METHODS: Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.
RESULTS: 5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.
CONCLUSION: Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.
MATERIALS AND METHODS: We investigated Google Trends® for popular search relating to medication errors, risk management and shift work. Relative search volumes (RSVs) were evaluated from 2008 to 2018. A comparison between RSV curves related to medication errors, risk management and shift work was carried out. Then, we compared the world to Italian search.
RESULTS: RSVs were persistently higher for risk management than for medication errors (mean RSVs 069 vs. 48%) and RSVs were stably higher for medication errors than shift work (mean RSVs 48 vs. 22%). In Italy, RSVs were much lower compared to the rest of the world, and RSVs for medication errors during the study period were negligible. Mean RSVs for risk management and shift work were 3 and 25%, respectively. RSVs related to medication errors and clinical risk management were correlated (r=0.520, p<0.0001).
CONCLUSIONS: Google Trends® search query volumes related to medication errors, risk management and shift work are different. RSVs for risk management are higher, and they are correlated with medication errors. Also, shift work search appears to be lower. These results should be interpreted in order to correctly evaluate how to decrease the number of medication errors in different health care related setting.
METHODOLOGY: This is a retrospective cohort study recruiting all kidney transplant recipients in South Australia from January 2010 till December 2018. Following that, the incidence of blood transfusion within one week post-operatively were traced (transfusion group). The outcomes were compared with all other transplant recipients (non-transfusion group). Recipient's demographic, donor characteristics and immunological risk profiles were obtained from the transplant unit database, while the biopsy report, history of blood transfusion, latest serum creatinine and follow-up status was gathered from the electronic medical system (OASIS). The HLA-DSA and HLA-Ab results were collected from the NOMS database. Finally, the survival data were merged with the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry for South Australia recipients graft survival.
RESULTS: A total of 699 patients were eligible for analysis. The mean age was 50.64 ± 13.23 years old. There were more elderly (>65 years old) and females who needed transfusion. The majority had glomerulonephritis as the primary disease. There was no statistical difference in donor characteristics, cold ischemic time and immunological risk between the transfusion and non-transfusion group. There was no difference in the development of de novo HLA-DSA, HLA-Ab and rejection episodes between the group and the results were consistent in a model adjusted for all potential confounders. Median graft survival in days between the transfusion vs non-transfusion group was 1845 IQR (961,2430) and 1250 IQR (672,2013).
CONCLUSION: Blood transfusion under strong immunosuppressive cover within a one-week post-operative period is safe with no significant association with the development of de novo HLA-DSA, HLA-Ab or clinical rejection.