Predictive Model for Estimating Prostate Resection Size in Transurethral Resection of the Prostate for Patients with Benign Prostatic Hyperplasia

Background: Transurethral resection of the prostate (TURP) is widely recognized as the gold standard surgical treatment for patients experiencing bladder outlet obstruction (BOO) due to benign prostatic hyperplasia (BPH). An essential consideration in TURP is determining the amount of tissue resecti...

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Main Authors: Okwudli C. Amu, Solomon K. Anyimba
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2024-07-01
Series:International Journal of Medicine and Health Development
Subjects:
Online Access:https://doi.org/10.4103/ijmh.ijmh_6_24
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author Okwudli C. Amu
Solomon K. Anyimba
author_facet Okwudli C. Amu
Solomon K. Anyimba
author_sort Okwudli C. Amu
collection DOAJ
description Background: Transurethral resection of the prostate (TURP) is widely recognized as the gold standard surgical treatment for patients experiencing bladder outlet obstruction (BOO) due to benign prostatic hyperplasia (BPH). An essential consideration in TURP is determining the amount of tissue resection necessary to achieve a clinical improvement of lower urinary tract symptoms. Objectives: To develop a model for predicting resected prostate weight (RPW) for TURP. Materials and Methods: This was a cross-sectional study involving 187 patients who underwent TURP between January 2016 and July 2017 in a Nigerian hospital. Results: The mean age of the patients was 66.13 years (SD = 8.02). The mean post-void residual urine volume (PVR) was 192.74 mL (SD = 241.88), while the mean transrectal ultrasound scan (TRUS) estimated prostate weight (EPW) was 44.24 g (SD = 18.40). The mean RPW was 27.01 g (SD = 10.80), and the mean International Prostate Symptom Score (IPSS) score was 25.88 (SD = 5.12). A statistically significant positive correlation was observed between RPW and TRUS EPW (r = 0.636, P < 0.001) as well as between RPW and PVR (r = 0.359, P < 0.001). A weak positive correlation was found between RPW and pre-treatment IPSS (r = 0.191, P = 0.023). In a regression model, only TRUS EPW and PVR were significant predictors of the RPW (P < 0.05). Conclusion: It is essential to develop a model for predicting the RPW for TURP. This could significantly aid in surgical planning before the procedure.
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spelling doaj-art-feb0232b8da549ac9d8325ea6e5e71f52025-01-25T10:09:58ZengWolters Kluwer Medknow PublicationsInternational Journal of Medicine and Health Development2635-36952667-28632024-07-0129317017510.4103/ijmh.ijmh_6_24Predictive Model for Estimating Prostate Resection Size in Transurethral Resection of the Prostate for Patients with Benign Prostatic HyperplasiaOkwudli C. AmuSolomon K. AnyimbaBackground: Transurethral resection of the prostate (TURP) is widely recognized as the gold standard surgical treatment for patients experiencing bladder outlet obstruction (BOO) due to benign prostatic hyperplasia (BPH). An essential consideration in TURP is determining the amount of tissue resection necessary to achieve a clinical improvement of lower urinary tract symptoms. Objectives: To develop a model for predicting resected prostate weight (RPW) for TURP. Materials and Methods: This was a cross-sectional study involving 187 patients who underwent TURP between January 2016 and July 2017 in a Nigerian hospital. Results: The mean age of the patients was 66.13 years (SD = 8.02). The mean post-void residual urine volume (PVR) was 192.74 mL (SD = 241.88), while the mean transrectal ultrasound scan (TRUS) estimated prostate weight (EPW) was 44.24 g (SD = 18.40). The mean RPW was 27.01 g (SD = 10.80), and the mean International Prostate Symptom Score (IPSS) score was 25.88 (SD = 5.12). A statistically significant positive correlation was observed between RPW and TRUS EPW (r = 0.636, P < 0.001) as well as between RPW and PVR (r = 0.359, P < 0.001). A weak positive correlation was found between RPW and pre-treatment IPSS (r = 0.191, P = 0.023). In a regression model, only TRUS EPW and PVR were significant predictors of the RPW (P < 0.05). Conclusion: It is essential to develop a model for predicting the RPW for TURP. This could significantly aid in surgical planning before the procedure.https://doi.org/10.4103/ijmh.ijmh_6_24bphpredictive modelresected weightturp
spellingShingle Okwudli C. Amu
Solomon K. Anyimba
Predictive Model for Estimating Prostate Resection Size in Transurethral Resection of the Prostate for Patients with Benign Prostatic Hyperplasia
International Journal of Medicine and Health Development
bph
predictive model
resected weight
turp
title Predictive Model for Estimating Prostate Resection Size in Transurethral Resection of the Prostate for Patients with Benign Prostatic Hyperplasia
title_full Predictive Model for Estimating Prostate Resection Size in Transurethral Resection of the Prostate for Patients with Benign Prostatic Hyperplasia
title_fullStr Predictive Model for Estimating Prostate Resection Size in Transurethral Resection of the Prostate for Patients with Benign Prostatic Hyperplasia
title_full_unstemmed Predictive Model for Estimating Prostate Resection Size in Transurethral Resection of the Prostate for Patients with Benign Prostatic Hyperplasia
title_short Predictive Model for Estimating Prostate Resection Size in Transurethral Resection of the Prostate for Patients with Benign Prostatic Hyperplasia
title_sort predictive model for estimating prostate resection size in transurethral resection of the prostate for patients with benign prostatic hyperplasia
topic bph
predictive model
resected weight
turp
url https://doi.org/10.4103/ijmh.ijmh_6_24
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