scholarly journals Patient reported outcome measures concerning urinary incontinence after robot assisted radical prostatectomy: development and validation of an online prediction model using clinical parameters, lower urinary tract symptoms and surgical experience

Author(s):  
Eelco R. P. Collette ◽  
Sjoerd O. Klaver ◽  
Birgit I. Lissenberg-Witte ◽  
Dies van den Ouden ◽  
Reindert J. A. van Moorselaar ◽  
...  

Abstract The prediction of post-prostatectomy incontinence (PPI) after robot-assisted radical prostatectomy (RARP) depends on multiple clinical, anatomical and surgical factors. There are only few risk formulas, tables or nomograms predicting PPI that may assist clinicians and their patients in adequate risk counseling on postoperative side-effects. Prospective data collection of 1814 patients who underwent RARP between 2009 and 2017 was done. Pre-operative parameters were age, body mass index (BMI), prostate volume, the American Society of Anesthesiologists (ASA) score, severity of Lower Urinary Tract Symptoms (LUTS), type of planned nerve-sparing surgery and surgical experience. The continence status was reported using Patient Reported Outcome Measurements (PROMs) using the validated pad-use questionnaire EPIC26. Continence was defined as either the use of zero pads or one safety pad. Multivariable logistic regression analysis was performed to identify predictors of PPI within one year after RARP. An online prediction tool was developed and validated. The median follow-up was 36 months (range 12–108). The response rate was high at 85.2%. A total of 85% (1537/1814) of patients was continent on follow-up. One-year continence rate was 80.1% (95% CI 78.3–81.9%) (1453/1814) and increased to 87.4% (95% CI 85.4–89.4%) after 5 years. On multivariable analysis, severity of LUTS (OR = 0.56 p = 0.004), higher age (OR = 0.73 p = 0.049), extend of nerve-sparing surgery (OR = 0.60 p = 0.001) and surgeon experience (OR = 1.48 p = 0.025) were significant independent predictors for PPI. The online prediction model performed well in predicting continence status with poor discrimination and good calibration. An intuitive online tool was developed to predict PPI after RARP that may assist clinicians and their patients in counseling of treatment.

2019 ◽  
Vol 101-B (9) ◽  
pp. 1138-1143 ◽  
Author(s):  
D. R. W. MacDonald ◽  
P. Caba-Doussoux ◽  
C. A. Carnegie ◽  
I. Escriba ◽  
D. P. Forward ◽  
...  

Aims The aim of this study was to compare the incidence of anterior knee pain after antegrade tibial nailing using suprapatellar and infrapatellar surgical approaches Patients and Methods A total of 95 patients with a tibial fracture requiring an intramedullary nail were randomized to treatment using a supra- or infrapatellar approach. Anterior knee pain was assessed at four and six months, and one year postoperatively, using the Aberdeen Weightbearing Test – Knee (AWT-K) score and a visual analogue scale (VAS) score for pain. The AWT-K is an objective patient-reported outcome measure that uses weight transmitted through the knee when kneeling as a surrogate for anterior knee pain. Results A total of 53 patients were randomized to a suprapatellar approach and 42 to an infrapatellar approach. AWT-K results showed a greater mean proportion of weight transmitted through the injured leg compared with the uninjured leg when kneeling in the suprapatellar group compared with the infrapatellar group at all timepoints at all follow-up visits. This reached significance at four months for all timepoints except 30 seconds. It also reached significance at six months at 0 seconds, and for one year at 60 seconds. Conclusion The suprapatellar surgical approach for antegrade tibial nailing is associated with less anterior knee pain postoperatively compared with the infrapatellar approach Cite this article: Bone Joint J 2019;101-B:1138–1143


Author(s):  
Jessy Hansen ◽  
Susannah Ahern ◽  
Pragya Gartoulla ◽  
Ying Khu ◽  
Elisabeth Elder ◽  
...  

Abstract Background Patient-reported outcome measures (PROMs) are an important tool for evaluating outcomes following breast device procedures, and are used by breast device registries. PROMs can assist with device monitoring through benchmarked outcomes, but need to account for demographic and clinical factors which may affect PROMs responses. Objectives This study aimed to develop appropriate risk-adjustment models for the benchmarking of PROMs data to accurately track device outcomes and identify outliers in an equitable manner. Methods Data for this study were obtained from the Australian Breast Device Registry, which consists of a large prospective cohort of patients with primary breast implants. The five-question BREAST-Q implant surveillance module was used to assess PROMs at one-year following implant insertion. Logistic regression models were used to evaluate associations between demographic and clinical characteristics and PROMs separately by implant indication. Final multivariate risk-adjustment models were built sequentially assessing the independent significant association of these variables. Results 2,221 reconstructive and 12,045 aesthetic primary breast implants with complete one-year follow-up PROMs were included in the study. Indication for operation (post-cancer, risk-reduction, developmental deformity) was included in the final model for all reconstructive implant PROMs. Site type (private or public hospital) was included in the final breast reconstruction model for look, rippling and tightness. Age at operation was included in the reconstruction models for rippling and tightness and in the aesthetic models for look, rippling, pain and tightness. Conclusions These multivariate models will be useful for equitable benchmarking of breast devices by PROMs to help track device performance.


2019 ◽  
Vol 101-B (7) ◽  
pp. 768-778 ◽  
Author(s):  
V. P. Galea ◽  
P. Rojanasopondist ◽  
L. H. Ingelsrud ◽  
H. E. Rubash ◽  
C. Bragdon ◽  
...  

AimsThe primary aim of this study was to quantify the improvement in patient-reported outcome measures (PROMs) following total hip arthroplasty (THA), as well as the extent of any deterioration through the seven-year follow-up. The secondary aim was to identify predictors of PROM improvement and deterioration.Patients and MethodsA total of 976 patients were enrolled into a prospective, international, multicentre study. Patients completed a battery of PROMs prior to THA, at three months post-THA, and at one, three, five, and seven-years post-THA. The Harris Hip Score (HHS), the 36-Item Short-Form Health Survey (SF-36) Physical Component Summary (PCS), the SF-36 Mental Component Summary (MCS), and the EuroQol five-dimension three-level (EQ-5D) index were the primary outcomes. Longitudinal changes in each PROM were investigated by piece-wise linear mixed effects models. Clinically significant deterioration was defined for each patient as a decrease of one half of a standard deviation (group baseline).ResultsImprovements were noted in each PROM between the preoperative and one-year visits, with one-year values exceeding age-matched population norms. Patients with difficulty in self-care experienced less improvement in HHS (odds ratio (OR) 2.2; p = 0.003). Those with anxiety/depression experienced less improvement in PCS (OR -3.3; p = 0.002) and EQ-5D (OR -0.07; p = 0.005). Between one and seven years, obesity was associated with deterioration in HHS (1.5 points/year; p = 0.006), PCS (0.8 points/year; p < 0.001), and EQ-5D (0.02 points/year; p < 0.001). Preoperative difficulty in self-care was associated with deterioration in HHS (2.2 points/year; p < 0.001). Preoperative pain from other joints was associated with deterioration in MCS (0.8 points/year; p < 0.001). All aforementioned factors were associated with clinically significant deterioration in PROMs (p < 0.035), except anxiety/depression with regard to PCS (p = 0.060).ConclusionThe present study finds that patient factors affect the improvement and deterioration in PROMs over the medium term following THA. Special attention should be given to patients with risk factors for decreased PROMs, both preoperatively and during follow-up. Cite this article: Bone Joint J 2019;101-B:768–778.


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