| Literature DB >> 25885318 |
Gianluigi Zaza1, Carlo Rugiu2, Alessandra Trubian3, Simona Granata4, Albino Poli5, Antonio Lupo6.
Abstract
BACKGROUND: The last decade has witnessed considerable improvement in dialysis technology and changes in clinical management of patients in peritoneal dialysis (PD) with a significant impact on long term clinical outcomes. However, the identification of factors involved in this process is still not complete.Entities:
Mesh:
Year: 2015 PMID: 25885318 PMCID: PMC4404116 DOI: 10.1186/s12882-015-0051-3
Source DB: PubMed Journal: BMC Nephrol ISSN: 1471-2369 Impact factor: 2.388
Trends in demographic and clinical characteristics among the three study periods
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| 29.3 (25.1) | 36.6 (27.4) | 33.7 (26.9) |
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| 63.5 (9.0) | 59.7 (12.7) | 59.0 (12.0) |
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| Males n. (%) | 36 (58.1) | 46 (69.7) | 94 (71.2) |
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| Females n. (%) | 26 (41.9) | 20 (30.3) | 38 (28.8) | |
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| No smokers n. (%) | 51 (82.2) | 39 (59.1) | 77 (58.3) |
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| Ex smokers n. (%) | 7 (11.3) | 11 (16.7) | 38 (28.8) | |
| Smokers n. (%) | 4 (6.5) | 16 (24.2) | 17 (12.9) | |
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| No diabetes n. (%) | 44 (71.0) | 52 (78.8) | 102 (77.3) |
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| Diabetes n. (%) | 18 (29.0) | 14 (21.2) | 30 (22.7) | |
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| 777.8 (560.0) | 924.2 (460.4) | 997.7 (469.2) |
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| 159.6 (25.2) | 154.0 (19.9) | 140.5 (15.4) |
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| 3.4 (0.49) | 3.2 (0.5) | 3.9 (2.8) |
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| 8.7 (1.5) | 9.6 (7.5) | 11.7 (1.36) |
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| 6.1 (1.9) | 6.4 (2.4) | 6.9 (2.6) |
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eGFR: estimated Glomerular Filtration Rate. (*) At the start of PD treatment.
Figure 1Patients’ distribution according to peritoneal dialysis (PD) modalities and percentage of patients on the waiting list for renal transplantation in the three study periods. The histograms represent (A) the percentage of patients on CAPD: Continuous Ambulatory Peritoneal Dialysis or APD: automated peritoneal dialysis and (B) the percentage of PD patients on the waiting list for renal transplantation in the three study groups. Group A: 1983–1992; Group B: 1993–2002; Group C: 2003–2012. P values calculated by fisher exact test.
Figure 2Multivariate Cox proportional hazard model for mortality according to several demographic and clinical characteristics. In this model are indicated Hazard ratio (HR) and 95% Coefficient interval (CI) for each factor analyzed. CVD: cardiovascular disease.
Figure 3Survival rate in the three study groups by Kaplan-Meier. Survival rate of patients in the three study groups (Group A: 1983–1992, Group B: 1993–2002 and Group C: 2003–2012). Survival rate was better in Group C compared to the other two groups.
Figure 4Incidence rate ratio of acute myocardial infarction (A), cerebrovascular disease (B) and vasculopathy (C) according to the three study groups. Group A: 1983–1992; Group B: 1993–2002; Group C: 2003–2012. Figure has been built on the basis of Cox analysis.
Figure 5Days of hospitalization in the three study periods. The histograms represent the mean ± SD of the days of hospitalization for all causes (white bars) and peritonitis (gray bars) in each study group. Group A: 1983–1992; Group B: 1993–2002; Group C: 2003–2012.
Frequency of occurrence of peritonitis and overall/post-peritonitis technique survival in the three study periods
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| Staphylococcus aureus (% of total CPP) | 20% | 17% | 19% |
| Staphylococcus epidermidis (% of total CPP) | 40% | 40% | 36% |
| Pseudomonas (% of total CPP) | 20% | 18% | 16% |
| Othergram-negativeorganisms (includingKlebsiella, Serratia and Enterobacter species) (% of total CPP) | 15% | 17% | 18% |
| Other organisms (% of total CPP) | 5% | 8% | 11% |
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