Prevalence of urinary incontinence among women in Saudi Arabia: a cross-sectional study.

OBJECTIVE: Urinary incontinence is defined as involuntary loss of urine, a common health condition that is more frequent in women. It disturbs the affected individuals and interferes with their daily activities. This study aimed to estimate the prevalence of urinary incontinence among Saudi women in the western area of the Kingdom of Saudi Arabia. SUBJECTS AND METHODS: A descriptive cross-sectional design was used for this study. A survey was administered to Saudi women in the western area of the Kingdom of Saudi Arabia ranging in age from 18 to 70 years. The data were collected using the Arabic version of the Questionnaire for Urinary Incontinence Diagnosis. Descriptive statistics were generated by calculating numbers and percentages of information on the prevalence of incontinence in women. p-values < 0.05 were considered statistically significant. RESULTS: The prevalence of urinary incontinence was 44.2%, with the urge type being the most reported. Stress urinary incontinence was reported by 155 women (15.4%), urgency urinary incontinence by 257 women (25.6%), and mixed urinary incontinence by 102 women (10.15%). CONCLUSIONS: Urinary incontinence is prevalent in women in Western Saudi Arabia. Age, multiparty obesity, and vaginal surgery are significant risk factors influencing its occurrence.

Artificial Intelligence machine learning and conventional physical therapy for upper limb outcome in patients with stroke: a systematic review and meta-analysis.

OBJECTIVE: The goal of this study was to compare the effect of different artificial intelligence (AI) machine learning and conventional therapy (CT) on upper limb impairments in patients with stroke. MATERIALS AND METHODS: PubMed, PubMed Central, Google Scholar, MEDLINE, Cochrane Library, Web of Science, Research Gate, and Wiley Online Library were searched. Descriptive statistics about variables were reported to calculate standardized mean differences in outcomes of motor control (the primary outcome), functional independence, upper extremity performance, and muscle tone. The Physiotherapy Evidence Database (PEDro) Scale was used to assess qualitative papers. The primary outcomes of AI and CT have been included in the meta-analyses. RESULTS: Ten papers with a total of 481 stroke patients were included and upper limb rehabilitation, upper limb functioning, and basic manual dexterity were examined. The heterogeneity test of the whole included measures (I2=45%) was medium. There were significant differences between the included measures (p-value=0.03) with a total SMD of 0.10 [0.01, 0.19]. According to the test for subgroup difference, it was found that there was a highly significant difference between the subgroups of the included measures (p-value=0.01) and the heterogeneity test (I2=59.8%). CONCLUSIONS: AI is a feasible and safe method in post-stroke rehabilitation and improves upper-extremity function compared to CT. Significant AI post-treatment effects on upper-limb impairments have been observed. The findings showed that higher-quality evidence was detected in six assessment scales. However, a lower quality of evidence was detected in other scales. This indicated large or very large and consistent estimates of the treatment effects, and researchers were confident about the results. Therefore, the included observational studies are likely to provide an overestimate of the true effect.