Development and validation of a nomogram for predicting early stress urinary incontinence following endoscopic enucleation of the prostate

Abstract Purpose To develop and validate a predictive nomogram for early stress urinary incontinence (SUI) after endoscopic enucleation of the prostate (EEP) in patients with benign prostatic hyperplasia (BPH). Methods The records of 458 patients who underwent plasmakinetic- or diode-based EEP at our center from March 2016 to December 2019 were reviewed. Among these, 326 and 132 cases were randomly assigned to the training and validation set, respectively. A predictive nomogram was constructed based on multivariate logistic regression analysis. Receiver operating characteristic (ROC) analysis and calibration curves were employed to evaluate its performance. Results 65 years ≤ age < 70 years, 75 years ≤ age, 25 kg/m2 ≤ BMI < 30 kg/m2, 30 kg/m2 ≤ BMI, 5 years ≤ LUTS duration, and 75 ml ≤ prostate volume were finally selected as independent predictors of early SUI into the multivariate logistics regression model. It was visualized as a concise nomogram with satisfactory discrimination and accuracy in both training and validation sets. Conclusions A concise nomogram was developed and validated as a useful clinical tool for predicting early SUI post-EEP.

Download Full-text

Development and validation of a nomogram for predicting early stress urinary incontinence following endoscopic enucleation of the prostate

World Journal of Urology ◽

10.1007/s00345-021-03654-0 ◽

2021 ◽

Author(s):

Eugenio Ventimiglia ◽

Federico Dehò ◽

Andrea Gallina ◽

Paolo Capogrosso ◽

Francesco Montorsi

Keyword(s):

Urinary Incontinence ◽

Stress Urinary Incontinence ◽

Early Stress ◽

Endoscopic Enucleation ◽

Development And Validation

Download Full-text

Development and Validation of a Risk Prediction Model of Linezolid-induced Thrombocytopenia in Elderly Patients

10.21203/rs.3.rs-582799/v1 ◽

2021 ◽

Author(s):

Yan Qin ◽

Zhe Chen ◽

Shuai Gao ◽

Ming Kun Pan ◽

Yu Xiao Li ◽

...

Keyword(s):

Risk Factors ◽

Elderly Patients ◽

Predictive Model ◽

Bacterial Infections ◽

Demographic Data ◽

Multivariate Logistic Regression Analysis ◽

Platelet Counts ◽

Linezolid Therapy ◽

Validation Set ◽

Development And Validation

Abstract Background Linezolid is an oxazolidinone antimicrobial agent developed for treating multi-drug-resistant gram-positive bacterial infections. Objective This study aimed at investigating risk factors of linezolid (LI)-induced thrombocytopenia (LI-TP) and establishing a risk predictive model for LI-TP.Setting ZhongShan Hospital, FuDan University, China. Method A retrospective study was performed in patients aged ≥ 65 years receiving linezolid therapy from January 2015 to April 2021. Clinical characteristics and demographic data were collected and compared between patients with LI-TP and those without.Main outcome measures Incidence and risk factors of LI-TP in elderly patients.Results A total of 343 inpatients were included as the train set from January 2015 to August 2020. Among them, 67 (19.5%) developed LI-TP. Multivariate logistic regression analysis revealed that baseline platelet counts < 150×109·L-1 (OR=3.576; P< 0.001), age ≥ 75 years (OR=2.258; P=0.009), eGFR< 60 mL·(min·1.73m2)-1 (OR=2.553; P=0.002), duration of linezolid therapy ≥ 10 d (OR=3.218; P<0.001), ICU admittance (OR=2.682; P=0.004), and concomitant with piperacillin-tazobactam (PTZ) (OR=3.863; P=0.006) were independent risk factors for LI-TP. The risk predictive model was established and exhibited a moderate discriminative power, with an AUC of 0.795 [95%CI 0.740-0.851] and 0.849 [95%CI 0.760-0.939] in train set (n=343) and validation set (n=90), respectively.Conclusion The risk factors of LI-TP in elderly patients were duration of linezolid therapy, age, eGFR, ICU admittance, baseline platelet counts, and concomitant with PTZ. A risk predictive model based on these risk factors may be useful to identify patients with high risk of LI-TP.

Download Full-text

Development and validation of a nomogram to predict the mortality risk in elderly patients with ARF

PeerJ ◽

10.7717/peerj.11016 ◽

2021 ◽

Vol 9 ◽

pp. e11016

Author(s):

Junnan Xu ◽

Jie Weng ◽

Jingwen Yang ◽

Xuan Shi ◽

Ruonan Hou ◽

...

Keyword(s):

Prognostic Factors ◽

Elderly Patients ◽

Mortality Risk ◽

Systolic Pressure ◽

Multivariate Logistic Regression Analysis ◽

Prediction Of Mortality ◽

Short Term Mortality ◽

Life Threatening ◽

Validation Set ◽

Development And Validation

Background Acute respiratory failure (ARF) is a life-threatening complication in elderly patients. We developed a nomogram model to explore the risk factors of prognosis and the short-term mortality in elderly patients with ARF. Methods A total of 759 patients from MIMIC-III database were categorized into the training set and 673 patients from our hospital were categorized into the validation set. Demographical, laboratory variables, SOFA score and APS-III score were collected within the first 24 h after the ICU admission. A 30-day follow-up was performed for all patients. Results Multivariate logistic regression analysis showed that the heart rate, respiratoryrate, systolic pressure, SPO2, albumin and 24 h urine output were independent prognostic factors for 30-day mortality in ARF patients. A nomogram was established based on above independent prognostic factors. This nomogram had a C-index of 0.741 (95% CI [0.7058–0.7766]), and the C-index was 0.687 (95% CI [0.6458–0.7272]) in the validation set. The calibration curves both in training and validation set were close to the ideal model. The SOFA had a C-index of 0.653 and the APS-III had a C-index of 0.707 in predicting 30-day mortality. Conclusion Our nomogram performed better than APS-III and SOFA scores and should be useful as decision support on the prediction of mortality risk in elderly patients with ARF.

Download Full-text

Development and Validation of a Nomogram to Predict Deteriorating Trajectory in Patients with COVID-19 Infection: A Population-Based Prospective Study

10.21203/rs.3.rs-30640/v1 ◽

2020 ◽

Author(s):

Wei Chen ◽

Menglin Zhu ◽

Jian Li ◽

Cuiping Pan ◽

Demian Zhao ◽

...

Keyword(s):

Multivariate Logistic Regression Analysis ◽

Area Under The Curve ◽

Population Based ◽

Clinical Prediction ◽

Single Center ◽

Multivariate Logistic Regression ◽

Training Set ◽

Clinical Prediction Model ◽

Validation Set ◽

Development And Validation

Abstract Background Most of the patients with COVID-19 infection are mild to moderate initially. However, there is no effective prediction for the patients to develop into severe or extremely severe. This study aims to develop an effective clinical prediction model.Methods A single-center, retrospective, observational study conducted. A nomogram was conducted based on the results of multivariate logistic regression analysis. Results A total of 483 patients diagnosed mild to moderate were included, among these patients 62 developed severe or extremely critical illness. Seven variables including hyperlipidemia, vomiting, diarrhea, lymphocyte, imaging and mentality were associated with deteriorating trajectory. The ROC curve showed that model was robust, for which the area under the curve of the training set and the validation set are 0.873 and 0.813.Conclusions For patients with mild to moderate COVID-19 infection, nomogram score can effectively predict the possibility of patients developing into severe or extremely critical.

Download Full-text

Commentary on "Development and validation of a prediction model for bothersome stress urinary incontinence after prolapse surgery" by Oh et al

BJOG An International Journal of Obstetrics & Gynaecology ◽

10.1111/1471-0528.17067 ◽

2021 ◽

Author(s):

J. Marinus van der Ploeg ◽

Ewout W. Steyerberg

Keyword(s):

Urinary Incontinence ◽

Stress Urinary Incontinence ◽

Prediction Model ◽

Prolapse Surgery ◽

Development And Validation

Download Full-text

Epidemiological survey of adult female stress urinary incontinence

BMC Women s Health ◽

10.1186/s12905-021-01319-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Rui Qin Zhang ◽

Man Cheng Xia ◽

Fan Cui ◽

Jia Wei Chen ◽

Xiao Dong Bian ◽

...

Keyword(s):

Risk Factors ◽

Urinary Incontinence ◽

Urinary Tract ◽

Stress Urinary Incontinence ◽

Adult Female ◽

Univariate Analysis ◽

Mode Of Delivery ◽

Multivariate Logistic Regression Analysis ◽

Female Stress Urinary Incontinence ◽

Prevention And Treatment

Abstract Background The prevalence of stress urinary incontinence (SUI) in adult female in Taiyuan and what are the related risk factors are not clear. The aim of this study was to provide a basis for exploring the prevention and treatment of SUI in adult female in Taiyuan. Methods A voluntary online questionnaire was used to investigate adult female in the community and surrounding townships of Taiyuan. Most of the questionnaires refer to the International Consultation on Incontinence Questionnaire-Female Lower Urinary Tract Symptoms, and adapt to the specific circumstances of the region. Data were analyzed using SPSS software (version 22.0). Results A total of 4004 eligible questionnaires were obtained. The prevalence of SUI in adult female in Taiyuan was 33.5%. Univariate analysis and multivariate logistic regression analysis showed that place of residence, smoking, body mass index, diet, number of deliveries, mode of delivery, dystocia, menopause, oral contraceptives, urinary tract infection, making the bladder empty faster by pushing down and holding urine were risk factors for adult female stress urinary incontinence in Taiyuan. Conclusion The prevalence of SUI in adult female in Taiyuan was high, and based on risk factors identified in this survey, population-level intervention strategies should be developed for the prevention and treatment of adult female SUI in Taiyuan.

Download Full-text

Effect of anogenital distance on stress urinary incontinence

African Journal of Urology ◽

10.1186/s12301-021-00247-6 ◽

2021 ◽

Vol 27 (1) ◽

Author(s):

Murat Ekmez ◽

Fırat Ekmez

Keyword(s):

Urinary Incontinence ◽

Stress Urinary Incontinence ◽

Important Implication ◽

Multivariate Logistic Regression Analysis ◽

Inclusion Criteria ◽

Multivariate Logistic Regression ◽

Anogenital Distance ◽

Female Patients ◽

Development Risk ◽

Study Inclusion

Abstract Background To clarify the effect of anogenital distance (AGD) on stress urinary incontinence (SUI) in female patients. Methods Charts of patients who admitted to urogynecology polyclinic between December 2020 and February 2021 were analyzed retrospectively. The AGD parameters including anogenital distance from the anus to the clitoris (AGDAC), anogenital distance from the anus to the fourchette (AGDAF) and genital hiatus (GH) were measured. To identify effect of ADG parameters on SUI, patients were divided into the two subgroups (patients with SUI and without SUI). Demographic characteristics of patients and perineal anatomy measurement were compared between groups. Results Totally, 256 female patients met study inclusion criteria. In comparison of patients with and without SUI, demonstrated that age, weight, height, and BMI were similar between groups (p = 0.200, p = 0.455, p = 0.131, and p = 0.215, respectively). The AGDAF was measured 22.6 mm in patients with SUI and 25.5 mm in patients without SUI (p = 0.014). In contrast, AGDAC was significantly longer in patients with SUI (81.1 mm vs. 72.2 mm, p = 0.001). Also, GH was significantly longer in patients with SUI (p = 0.016). Multivariate logistic regression analysis revealed that one mm increment in AGDAC and GH, is associated with 1.108- and 1.038-fold time of SUI development risk, respectively (p = 0.001 and p = 0.004). In contrast, decrease in AGDAF is resulted with significantly higher risk for SUI (p = 0.001). Conclusion The present study demonstrated that shorter AGDAF, and longer AGDAC and GH were resulted with significantly higher incidence of SUI. Considering the ease and non-invasiveness of anogenital distance measurement, an important implication of the results of current study is that it is a measurement that can be easily performed during routine gynecological and obstetric examinations as a suitable tool for use in the prediction of women who will develop stress incontinence in the future.

Download Full-text

Modified Colon Leakage Score to Predict Anastomotic Leakage in Patients Who Underwent Left-Sided Colorectal Surgery

Journal of Clinical Medicine ◽

10.3390/jcm8091450 ◽

2019 ◽

Vol 8 (9) ◽

pp. 1450

Author(s):

Seung Up Yang ◽

Eun Jung Park ◽

Seung Hyuk Baik ◽

Kang Young Lee ◽

Jeonghyun Kang

Keyword(s):

Colorectal Surgery ◽

Anastomotic Leakage ◽

Operating Characteristic ◽

Predictive Performance ◽

Lasso Regression ◽

Clinical Tool ◽

Training Set ◽

Validation Set ◽

Selection Operator ◽

Better Than

Colon leakage score (CLS) was introduced as a clinical tool to predict anastomotic leakage (AL) in patients who underwent left-sided colorectal surgery, but its clinical validity has not been widely studied. We evaluated the clinical utility of CLS and developed a modified CLS (m-CLS). In total, 566 patients who underwent left-sided colorectal surgery were enrolled and categorized into training (n = 396) and validation (n = 170) sets via random sampling. Using CLS variables, the least absolute shrinkage and selection operator (LASSO) regression model was applied for variable selection and predictive signature building in the training set. The model’s performance was validated in the validation set. The predictive powers of m-CLS and CLS were compared by the area under the receiver operating characteristic (AUROC) curve in the overall group. Twenty-three AL events (4.1%) were noted. The AL group had a significantly higher mean CLS than the No Leakage group (12.5 vs. 9.6, p = 0.001). Five clinical variables were selected and used to generate m-CLS. The predictive performance of m-CLS was similar in training and validation sets (AUROC 0.838 vs. 0.803, p = 0.724). In the overall set, m-CLS was significantly predictive of AL and performed better than CLS (AUROC 0.831 vs. 0.701, p = 0.008). In conclusion, LASSO-model-generated m-CLS could predict AL more accurately than CLS.

Download Full-text