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OBJECTIVE: To determine the importance of optical coherence tomography (OCT) in patients scheduled for cataract surgery who present with no pathologies in biomicroscopic fundus examination.
METHODS: Retrospective study.
METHODS: In this study, the routine ophthalmologic examination of patients who were recommended cataract surgery was performed.Occult retinal pathologies were evaluated using OCT in patients without any pathologies in biomicroscopic fundus examination.According to whether retinal pathologies were detected on OCT, the patients were divided into two groups: normal and abnormal OCT.The findings of patients with retinal pathologies on OCT and their distribution according to age were also evaluated.
RESULTS: A total of 271 eyes from 271 patients were evaluated.The number of patients with retinal pathologies on OCT despite normal fundoscopic examination findings was 38(14.0%).Of these patients,15(39.4%) had an epiretinal membrane,10(26.3%) had age-related macular degeneration, eight(21%) had vitreomacular traction, two(5.2%) had a lamellar hole, and 1(2.6%) patient each had a full-thickness macular hole, an intraretinal cyst, and photoreceptor layer damage.The age distribution of the patients with retinal pathologies was as follows: two patients,<60 years; six patients,60-70 years;14 patients,70-80 years; and 16 patients,>80 years.The rate of patients aged > 70 years and above was 78.9%.There was no statistically significant difference between the normal and abnormal OCT groups in terms of age, gender, the presence of systemic diseases, visual acuity, central macular thickness, and cataract type or density(p > 0.05 for all).
CONCLUSIONS: In one of seven patients evaluated, retinal pathologies were detected on OCT despite normal fundoscopic examination findings.OCT can be used to detect occult retinal pathologies that cannot be detected by biomicroscopic fundus examination before cataract surgery.

BACKGROUND: Endometrial cancer (EC) is the strongest obesity-associated malignancy and the fastest-growing cancer in young women. Early identification of EC and other endometrial pathology (malignant and nonmalignant) in women with severe obesity may improve treatment options and uterine preservation. Screening for endometrial pathology using abnormal or postmenopausal uterine bleeding (APUB) as a surrogate in women pursuing metabolic/bariatric surgery may be clinically beneficial, but data supporting this effort are limited.
OBJECTIVE: To develop and institute a screening program for APUB as a surrogate for endometrial pathology in bariatric surgery candidates.
METHODS: Two, academic metabolic/bariatric surgery programs in Louisiana, United States.
METHODS: The Modified SAMANTA is a 10-item questionnaire that was implemented to identify patients with APUB, specifically combining tools designed to identify anovulatory/postmenopausal and heavy menstrual bleeding. Demographic (age, race), body mass index, and questionnaire data were analyzed with respect to positive screening using data from March 2021 through May 2023.
RESULTS: Of 1371 eligible women presenting for surgical evaluation, 664 (48.4%) positive screens were identified and referred for gynecologic evaluation to rule out endometrial hyperplasia/cancer or other endometrial pathology. The likelihood of positive screening for APUB was associated with increasing BMI (P = .001) and Black/African American race (P = .003), as well as increasing SAMANTA score (P < .001). In contrast, risk of positive screening was negatively associated with increasing age (P < .001).
CONCLUSIONS: Women presenting for metabolic/bariatric surgery have a high prevalence of APUB and, given this dysfunctional bleeding and concurrent obesity, are at greater risk for underlying EC. Potential risk factors for APUB, given their associations with screening positive, include increased body mass index, younger age, and Black/African American race. Standardized screening with appropriate gynecologic referral should be a routine part of the overall evaluation for women with severe obesity.

BACKGROUND: The utility of preoperative abdominal ultrasonography (US) in evaluating patients with obesity before metabolic bariatric surgery (MBS) remains ambiguously defined.
METHODS: Retrospective analysis whereby patients were classified into four groups based on ultrasound results. Group 1 had normal findings. Group 2 had non-significant findings that did not affect the planned procedure. Group 3 required additional or follow-up surgeries without changing the surgical plan. Group 4, impacting the procedure, needed further investigations and was subdivided into 4A, delaying surgery for more assessments, and 4B, altering or canceling the procedure due to critical findings. Machine learning techniques were utilized to identify variables.
RESULTS: Four thousand four hundred eighteen patients\' records were analyzed. Group 1 was 45.7%. Group 2, 35.7%; Group 3, 17.0%; Group 4, 1.5%, Group 4A, 0.8%; and Group 4B, 0.7%, where surgeries were either canceled (0.3%) or postponed (0.4%). The hyperparameter tuning process identified a Decision Tree classifier with a maximum tree depth of 7 as the most effective model. The model demonstrated high effectiveness in identifying patients who would benefit from preoperative ultrasound before MBS, with training and testing accuracies of 0.983 and 0.985. It also showed high precision (0.954), recall (0.962), F1 score (0.958), and an AUC of 0.976.
CONCLUSIONS: Our study found that preoperative ultrasound demonstrated clinical utility for a subset of patients undergoing metabolic bariatric surgery. Specifically, 15.9% of the cohort benefited from the identification of chronic calculous cholecystitis, leading to concomitant cholecystectomy. Additionally, surgery was postponed in 1.4% of the cases due to other findings. While these findings indicate a potential benefit in certain cases, further research, including a cost-benefit analysis, is necessary to fully evaluate routine preoperative ultrasound\'s overall utility and economic impact in this patient population.

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Patients with peripheral arterial disease have an increased risk of developing cardiovascular complications in the postoperative period of arterial surgeries known as Major Adverse Cardiac Events (MACE), which includes acute myocardial infarction, heart failure, malignant arrhythmias, and stroke. The preoperative evaluation aims to reduce mortality and the risk of MACE. However, there is no standardized approach to performing them. The aim of this study was to compare the preoperative evaluation conducted by general practitioners with those performed by cardiologists.
This is a retrospective analysis of medical records of patients who underwent elective arterial surgeries from January 2016 to December 2020 at a tertiary hospital in São Paulo, Brazil. The authors compared the preoperative evaluation of these patients according to the initial evaluator (general practitioners vs. cardiologists), assessing patients\' clinical factors, mortality, postoperative MACE incidence, rate of requested non-invasive stratification tests, length of hospital stay, among others.
281 patients were evaluated: 169 assessed by cardiologists and 112 by general practitioners. Cardiologists requested more non-invasive stratification tests (40.8%) compared to general practitioners (9%) (p < 0.001), with no impact on mortality (8.8% versus 10.7%; p = 0.609) and postoperative MACE incidence (10.6% versus 6.2%; p = 0.209). The total length of hospital stay was longer in the cardiologist group (17.27 versus 11.79 days; p < 0.001).
The increased request for exams didn\'t have a significant impact on mortality and postoperative MACE incidence, but prolonged the total length of hospital stay. Health managers should consider these findings and ensure appropriate utilization of human and financial resources.

BACKGROUND: The preadmission clinic (PAC) is crucial in perioperative care, offering evaluations, education, and patient optimization before surgical procedures. During the COVID-19 pandemic, the PAC adapted by implementing telephone visits due to a lack of infrastructure for video consultations. While the pandemic significantly increased the use of virtual care, including video appointments as an alternative to in-person consultations, our PAC had not used video consultations for preoperative assessments.
OBJECTIVE: This study aimed to develop, implement, and integrate preoperative video consultations into the PAC workflow.
METHODS: A prospective quality improvement project was undertaken using the Plan-Do-Study-Act (PDSA) methodology. The project focused on developing, implementing, and integrating virtual video consultations at London Health Sciences Centre and St. Joseph Health Care (London, Ontario, Canada) in the PAC. Data were systematically collected to monitor the number of patients undergoing video consultations, address patient flow concerns, and increase the percentage of video consultations. Communication between the PAC, surgeon offices, and patients was analyzed for continuous improvement. Technological challenges were addressed, and procedures were streamlined to facilitate video calls on appointment days.
RESULTS: The PAC team, which includes professionals from medicine, anesthesia, nursing, pharmacy, occupational therapy, and physiotherapy, offers preoperative evaluation and education to surgical patients, conducting approximately 8000 consultations annually across 3 hospital locations. Following the initial PDSA cycles, the interventions consistently improved the video consultation utilization rate to 17%, indicating positive progress. With the onset of PDSA cycle 3, there was a notable surge to a 29% utilization rate in the early phase. This upward trend continued, culminating in a 38% utilization rate of virtual video consultations in the later stages of the cycle. This heightened level was consistently maintained throughout 2023, highlighting the sustained success of our interventions.
CONCLUSIONS: The quality improvement process significantly enhanced the institution\'s preoperative video consultation workflow. By understanding the complexities within the PAC, strategic interventions were made to integrate video consultations without compromising efficiency, morale, or safety. This project highlights the potential for transformative improvements in health care delivery through the thoughtful integration of virtual care technologies.

BACKGROUND: Hiatal hernia (HH) is estimated to affect between 20 and 50% of patients undergoing bariatric surgery. However, there is no consensus regarding the preoperative assessment and intraoperative repair of HH. The aim of this study was to evaluate the variation in surgeon assessment and repair of HH during bariatric surgery across a multi-hospital healthcare system.
METHODS: A retrospective cohort analysis was conducted using data obtained from the metabolic and bariatric accreditation quality improvement program (MBSAQIP) and institutional medical records. All adult patients who underwent laparoscopic sleeve gastrectomy (SG) or Roux-en-Y gastric bypass (RYGB) were included. Preoperative assessment of HH was defined as either EGD or upper GI/Esophagram (UGI) within one year of surgery. Surgeons were evaluated individually and by hospital. Chi-square analysis and ANOVA were performed.
RESULTS: From January 2018 to February 2023, 3,487 bariatric surgeries were performed across 4 hospitals and 11 surgeons (2481 SG and 1006 RYGB). HH were concurrently repaired during 24% of operations. The rate of HH repair in SG was 25 and 22% in RYGB (p = 0.06). Preoperatively, 41% of patients underwent EGD and 23% had an UGI. HH was diagnosed in 22% of EGDs. Patients who underwent preoperative EGD had higher rates of HH repair than those without a preop EGD (33% vs. 17%; p < 0.001). The rate of preoperative EGD utilization by surgeon varied significantly from 3 to 92% (p < 0.001) as did HH repair rates between surgeons (range 8-57%; p < 0.001). Even among patients with a preoperatively diagnosed HH, the repair rate ranged 20-91% between individual surgeons (p < 0.001).
CONCLUSIONS: Within a healthcare system there was significant heterogeneity in approach to assessment and repair of HH during bariatric surgery. This appears to be mediated by multiple factors, including utilization of preoperative studies, individual surgeon differences, and differences between hospitals.

BACKGROUND: Preoperative evaluation is important, and this study explored the application of machine learning methods for anesthetic risk classification and the evaluation of the contributions of various factors. To minimize the effects of confounding variables during model training, we used a homogenous group with similar physiological states and ages undergoing similar pelvic organ-related procedures not involving malignancies.
OBJECTIVE: Data on women of reproductive age (age 20-50 years) who underwent gestational or gynecological surgery between January 1, 2017, and December 31, 2021, were obtained from the National Taiwan University Hospital Integrated Medical Database.
METHODS: We first performed an exploratory analysis and selected key features. We then performed data preprocessing to acquire relevant features related to preoperative examination. To further enhance predictive performance, we used the log-likelihood ratio algorithm to generate comorbidity patterns. Finally, we input the processed features into the light gradient boosting machine (LightGBM) model for training and subsequent prediction.
RESULTS: A total of 10,892 patients were included. Within this data set, 9893 patients were classified as having low anesthetic risk (American Society of Anesthesiologists physical status score of 1-2), and 999 patients were classified as having high anesthetic risk (American Society of Anesthesiologists physical status score of >2). The area under the receiver operating characteristic curve of the proposed model was 0.6831.
CONCLUSIONS: By combining comorbidity information and clinical laboratory data, our methodology based on the LightGBM model provides more accurate predictions for anesthetic risk classification.
BACKGROUND: Research Ethics Committee of the National Taiwan University Hospital 202204010RINB; https://www.ntuh.gov.tw/RECO/Index.action.