Evaluating the Quality of Primary Transurethral Resection of Bladder Tumor: A Nine-Year Review at a Tertiary Healthcare Center.

OBJECTIVE: This study aimed to assess the quality of primary transurethral resection of bladder tumor (TURBT) procedures performed at Aga Khan University Hospital (AKUH) over nine years, focusing on proper documentation, completeness of tumor resection, quality of histopathology reports, complication rates, and adherence to European Association of Urology (EAU) guidelines. MATERIALS AND METHODS: A retrospective analysis of patients aged 25-75 who underwent primary TURBT at AKUH between 2010 and 2019 was done. Patients with incomplete records, concomitant procedures, or those who underwent emergency TURBT were excluded. Data was collected on patient demographics, clinical presentation, intraoperative details, and histopathology reports. Statistical analysis was performed using SPSS Version 27.0. RESULTS: 300 patients were initially identified, with 265 meeting the inclusion criteria. The mean age was 61.5 years, with 83% being male. Complete tumor resection was achieved in 35% (n=92) of cases, while deep biopsy was taken in 85% (n=226). Detrusor muscle (DM), a marker of resection quality, was noted in 75% (n=200) of histopathology reports. However, documentation quality varied, with 54% (n=143) of cases lacking clear information on resection completeness. The administration of a single instillation of a chemotherapeutic agent (SICA) was recorded in 79% (n=210) of patients, and the 30-day postoperative complication rate was monitored. CONCLUSION: The study highlights areas for improvement in the quality of TURBT procedures at AKUH, particularly in the documentation of resection completeness and adherence to established guidelines. Ensuring thorough resection and proper documentation is critical to optimizing patient outcomes and future management plans.

To resuscitate or not to resuscitate? The crossroads of ethical decision-making in resuscitation in the emergency department.

Emergency physicians (EPs) working in low-resource settings, where patients mainly bear the cost of healthcare delivery, face many challenges. Emergency care is patient-centered and ethical challenges are numerous in situations where patient autonomy and beneficence are fragile. This review discusses some of the common bioethical issues in the resuscitation and postresuscitation phases of treatment. Solutions are proposed and the necessity for evidence-based ethics and unanimity on ethical standards is emphasized. After a consensus was reached on the structure of the article, smaller groups of authors (2-3) wrote narrative reviews of ethical issues such as patient autonomy and honesty, beneficence and nonmaleficence, dignity, justice, and specific practices and circumstances such as family presence during resuscitation after discussions with senior EPs. Ethical dilemmas were discussed, and solutions were proposed. Cases related to medical decision-making by proxy, financial constraints in management, and resuscitation in the face of medical futility have been discussed. Solutions proposed include the early-stage involvement of hospital ethics committees, financial assurance in place beforehand, and allowing some leverage on a case-to-case basis when care is futile. We recommend developing evidence-based national ethical guidelines and incorporating societal and cultural norms with autonomy, beneficence, nonmaleficence, honesty, and justice principles.

Emerging technology for intraoperative margin assessment and post-operative tissue diagnosis for breast-conserving surgery.

INTRODUCTION: Tissue-preserving surgery is utilized progressively in cancer therapy, where a clear surgical margin is critical to avoid cancer recurrence, specifically in breast cancer (BC) surgery. The Intraoperative pathologic approaches that rely on tissue segmenting and staining have been recognized as the ground truth for BC diagnosis. Nevertheless, these methods are constrained by its complication and timewasting for tissue preparation. OBJECTIVE: We present a non-invasive optical imaging system incorporating a hyperspectral (HS) camera to discriminate between cancerous and non-cancerous tissues in ex-vivo breast specimens, which could be an intraoperative diagnostic technique to aid surgeons during surgery and later a valuable tool to assist pathologists. METHODS: We have established a hyperspectral Imaging (HSI) system comprising a push-broom HS camera at wavelength 380∼1050 nm with source light 390∼980 nm. We have measured the investigated samples' diffuse reflectance (Rd), fixed on slides from 30 distinct patients incorporating mutually normal and ductal carcinoma tissue. The samples were divided into two groups, stained tissues during the surgery (control group) and unstained samples (test group), both captured with the HSI system in the visible and near-infrared (VIS-NIR) range. Then, to address the problem of the spectral nonuniformity of the illumination device and the influence of the dark current, the radiance data were normalized to yield the radiance of the specimen and neutralize the intensity effect to focus on the spectral reflectance shift for each tissue. The selection of the threshold window from the measured Rd is carried out by exploiting the statistical analysis by calculating each region's mean and standard deviation. Afterward, we selected the optimum spectral images from the HS data cube to apply a custom K-means algorithm and contour delineation to identify the regular districts from the BC regions. RESULTS: We noticed that the measured spectral Rd for the malignant tissues of the investigated case studies versus the reference source light varies regarding the cancer stage, as sometimes the Rd is higher for the tumor or vice versa for the normal tissue. Later, from the analysis of the whole samples, we found that the most appropriate wavelength for the BC tissues was 447 nm, which was highly reflected versus the normal tissue. However, the most convenient one for the normal tissue was at 545 nm with high reflection versus the BC tissue. Finally, we implement a moving average filter for noise reduction and a custom K-means clustering algorithm on the selected two spectral images (447, 551 nm) to identify the various regions and effectively-identified spectral tissue variations with a sensitivity of 98.95%, and specificity of 98.44%. A pathologist later confirmed these outcomes as the ground truth for the tissue sample investigations. CONCLUSIONS: The proposed system could help the surgeon and the pathologist identify the cancerous tissue margins from the non-cancerous tissue with a non-invasive, rapid, and minimum time method achieving high sensitivity up to 98.95%.