Measuring quality of life after intensive care using the Arabic version for Morocco of the EuroQol 5 Dimensions

<p>Abstract</p> <p>Background</p> <p>Health-related quality of life (HRQL) is a relevant outcome measures in intensive care unit (ICU). The aim of this study was to evaluate HRQL of ICU patients 3 months after discharge using the Arabic version for Morocco of the EuroQol-5-Dimension (EQ-5D), and to examine the psychometric properties of the questionnaire.</p> <p>Results</p> <p>The Arabic version for Morocco of the EQ-5D was approved by the EuroQol group. A prospective cohort study was conducted after medical ICU discharge. At 3-month follow up, the EQ-5D (self classifier and EQ-VAS) was administered in consultation or by telephone. EQ-VAS varies from 0 (better HRQL) to 100 (worst HRQL). An unweighted scoring for EQ5D-index was calculated. EQ5D-index ranges from -0.59 to 1. Test-retest reliability of the EQ-5D was tested using Kappa coefficient and intraclass correlation coefficient (ICC). Criterion validity was assessed by correlating EQ-VAS and EQ5D-index with the Short Form 36 (SF-36). Construct validity was tested using simple and multiple liner regression to assess factors influencing patients'HRQL. 145 survivors answered the EQ-5D. Median EQ5D-index was 0.52 [0.20-1]. Mean EQ-VAS was 62 ± 20. Test-retest reliability was conducted in 83 patients. ICCs of EQ5D-index and EQ-VAS were 0.95 and 0.92 respectively. For EQ-5D self classifier, agreement by kappa was above 0.40. Significant correlations were noted between EQ5D-index, EQ-VAS and SF-36 (<it>p </it>< 0.001). In multivariate analysis, factors associated with poorer HRQL for EQ5D-index were longer ICU length of stay (β = -0.01; <it>p </it>= 0.017) and higher educational level (β = -0.2; <it>p </it>= 0.001). For EQ-VAS men were associated with better HRQL (β = 6.5; <it>p </it>= 0.048).</p> <p>Conclusions</p> <p>The Arabic version for Morocco of the EQ-5D is reliable and valid. Women, high educational level and longer ICU length of stay were associated with poorer HRQL.</p

Prevalence of hospital-acquired infections in the university medical center of Rabat, Morocco

<p>Abstract</p> <p>Background</p> <p>The aims of this study were to determine the hospital-acquired infections (HAI) prevalence in all institutions of Rabat University Medical Center, to ascertain risk factors, to describe the pathogens associated with HAI and their susceptibility profile to antibiotics.</p> <p>Materials and methods</p> <p>Point-prevalence survey in January 2010 concerning all patients who had been in the hospital for at least 48 hours. At bedside, 27 investigators filled a standardized questionnaire from medical records, temperature charts, radiographs, laboratory reports and by consultation with the ward’s collaborating health professionals. Risk factors were determined using logistic regression.</p> <p>Results</p> <p>1195 patients involved, occupancy rate was 51%. The prevalence of HAI was 10.3%. Intensive care units were the most affected wards (34.5%). Urinary tract infection was the most common infected site (35%). Microbiological documentation was available in 61% of HAI. <it>Staphylococcus</it> was the organism most commonly isolated (18.7%) and was methicillin-resistant in 50% of cases. In multivariate analysis, risk factors associated with HAI were advanced age, longer length of hospital stay, presence of comorbidity, invasive devices and use of antibiotic use.</p> <p>Conclusion</p> <p>HAI prevalence was high in this study. Future prevention program should focus on patients with longer length of stay, invasive devices, and overprescribing antibiotics.</p

Trend analysis of leprosy in Morocco between 2000 and 2017: Evidence on the single dose rifampicin chemoprophylaxis.

BACKGROUND:Morocco has achieved the goal of leprosy elimination as a public health problem several years ago (less than 1 case/ 10 000 habitant). The aim of this study was to analyze trends of leprosy detection during the last 17 years taking into consideration the implementation of single dose rifampicin chemoprophylaxis (SDRC) started in 2012. METHODOLOGY:Time series of leprosy cases detected at national level between 2000 and 2017. Variable collected for each year were leprosy per 100000 H, age category, gender, origin, regions, grade of disabilities and clinical forms. The detection time series was assessed by Joinpoint Regression Analysis. Annual percentage changes (APCs) were estimated to identify the years (joinpoint) when significant changes occurred in the trend. We therefore examined trends in leprosy detection according to epidemiological variables. FINDINGS:Joinpoint regression showed a reduction in the detection rate between 2000 and 2017. The APC for the period 2012-2017 (-16.83, 95% CI: -29.2 to -2.3, p <0.05) was more pronounced than that of the previous period 2000-2012 (- 4.68, 95% CI: -7.3 to -2.0, p <0.05); with a significant break in the same joinpoint year SDRC implementation. In stratified analysis, case detection decreased, but not significantly, after the joinpoint years in men, children, multi-bacillary cases, grade 0-1 disabilities, rural and urban cases and in ten regions. CONCLUSIONS:Leprosy detection was declining over years with a significant reduction by 16% per year from 2012 to 2017. SDRC may reduce leprosy detection over the years following its administration

Eosinophil cell count and C-reactive protein level for discrimination of systemic inflammatory response syndrome and infection

Receiver operating characteristic (ROC) curve of eosinophil cell count and C-reactive protein (CRP) level for the discrimination of systemic inflammatory response syndrome patients and infected patients (sepsis + severe sepsis + septic shock). Areas under the ROC curves were 0.84 (95% confidence interval, 0.74 to 0.94) for eosinophils and 0.77 (95% confidence interval, 0.67 to 0.87) for CRP. Comparison of the areas under ROC curves between eosinophils and CRP, = 0.175.<p><b>Copyright information:</b></p><p>Taken from "Eosinopenia is a reliable marker of sepsis on admission to medical intensive care units"</p><p>http://ccforum.com/content/12/2/R59</p><p>Critical Care 2008;12(2):R59-R59.</p><p>Published online 24 Apr 2008</p><p>PMCID:PMC2447615.</p><p></p

Eosinophil cell count and C-reactive protein level in the different diagnostic groups

Box plot of eosinophil cell count and C-reactive protein (CRP) level in the different diagnostic groups. SIRS, systemic inflammatory response syndrome. Central line, median; boxes, 25th to 75th percentiles; whiskers, 95% confidence intervals.<p><b>Copyright information:</b></p><p>Taken from "Eosinopenia is a reliable marker of sepsis on admission to medical intensive care units"</p><p>http://ccforum.com/content/12/2/R59</p><p>Critical Care 2008;12(2):R59-R59.</p><p>Published online 24 Apr 2008</p><p>PMCID:PMC2447615.</p><p></p

Eosinophil cell count and C-reactive protein level for comparison of systemic inflammatory response syndrome and infection ( 0

001). Box plot of eosinophil count and C-reactive protein (CRP) level for comparisons between the systemic inflammatory response syndrome (SIRS) group and the infected group (sepsis + severe sepsis + septic shock). Central line, median; boxes, 25th to 75th percentiles; whiskers, 95% confidence intervals.< 0.001 between eosinophils and CRP groups.<p><b>Copyright information:</b></p><p>Taken from "Eosinopenia is a reliable marker of sepsis on admission to medical intensive care units"</p><p>http://ccforum.com/content/12/2/R59</p><p>Critical Care 2008;12(2):R59-R59.</p><p>Published online 24 Apr 2008</p><p>PMCID:PMC2447615.</p><p></p