per 1000 patient-days. The most common HAIs were urinary tract infections (26.83%; 1.99 per 1000 patient-days), ventilator-associated events (20.28%; 1.5 per 1000 patient-days), surgical-site infections (19.73%; 1.45 per 1000 patient-days) and bloodstream infections (13.51%; 1 per 1000 patient-days), respectively. The highest rate of HAIs was observed in intensive care units. Device, catheter and ventilator-associated infections accounted for 38.72%, 18.79% and 16% of all HAIs, respectively. Based on the results, HAIs are common in intensive care units, and urinary tract infections and device-related infections are more prevalent in Iran. To reduce HAIs it is recommended to implement appropriate policies and interventions, train staff about the use of devices, and prepare and update protocols and guidelines for improving the quality of care.

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The overall rate of HAIs was 26.57 per 1000 patients and 7.41 per 1000 patient-days.

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Hospital-acquired infections are common in ICU wards, while UTIs and device-related infections are more prevalent in Iran.

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Device, catheter and ventilator-associated infections accounted for 38.72, 18.79%, and 16% of all HAIs, respectively.

Serogroups, and drug resistance of nontyphoidal Salmonella in symptomatic patients with community-acquired diarrhea and chicken meat samples in Tehran

BACKGROUND

Salmonella is considered as a main cause of community-acquired diarrhea in humans, however, sources of the multi-drug resistant (MDR) strains and their link with the disease are not well known.

AIMS

This study aimed to investigate the frequency, serogroup diversity, and antimicrobial susceptibility patterns of Salmonella strains in poultry meat and stool samples of patients with community acquired diarrhea in Tehran.

METHODS

We compared the frequency of non-typhoidal Salmonella serogroups, the similarities of their resistance patterns to 10 antimicrobial compounds, the prevalence of extended spectrum β-lactamase (ESBL) and ampicillinase C (AmpC) genetic determinants, and class 1 and 2 integrons in 100 chicken meat and 400 stool samples of symptomatic patients in Tehran during June 2018 to March 2019.

RESULTS

Salmonella was isolated from 75% and 5.5% of the chicken meats and human stool samples, respectively. The chicken meat isolates mainly belonged to serogroup C (88%, 66/75), while the human stool isolates were mainly related to serogroup D (59.1%, 13/22). The MDR phenotype and the most common rates of resistance to antibiotics, including tetracycline, trimethoprim/sulfamethoxazole (TS) and azithromycin, were detected in 4.5% and 45.3%, 59% and 13.6%, 43% and 9.1%, 42% and 9.1% of the human stool and chicken meat samples, respectively. Carriage of bla _CTX, bla _SHV, and bla _PER genes in the meat isolate with ESBL resistance phenotype and bla _ACC, bla _FOX, and bla _CMY-2 among the 7 meat strains with AmpC resistance phenotype was not confirmed using polymerase chain reaction (PCR). High prevalence of class 1 and 2 integrons was characterized and showed a correlation with resistance to TS and chloramphenicol.

CONCLUSION

These findings showed a lack of association between chicken meats and human isolates due to discrepancy between the characterized serogroups and resistance phenotypes.

Decomposition of inequity determinants of healthcare utilization, Iran

OBJECTIVE

To investigate and decompose the determinants of healthcare utilization in a central province in Iran.

STUDY SETTING

Data from 2711 individuals were gathered through interview in a cross-sectional study in Markazi province, Iran, as part of the Healthcare Utilization Survey in 2008.

METHODS

The household economic index (HEI) was created using principal component analysis, and data were analyzed according to the type of healthcare utilization. In addition, the generalized estimation equation model was used to identify the determinants, and the concentration index was calculated and decomposed based on the healthcare utilization determinants.

RESULTS

HEI was a fixed determinant for all three types of healthcare utilization (general physician, specialist and health worker); however, other determinants changed with the type of health care. The greatest contributors to inequity in the use of general physician, specialist and health worker care were HEI quintile (41.4%), housewife/retired (32.8%) and living in an urban area (47%), respectively. The concentration index was highest for specialist care and lowest for health worker care.

CONCLUSION

The pattern of utilization differed between the types of health care. Nevertheless, inequity in healthcare utilization is related to government health policies, including the role of the system in reducing inequity by application of policies such as the family physician and rural insurance programme; and factors which are beyond the health system authorities, and are related to population living standards and need intersectoral cooperation.

Estimating the proportion of diabetes to the attributable burden of cardiovascular diseases in iran

BACKGROUND

This study aimed at estimating the proportion of diabetes as a risk factor to the attributable burden of cardiovascular diseases in Iran.

METHODS

Comparative Risk Assessment methodology was used to calculating Potential Impact Fraction (PIF). To calculate PIF, data on the prevalence of newly diagnosed diabetes mellitus (NDM) and known diabetes mellitus (KDM) were obtained from 3rd Iranian surveillance of risk factors of non-communicable diseases and data on corresponding measures of effect were derived from a cohort study. PIF were estimated on both theoretical minimum and feasible minimum risk. Uncertainty for the attributable burden was estimated by Monte Carlo simulation-modeling techniques incorporating sources of uncertainty.

RESULTS

According to multivariate-adjusted hazard ratios, by reducing the prevalence of Iranian women with diabetes from 10.05 percent to the feasible minimum risk level i.e. 5 percent, 6.8% (95% uncertainty intervals: 3.5-9.8) of attributable Disability Adjusted Life Years (DALYs) to CVD are avoidable and the corresponding value for men were 3.1% (95% uncertainty intervals: 1.4-4.8).

CONCLUSION

Although data on the prevalence of diabetes and corresponding measures of associations were obtained from an updated and country-specific source, but to better priority setting, PIF should be applied to updated and revised burden of CVDs.

Model of cholera dissemination using geographic information systems and fuzzy clustering means: case study, Chabahar, Iran

OBJECTIVES

Cholera is spread by drinking water or eating food that is contaminated by bacteria, and is related to climate changes. Several epidemics have occurred in Iran, the most recent of which was in 2005 with 1133 cases and 12 deaths. This study investigated the incidence of cholera over a 10-year period in Chabahar district, a region with one of the highest incidence rates of cholera in Iran.

STUDY DESIGN

Descriptive retrospective study on data of patients with Eltor and NAG cholera reported to the Iranian Centre of Disease Control between 1997 and 2006.

METHODS

Data on the prevalence of cholera were gathered through a surveillance system, and a spatial database was developed using geographic information systems (GIS) to describe the relation of spatial and climate variables to cholera incidences. Fuzzy clustering (fuzzy C) method and statistical analysis based on logistic regression were used to develop a model of cholera dissemination. The variables were demographic characteristics, specifications of cholera infection, climate conditions and some geographical parameters.

RESULTS

The incidence of cholera was found to be significantly related to higher temperature and humidity, lower precipitation, shorter distance to the eastern border of Iran and local health centres, and longer distance to the district health centre. The fuzzy C means algorithm showed that clusters were geographically distributed in distinct regions.

CONCLUSION

In order to plan, manage and monitor any public health programme, GIS provide ideal platforms for the convergence of disease-specific information, analysis and computation of new data for statistical analysis.

Accuracy of ultrasound, clinical and maternal estimates of birth weight in term women

Accurate prenatal estimation of birth weight is useful in the management of labour and delivery. This study compared the accuracy of ultrasound, clinical and maternal estimates of fetal weight in 246 parous women with singleton, term pregnancies admitted for scheduled caesarean section. The sensitivity and specificity of predicting birth weight by ultrasound measures were 12.6% and 92.1%, by clinical palpation were 11.8% and 99.6% and by maternal estimate were 6.3% and 98.0% respectively. Clinicians' estimates of birth weight in term pregnancy were as accurate as routine ultrasound estimation in the week before delivery. Parous women's estimates of birth weight were more accurate than either clinical or ultrasound estimation.