981 resultados para Laestadius, Lars Levi: Saarnat. 1-3


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Background: Nursing home short stays (NHSS) in the canton of Vaud have been introduced for respite care purpose. However, a growing number of older patients are urgently admitted from home (within 24h) or directly after hospital discharge (58% of all admissions in 2010). NHSS appears therefore as an increasingly important component of the health care system, but the characteristics of admitted patients have not been previously described. A better knowledge would contribute to identify specific care needs and enhance their care. Objectives: 1) To describe the characteristics of patients admitted in unplanned NHSS ( after hospital stay or urgently from home); 2) To determine living disposition 3-month after NHSS discharge. Method: Over a 18-month period, elderly patients with unplanned NHSS admission to 2 facilities in Lausanne were identified. Demographic, social, health, and functional data, as well as main reason for admission were collected. Death and place of living at 3-months were collected using the administrative database. Results: Overall, 114 patients (mean age 83.1 ± 6.2 years, 77% women, 84% living alone) were assessed, 80% being admitted from hospital. Mean score in Lawton's instrumental ADL before NHSS admission was 4.6 ± 2.5 and 69% of the patients were home care recipients (median number of weekly visits: 5 ± 3). Patients reported going out 4.2 ± 1.3 times/week and 56% reported at least one fall over the past year. Among the 91 patients coming from the hospital, main reason for admission was injury/limb immobilization (58%), recuperation (13%) and functional impairment in basic ADL (10%). Mean score at Katz's Basic ADL at admission was 3.7 ± 1.9. Overall, 90% of patients were identified with gait and balance impairment, 78% with cognitive impairment and 70% with polypharmacy (>6 different drugs). At 3-month after NHSS discharge (N = 92), 72% patients were living at home, 16% had been admitted to long term care, and 6% died. Among patients living at home at follow-up, 11% had been readmitted to hospital during the follow-up period. Conclusion: Older patients with unplanned NHSS admission show a high prevalence of functional, mobility, and cognitive impairments, as well as other geriatric syndromes. Specific measures should be considered during these stays to prevent further functional decline and, possibly, hospital readmission. Patients admitted with basic ADLs impairment might be candidate for higher levels of care (rehabilitation).

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Engagements des 26 septembre 1863, 29 janvier 1865 et 31 mars 1868

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Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method. METHODS: This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression. RESULTS: The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced. CONCLUSION: This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.

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BACKGROUND: Minor protease inhibitor (PI) mutations often exist as polymorphisms in HIV-1 sequences from treatment-naïve patients. Previous studies showed that their presence impairs the antiretroviral treatment (ART) response. Evaluating these findings in a larger cohort is essential. METHODS: To study the impact of minor PI mutations on time to viral suppression and time to virological failure, we included patients from the Swiss HIV Cohort Study infected with HIV-1 subtype B who started first-line ART with a PI and two nucleoside reverse transcriptase inhibitors. Cox regression models were performed to compare the outcomes among patients with 0 and ≥ 1 minor PI mutation. Models were adjusted for baseline HIV-1 RNA, CD4 cell count, sex, transmission category, age, ethnicity, year of ART start, the presence of nucleoside reverse transcriptase inhibitor mutations, and stratified for the administered PIs. RESULTS: We included 1199 patients of whom 944 (78.7%) received a boosted PI. Minor PI mutations associated with the administered PI were common: 41.7%, 16.1%, 4.7% and 1.9% had 1, 2, 3 or ≥ 4 mutations, respectively. The time to viral suppression was similar between patients with 0 (reference) and ≥ 1 minor PI mutation (multivariable hazard ratio (HR): 1.1 [95% confidence interval (CI): 1.0-1.3], P = .196). The time to virological failure was also similar (multivariable HR:.9 [95% CI:.5-1.6], P = .765). In addition, the impact of each single minor PI mutation was analyzed separately: none was significantly associated with the treatment outcome. CONCLUSIONS: The presence of minor PI mutations at baseline has no effect on the therapy outcome in HIV infected individuals.