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8 ± 4.3 vs 8.4 ± 6.8 days; P < .01). There was no difference in time to reimplantation, change in ROM from pre-Stage 1 to most recent follow-up, or reinfection. Real-component spacers had shorter hospital stays (3.3 ± 1.7 vs 5.4 ± 4.9 days; P < .01) and operative times during Stage 2 (162.2 ± 47.5 vs 188.0 ± 66.0minutes; P= .01).

Real-component spacers had improved ROM after Stage 1 and lower blood loss, shorter operative time, and shorter hospital stays after Stage 2 compared to all-cement articulating spacers. The 2 spacer constructs had the same ultimate change in ROM and no difference in reinfection rates, indicating that both articulating spacer types may be safe and effective options for 2-stage revision TKA.

III, retrospective observational analysis.

III, retrospective observational analysis.Quality improvement is driven by benchmarking between and within institutions over time and the collaborative improvement efforts that stem from these comparisons. Benchmarking requires systematic collection and use of standardized data. Low- and middle-income countries (LMIC) have great potential for improvements in newborn outcomes but serious obstacles to data collection, analysis, and implementation of robust improvement methodologies exist. We review the importance of data collection, internationally recommended neonatal metrics, selected methods of data collection, and reporting. The transformation from data collection to data use is illustrated by several select data system examples from LMIC. GPR84 antagonist 8 price Key features include aims and measures important to neonatal team members, co-development with local providers, immediate access to data for review, and multidisciplinary team involvement. The future of neonatal care, use of data, and the trajectory to reach global neonatal improvement targets in resource-limited settings will be dependent on initiatives led by LMIC clinicians and experts.

The presence of carcinoma in situ (Cis) in association with bladder cancer is associated with a poor prognosis. However, the prognosis associated with the presence of Cis in ureteral margins (CUM) during radical cystectomy has been poorly defined. To assess the prognosis associated with the presence of Cis in ureteral margins in patients with pM0 bladder cancer who have not undergone neoadjuvant chemotherapy.

A retrospective case-control study was conducted between 2001 and 2016 using data from one academic center in France. From 1,450 radical cystectomies, 122 patients (case) who had CUM were matched according to age, sex, pTNM stage and urinary diversion method with a population sample of 122 patients (controls) who did not have Cis in ureteral margins during radical cystectomy. The survival analysis was performed by Kaplan-Meier using a (95%) CI. Multivariate Cox regression analysis was used to test the effect of CUM on cancer-specific survival. Recurrence-free survival was defined as a recurrence of use in the risk of urothelial recurrence, and adecrease inbothoverall and specific survival. This supports the use of frozen section analysis to complete radical cystectomy without CUM.

CUM is a poor prognostic factor that impacts cancer-specific survival and Recurrence-free survival. The presence of CUM has been independently associated with a significant increase in the risk of urothelial recurrence, and a decrease in both overall and specific survival. This supports the use of frozen section analysis to complete radical cystectomy without CUM.

To validate the prognostic utility of the novel European Urology Association (EAU) biochemical recurrence (BCR) risk groups in an Asian cohort and to determine whether refinement is necessary.

Two cohorts of men who experienced BCR after radical prostatectomy between 1998 and 2014 were employed. The Cox model was used to validate and model the probability of metastasis and death after BCR. Data from 817 men from the first cohort were used to develop a modified model and external validation was performed on 344 men from the second cohort.

Distant metastasis-free survival and cancer-specific survival from the time of BCR were significantly higher in patients with a low EAU BCR risk (prostate-specific antigen doubling time [PSADT] >1 year and pathologic Gleason score [pGS] ≤7) than in high EAU BCR risk patients (PSADT ≤1 year or pGS 8-10). In the high EAU BCR risk group, survival outcomes and efficacy of early salvage radiotherapy in patients with PSADT 6-12 months and pGS ≤7 were similar to those in the low EAU BCR risk group. The C-index, which predicts metastatic progression and cancer-specific death, improved after PSADT cutoff point was modified to 6 months, and was validated externally.

EAU BCR risk stratification reliably identified patients at increased risk of metastasis and cancer-specific mortality in the present cohort. Modification of the PSADT cutoff point may help to optimize the predictive performance and utility of the EAU BCR risk groups in clinical practice.

EAU BCR risk stratification reliably identified patients at increased risk of metastasis and cancer-specific mortality in the present cohort. Modification of the PSADT cutoff point may help to optimize the predictive performance and utility of the EAU BCR risk groups in clinical practice.A cross-sectional, nationwide survey was conducted in Japan to examine the relationship between tobacco smoking and oral diseases including implant failure. A questionnaire survey was sent to designated facilities by post, and 158 answered questions regarding implant loss. Smoking status, number of implant failures, and other related variables were collected from the participating dentists as secondary data. A total of 1966 patients who were treated with dental implants by participating dentists during the survey period were analysed. Among the total sample, 90 (5%) had early implant loss (≤12 months) and 153 (8%) had late implant loss (>12 months and ≤120 months). The number of pack-years was significantly higher in the total (early and late) implant loss group (31.2±15.9) than in the group with no implant loss (26.1±18.1) (P=0.026). In the multivariate analysis, the number of implants installed, smoking, and pack-years were significant factors for total implant loss. The adjusted odds ratio for implant failure for current smokers compared with never smokers was 2.