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Cureus May 2024Industrial accidents involving compressed air can lead to significant colonic injuries, ranging from minor tears to complete perforations. This study investigates a case...
Industrial accidents involving compressed air can lead to significant colonic injuries, ranging from minor tears to complete perforations. This study investigates a case of colonic barotrauma in a 40-year-old male oil refinery worker who suffered symptoms of lower abdominal discomfort, distension, and tenderness following the application of compressed air to his anus. Diagnostic tests, including blood count, abdominal X-ray, and ultrasonography, indicated fecal impaction, dilated bowel loops, and free gas under the diaphragm. An exploratory laparotomy revealed a 4 cm x 2 cm hole in the colon at the hepatic flexure. There were also small breaks in the mucosa at the junction of the recto-sigmoid. We surgically repaired the perforation with primary closure, metrogyl lavage, and the placement of an intra-abdominal pelvic drain. Two weeks later, the patient recovered without any complications and was discharged. This case report highlights the severe risks of non-medical compressed air exposure, as well as the critical need for immediate surgical intervention and preventive safety measures in industrial settings.
PubMed: 38919243
DOI: 10.7759/cureus.61096 -
Annali Italiani Di Chirurgia 2024The management of uterine prolapse poses a significant clinical challenge, with surgical intervention often necessary for symptom relief and restoration of pelvic floor... (Meta-Analysis)
Meta-Analysis Comparative Study
AIM
The management of uterine prolapse poses a significant clinical challenge, with surgical intervention often necessary for symptom relief and restoration of pelvic floor function. However, the optimal surgical approach for uterine prolapse remains uncertain, prompting a comprehensive meta-analysis to compare the efficacy of various surgical methods. This study aims to assess the effectiveness of different surgical methods for treating uterine prolapse.
METHODS
We used computer search to retrieve relevant literature to compare the therapeutic effects of different surgical methods for treating uterine prolapse. The search was conducted in the Web of Science and PubMed databases, and articles published until October 2023 were obtained. We employed random effects and fixed effects models and performed a meta-analysis using the R software.
RESULTS
This study included 40 standard papers covering 25,896 patients with uterine prolapse. We used random and fixed effects models to conduct a meta-analysis of hysterectomy and uterine fixation procedures. The findings indicated that different surgical approaches had no significant impact on surgical success rates (I2 = 69%, p < 0.01; risk ratio (RR) (95% confidence intervals (CI)): 1.00 [0.98; 1.03]) or postoperative adverse reactions (I2 = 54%, p < 0.01; RR (95% CI), 1.10 [0.83; 1.45]). However, the durations of the surgical procedure for hysterectomy (I2 = 91%, p < 0.01; standardized mean difference (SMD) (95% CI), 0.78 [0.49; 1.07]), surgical blood loss (I2 = 97%, p < 0.01, SMD (95% CI): 1.14 [0.21; 2.07]), and intraoperative adverse reactions (I2 = 0%, p = 0.61, RR (95% CI): 1.37 [1.10; 1.71]) were statistically significant between hysterectomy and uterine fixation procedures. Additionally, publication bias and sensitivity tests showed no publication bias in this meta-analysis and no literature causing significant sensitivity.
CONCLUSIONS
In the treatment of uterine prolapse, both hysterectomy and uterine fixation are similar in terms of surgical success rates and postoperative adverse reactions. However, hysterectomy is associated with longer duration of the surgical procedure, increased blood loss and higher incidence of intraoperative adverse reactions compared to uterine fixation.
Topics: Humans; Female; Uterine Prolapse; Treatment Outcome; Gynecologic Surgical Procedures; Hysterectomy; Postoperative Complications
PubMed: 38918960
DOI: 10.62713/aic.3385 -
Techniques in Coloproctology Jun 2024Patient selection is extremely important in obstructed defecation syndrome (ODS) and rectal prolapse (RP) surgery. This study assessed factors that guided the... (Observational Study)
Observational Study
Analysis of factors that indicated surgery in 400 patients submitted to a complete diagnostic workup for obstructed defecation syndrome and rectal prolapse using a supervised machine learning algorithm.
BACKGROUND
Patient selection is extremely important in obstructed defecation syndrome (ODS) and rectal prolapse (RP) surgery. This study assessed factors that guided the indications for ODS and RP surgery and their specific role in our decision-making process using a machine learning approach.
METHODS
This is a retrospective analysis of a long-term prospective observational study on female patients reporting symptoms of ODS who underwent a complete diagnostic workup from January 2010 to December 2021 at an academic tertiary referral center. Clinical, defecographic, and other functional tests data were assessed. A supervised machine learning algorithm using a classification tree model was performed and tested.
RESULTS
A total of 400 patients were included. The factors associated with a significantly higher probability of undergoing surgery were follows: as symptoms, perineal splinting, anal or vaginal self-digitations, sensation of external RP, episodes of fecal incontinence and soiling; as physical examination features, evidence of internal and external RP, rectocele, enterocele, or anterior/middle pelvic organs prolapse; as defecographic findings, intra-anal and external RP, rectocele, incomplete rectocele emptying, enterocele, cystocele, and colpo-hysterocele. Surgery was less indicated in patients with dyssynergia, severe anxiety and depression. All these factors were included in a supervised machine learning algorithm. The model showed high accuracy on the test dataset (79%, p < 0.001).
CONCLUSIONS
Symptoms assessment and physical examination proved to be fundamental, but other functional tests should also be considered. By adopting a machine learning model in further ODS and RP centers, indications for surgery could be more easily and reliably identified and shared.
Topics: Humans; Female; Middle Aged; Rectal Prolapse; Retrospective Studies; Constipation; Aged; Supervised Machine Learning; Syndrome; Defecation; Adult; Prospective Studies; Defecography; Patient Selection; Algorithms; Clinical Decision-Making
PubMed: 38918256
DOI: 10.1007/s10151-024-02951-1 -
BMC Women's Health Jun 2024Pelvic floor disorders are a group of disorders affecting the pelvic floor that include clinically definable conditions such as pelvic organ prolapse, urinary...
BACKGROUND
Pelvic floor disorders are a group of disorders affecting the pelvic floor that include clinically definable conditions such as pelvic organ prolapse, urinary incontinence and fecal incontinence. These conditions silently affect millions of women worldwide and related problems are not well disclosed by women due to associated social stigma or lack of access to services in developing countries. Thus, the magnitude and related burden of these conditions vary, and little is known about them. This study was conducted to assess the magnitude and associated factors of symptomatic pelvic floor disorders in Debre Tabor town, Northwest, Ethiopia, from May 30-July 30, 2020.
METHOD
A community-based cross-sectional study was conducted on child bearing women (> 15 years) who resided in Debre Tabor Town from May 30-July 30, 2020. The participants were selected through multistage systematic random sampling. The data were collected via a structured questionnaire through face-to-face interviews, entered into Epi-info-7.2, and subsequently analyzed using SPSS version 20. The prevalence of pelvic floor disorders was presented along with the 95% CI.
RESULTS
A total of 402 women participated in this study, 59 (14.7%; 95% CI; 11.4, 18.2) of whom reported one or more types of pelvic floor disorders. The most prevalently reported pelvic floor disorders were pelvic organ prolapse (13.9%; 95% CI: 10.9, 17.4), urinary incontinence (10.9%; 95% CI: 7.4, 9.2) and fecal incontinence (7.7%; 95% CI: 5.2, 10.2). Additionally, aging, multiparity and having early marriage (< 18 yrs.) were identified as potential risk factors associated with pelvic floor disorders.
CONCLUSIONS
The prevalence of symptomatic pelvic floor disorders in the current study was high. Thus, early detection, preventive and treatment strategies should be considered. In addition, it is better to educate the community and women on the association of early marriage and multiparty with PFDs.
Topics: Humans; Female; Ethiopia; Adult; Prevalence; Cross-Sectional Studies; Pelvic Floor Disorders; Middle Aged; Young Adult; Urinary Incontinence; Fecal Incontinence; Adolescent; Pelvic Organ Prolapse; Risk Factors; Surveys and Questionnaires
PubMed: 38915020
DOI: 10.1186/s12905-024-03176-y -
International Urogynecology Journal Jun 2024The objective was to create and validate the usefulness of a convolutional neural network (CNN) for identifying different organs of the pelvic floor in the midsagittal...
INTRODUCTION AND HYPOTHESIS
The objective was to create and validate the usefulness of a convolutional neural network (CNN) for identifying different organs of the pelvic floor in the midsagittal plane via dynamic ultrasound.
METHODS
This observational and prospective study included 110 patients. Transperineal ultrasound scans were performed by an expert sonographer of the pelvic floor. A video of each patient was made that captured the midsagittal plane of the pelvic floor at rest and the change in the pelvic structures during the Valsalva maneuver. After saving the captured videos, we manually labeled the different organs in each video. Three different architectures were tested-UNet, FPN, and LinkNet-to determine which CNN model best recognized anatomical structures. The best model was trained with the 86 cases for the number of epochs determined by the stop criterion via cross-validation. The Dice Similarity Index (DSI) was used for CNN validation.
RESULTS
Eighty-six patients were included to train the CNN and 24 to test the CNN. After applying the trained CNN to the 24 test videos, we did not observe any failed segmentation. In fact, we obtained a DSI of 0.79 (95% CI: 0.73 - 0.82) as the median of the 24 test videos. When we studied the organs independently, we observed differences in the DSI of each organ. The poorest DSIs were obtained in the bladder (0.71 [95% CI: 0.70 - 0.73]) and uterus (0.70 [95% CI: 0.68 - 0.74]), whereas the highest DSIs were obtained in the anus (0.81 [95% CI: 0.80 - 0.86]) and levator ani muscle (0.83 [95% CI: 0.82 - 0.83]).
CONCLUSIONS
Our results show that it is possible to apply deep learning using a trained CNN to identify different pelvic floor organs in the midsagittal plane via dynamic ultrasound.
PubMed: 38913129
DOI: 10.1007/s00192-024-05841-0 -
Gastroenterology Report 2024
PubMed: 38912039
DOI: 10.1093/gastro/goae068 -
Current Status and Role of Artificial Intelligence in Anorectal Diseases and Pelvic Floor Disorders.JSLS : Journal of the Society of... 2024Anorectal diseases and pelvic floor disorders are prevalent among the general population. Patients may present with overlapping symptoms, delaying diagnosis, and... (Review)
Review
BACKGROUND
Anorectal diseases and pelvic floor disorders are prevalent among the general population. Patients may present with overlapping symptoms, delaying diagnosis, and lowering quality of life. Treating physicians encounter numerous challenges attributed to the complex nature of pelvic anatomy, limitations of diagnostic techniques, and lack of available resources. This article is an overview of the current state of artificial intelligence (AI) in tackling the difficulties of managing benign anorectal disorders and pelvic floor disorders.
METHODS
A systematic literature review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched the PubMed database to identify all potentially relevant studies published from January 2000 to August 2023. Search queries were built using the following terms: AI, machine learning, deep learning, benign anorectal disease, pelvic floor disorder, fecal incontinence, obstructive defecation, anal fistula, rectal prolapse, and anorectal manometry. Malignant anorectal articles and abstracts were excluded. Data from selected articles were analyzed.
RESULTS
139 articles were found, 15 of which met our inclusion and exclusion criteria. The most common AI module was convolutional neural network. researchers were able to develop AI modules to optimize imaging studies for pelvis, fistula, and abscess anatomy, facilitated anorectal manometry interpretation, and improved high-definition anoscope use. None of the modules were validated in an external cohort.
CONCLUSION
There is potential for AI to enhance the management of pelvic floor and benign anorectal diseases. Ongoing research necessitates the use of multidisciplinary approaches and collaboration between physicians and AI programmers to tackle pressing challenges.
Topics: Humans; Pelvic Floor Disorders; Artificial Intelligence; Rectal Diseases; Anus Diseases; Manometry; Fecal Incontinence
PubMed: 38910957
DOI: 10.4293/JSLS.2024.00007 -
Journal of Biomechanics Jun 2024The perineum is a layered soft tissue structure with mechanical properties that maintain the integrity of the pelvic floor. During childbirth, the perineum undergoes...
The perineum is a layered soft tissue structure with mechanical properties that maintain the integrity of the pelvic floor. During childbirth, the perineum undergoes significant deformation that often results in tears of various degrees of severity. To better understand the mechanisms underlying perineal tears, it is crucial to consider the mechanical properties of the different tissues that make up the perineum. Unfortunately, there is a lack of data on the mechanical properties of the perineum in the literature. The objective of this study is to partly fill these gaps. Hence sow perineums were dissected and the five perineal tissues involved in tears were characterized by uniaxial tension tests: Skin, Vagina, External Anal Sphincter, Internal Anal Sphincter and Anal Mucosa. From our knowledge, this study is the first to investigate all these tissues and to design a testing protocol to characterize their material properties. Six material models were used to fit the experimental data and the correlation between experimental and predicted data was evaluated for comparison. As a result, even if the tissues are of different nature, the best correlation was obtained with the Yeoh and Martins material models for all tissues. Moreover, these preliminary results show the difference in stiffness between the tissues which indicates that they might have different roles in the structure. These obtained results will serve as a basis to design an improved experimental protocol for a more robust structural model of the porcine perineum that can be used for the human perineum to predict perineal tears.
PubMed: 38908107
DOI: 10.1016/j.jbiomech.2024.112175 -
Techniques in Coloproctology Jun 2024Four patients with rectal cancer required reconstruction of a defect of the posterior vaginal wall. All patients received neoadjuvant (chemo)radiotherapy, followed by an...
Four patients with rectal cancer required reconstruction of a defect of the posterior vaginal wall. All patients received neoadjuvant (chemo)radiotherapy, followed by an en bloc (abdomino)perineal resection of the rectum and posterior vaginal wall. The extent of the vaginal defect necessitated closure using a tissue flap with skin island. The gluteal turnover flap was used for this purpose as an alternative to conventional more invasive myocutaneous flaps (gracilis, gluteus, or rectus abdominis). The gluteal turnover flap was created through a curved incision at a maximum width of 2.5 cm from the edge of the perineal wound, thereby creating a half-moon shape skin island. The subcutaneous fat was dissected toward the gluteal muscle, and the gluteal fascia was incised. Thereafter, the flap was rotated into the defect and the skin island was sutured into the vaginal wall defect. The contralateral subcutaneous fat was mobilized for perineal closure in the midline, after which no donor site was visible.The duration of surgery varied from 77 to 392 min, and the hospital stay ranged between 3 and 16 days. A perineal wound dehiscence occurred in two patients, requiring an additional VY gluteal plasty in one patient. Complete vaginal and perineal wound healing was achieved in all patients. The gluteal turnover flap is a promising least invasive technique to reconstruct posterior vaginal wall defects after abdominoperineal resection for rectal cancer.
Topics: Humans; Female; Vagina; Buttocks; Rectal Neoplasms; Middle Aged; Plastic Surgery Procedures; Surgical Flaps; Aged; Perineum; Operative Time; Treatment Outcome
PubMed: 38907171
DOI: 10.1007/s10151-024-02941-3 -
Techniques in Coloproctology Jun 2024Chronic pelvic pain is a hidden issue which needs to involve many different usually uncoordinated specialists. For this reason there is a risk that treatments, in the... (Review)
Review
Chronic pelvic pain is a hidden issue which needs to involve many different usually uncoordinated specialists. For this reason there is a risk that treatments, in the absence of well-defined pathways, common goals, and terminology, may be poorly effective. The aim of the present paper is to summarize the evidence on anorectal pelvic pain, offering useful evidence-based practice parameters for colorectal surgeons' daily activity. Analysis of chronic anorectal and pelvic pain syndromes, the diagnostic and clinical optimal needs for evaluation, and the innumerable low evidence treatments and therapeutic options currently available suggests that a multimodal individualized management of pain may be the most promising approach. The limited availability of dedicated centers still negatively affects the applicability of these principles.
Topics: Humans; Pelvic Pain; Chronic Pain; Colorectal Surgery; Syndrome; Rectal Diseases; Italy; Societies, Medical; Anal Canal; Pain Management
PubMed: 38907168
DOI: 10.1007/s10151-024-02943-1