21 resultados para Quantifiable measures


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Multi-resistant gram-negative rods are important pathogens in intensive care units (ICU), cause high rates of mortality, and need infection control measures to avoid spread to another patients. This study was undertaken prospectively with all of the patients hospitalized at ICU, Anesthesiology of the Hospital São Paulo, using the ICU component of the National Nosocomial Infection Surveillance System (NNIS) methodology, between March 1, 1997 and June 30, 1998. Hospital infections occurring during the first three months after the establishment of prevention and control measures (3/1/97 to 5/31/97) were compared to those of the last three months (3/1/98 to 5/31/98). In this period, 933 NNIS patients were studied, with 139 during the first period and 211 in the second period. The overall rates of infection by multi-resistant microorganisms in the first and second periods were, respectively, urinary tract infection: 3.28/1000 patients/day; 2.5/1000 patients/day; pneumonia: 2.10/1000 patients/day; 5.0/1000 patients/day; bloodstream infection: 1.09/1000 patients/day; 2.5/1000 patients/day. A comparison between overall infection rates of both periods (Wilcoxon test) showed no statistical significance (p = 0.067). The use of intervention measures effectively decreased the hospital bloodstream infection rate (p < 0.001), which shows that control measures in ICU can contribute to preventing hospital infections.

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To evaluate ultrasonographic (US) cross-sectional areas (CSAs) of peripheral nerves, indexes of the differences between CSAs at the same point (∆CSAs) and between tunnel (T) and pre-tunnel (PT) ulnar CSAs (∆TPTs) in leprosy patients (LPs) and healthy volunteers (HVs). Seventy-seven LPs and 49 HVs underwent bilateral US at PT and T ulnar points, as well as along the median (M) and common fibular (CF) nerves, to calculate the CSAs, ∆CSAs and ∆TPTs. The CSA values in HVs were lower than those in LPs (p < 0.0001) at the PT (5.67/9.78 mm2) and T (6.50/10.94 mm2) points, as well as at the M (5.85/8.48 mm2) and CF (8.17/14.14 mm2) nerves. The optimum CSA- receiver operating characteristic (ROC) points and sensitivities/specificities were, respectively, 6.85 mm2 and 68-85% for the PT point, 7.35 mm2 and 71-78% for the T point, 6.75 mm2 and 62-75% for the M nerve and 9.55 mm2 and 81-72% for the CF nerve. The ∆CSAs of the LPs were greater than those of the HVs at the PT point (4.02/0.85; p = 0.007), T point (3.71/0.98; p = 0.0005) and CF nerve (2.93/1.14; p = 0.015), with no difference found for the M nerve (1.41/0.95; p = 0.17). The optimum ∆CSA-ROC points, sensitivities, specificities and p-values were, respectively, 1.35, 49%, 80% and 0.003 at the PT point, 1.55, 55-85% and 0.0006 at the T point, 0.70, 58-50% and 0.73 for the M nerve and 1.25, 54-67% and 0.022 for the CF nerve. The ∆TPT in the LPs was greater than that in the HVs (4.43/1.44; p <0.0001). The optimum ∆TPT-ROC point was 2.65 (90% sensitivity/41% specificity, p < 0.0001). The ROC analysis of CSAs showed the highest specificity and sensitivity at the PT point and CF nerve, respectively. The PT and T ∆CSAs had high specificities (> 80%) and ∆TPT had the highest specificity (> 90%). New sonographic peripheral nerve measurements (∆CSAs and ∆TPT) provide an important methodological improvement in the detection of leprosy neuropathy.

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AbstractOBJECTIVEEvaluate pre- and intraoperative practices adopted by medical and nursing teams for the prevention of surgical infections.METHODA prospective study carried out in the period of April to May 2013, in a surgical center of a university hospital in Belo Horizonte, Minas Gerais.RESULTS18 surgeries were followed and 214 surgical gloves were analyzed, of which 23 (10.7%) had postoperative glove perforation detected, with 52.2% being perceived by users. Hair removal was performed on 27.7% of patients in the operating room, with the use of blades in 80% of the cases. Antibiotic prophylaxis was administered to 81.8% of patients up to 60 minutes prior to surgical incision. An average of nine professionals were present during surgery and the surgery room door remained open in 94.4% of the procedures.CONCLUSIONPartial adhesion to the recommended measures was identified, reaffirming a need for greater attention to these critical steps/actions in order to prevent surgical site infection.

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This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

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Angiotensin-converting enzyme (ACE) activity and polymorphism contribute significantly to the prognosis of patients with cardiomyopathy. The aim of this study was to determine the activity and type of ACE polymorphism in patients with familial and nonfamilial hypertrophic cardiomyopathy (HCM) and to correlate these with echocardiographic measurements (echo-Doppler). We studied 136 patients (76 males) with HCM (69 familial and 67 nonfamilial cases). Mean age was 41 ± 17 years. DNA was extracted from blood samples for the polymerase chain reaction and the determination of plasma ACE levels. Left ventricular mass, interventricular septum, and wall thickness were measured. Mean left ventricular mass index, interventricular septum and wall thickness in familial and nonfamilial forms were 154 ± 63 and 174 ± 57 g/m² (P = 0.008), 19 ± 5 and 21 ± 5 mm (P = 0.02), and 10 ± 2 and 12 ± 3 mm (P = 0.0001), respectively. ACE genotype frequencies were DD = 35%, ID = 52%, and II = 13%. A positive association was observed between serum ACE activity and left ventricular mass index (P = 0.04). Logistic regression showed that ACE activity was twice as high in patients with familial HCM and left ventricular mass index ≥190 g/m² compared with the nonfamilial form (P = 0.02). No other correlation was observed between ACE polymorphisms and the degree of myocardial hypertrophy. In conclusion, ACE activity, but not ACE polymorphisms, was associated with the degree of myocardial hypertrophy in the patients with HCM.

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The objectives of the present study were to describe and compare the body composition variables determined by bioelectrical impedance (BIA) and the deuterium dilution method (DDM), to identify possible correlations and agreement between the two methods, and to construct a linear regression model including anthropometric measures. Obese adolescents were evaluated by anthropometric measures, and body composition was assessed by BIA and DDM. Forty obese adolescents were included in the study. Comparison of the mean values for the following variables: fat body mass (FM; kg), fat-free mass (FFM; kg), and total body water (TBW; %) determined by DDM and by BIA revealed significant differences. BIA overestimated FFM and TBW and underestimated FM. When compared with data provided by DDM, the BIA data presented a significant correlation with FFM (r = 0.89; P < 0.001), FM (r = 0.93; P < 0.001) and TBW (r = 0.62; P < 0.001). The Bland-Altman plot showed no agreement for FFM, FM or TBW between data provided by BIA and DDM. The linear regression models proposed in our study with respect to FFM, FM, and TBW were well adjusted. FFM obtained by DDM = 0.842 x FFM obtained by BIA. FM obtained by DDM = 0.855 x FM obtained by BIA + 0.152 x weight (kg). TBW obtained by DDM = 0.813 x TBW obtained by BIA. The body composition results of obese adolescents determined by DDM can be predicted by using the measures provided by BIA through a regression equation.