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Bladder cancer is the sixth most common cancer in the United States. Although cure rates are high when malignancy is in situ, survival rates drop significantly if disease is locally invasive or has metastasized. 1 Therefore, an urgent need exists to develop additional therapeutic options for advanced-stage bladder cancer and optimize the process of connecting patients to these treatments.

Background Preventable morbidity and mortality among emergency surgery patients is not adequately analyzed. We aim to describe and classify preventable complications and deaths in this population. Methods The medical records and quality control documents of patients with emergency, non-trauma, surgical disease admitted between September 1, 2006, and August 31, 2018, and recorded to have a preventable or potentially preventable morbidity and mortality were reviewed. The primary outcome was a classification of the complications and deaths by a panel of experts, as attributable to issues of personal performance or system deficiencies. Results One hundred and fifty patients were identified (127 complications and 23 deaths). The most commonly encountered preventable complications were surgical-site infection (17%), bleeding (13%), injury to adjacent structures (12%), and anastomotic leak (8%). The majority of complications seemed to stem from personal performance (97%), due to either technical or judgment issues, and only 3% were linked with system flaws, either in the form of communication or inadequate protocols. Alcohol use disorder and duration of operation were different between patients with preventable adverse events related to technical issues and patients related to judgment issues; furthermore, more patients who experienced judgment issues died during hospital stay (p \0.05). Conclusion Among emergency surgery patients, who suffer preventable complications and deaths, issues related to personal performance are more frequent than system flaws. Whereas the effort to improve systems should be unwavering, the emphasis on the surgeon's personal responsibility to avoid preventable complications should not be derailed.

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Background Complex machine learning (ML) models have revolutionized predictions in clinical care. However, for laparoscopic colectomy (LC), prediction of morbidity by ML has not been adequately analyzed nor compared against traditional logistic regression (LR) models. Methods All LC patients, between 2017 and 2019, in the National Surgical Quality Improvement Program (NSQIP) were identified. A composite outcome of 17 variables defined any post-operative morbidity. Seven of the most common complications were additionally analyzed. Three ML models (Random Forests, XGBoost, and L1-L2-RFE) were compared with LR. Results Random Forests, XGBoost, and L1-L2-RFE predicted 30-day post-operative morbidity with average area under the curve (AUC): .709, .712, and .712, respectively. LR predicted morbidity with AUC = .712. Septic shock was predicted with AUC ≤ .9, by ML and LR. Conclusion There was negligible difference in the predictive ability of ML and LR in post-LC morbidity prediction. Possibly, the computational power of ML cannot be realized in limited datasets.

Study question How do different sperm preparations, such as simple-wash (SW) and density-gradient (DG), impact intrauterine insemination (IUI) outcomes among women seeking fertility treatments? Summary answer Using a population from a large, academic medical center, this study discerned no differences in pregnancy outcomes between SW and DG sperm preparations. What is known already IUI with or without ovulation induction (OI) is often a first-line treatment among couples seeking fertility services. SW and DG are two common methods used to prepare sperm for IUI. In comparison to its latter counterpart, the SW technique is lesser-used, yet is more time-efficient, and cost-effective due to its utilization of only a single centrifugation step. Since the impact of sperm preparation techniques on the post-processing sperm yield and its parameters varies by the method used, the cycle outcomes might differ as well. However, limited data exists on various sperm preparations’ impact on IUI clinical outcomes. Study design, size, duration Data from 3378 IUI+OI cycles (from 1503 women of all diagnoses seeking IUI with fresh-ejaculated sperm) that took place at a large academic fertility center between 9/2014 and 3/2021 were retrospectively reviewed. Cycles were either unstimulated (natural) or stimulated with either oral OI agents (clomiphene-citrate & letrozole) or gonadotropins. Cycles were divided in two groups based on sperm preparation technique: SW (n = 1691) and DG (n = 1687) and outcomes were compared between them. Participants/materials, setting, methods Sperm preparation: SW semen were mixed in 10ml MHM (FujiFilm) and centrifuged for 10min. DG semen were layered over 45:90 gradient of Isolate (FujiFilm), centrifuged for 20min, and washed twice (10min) in 10ml MHM. Outcome measures: hCG-positivity (posHCGR), clinical pregnancy (CPR), spontaneous abortion (SABR), and livebirth rates/cycle (LBR). Statistics: Logistic regression with Odds Ratios (OR) adjusted for both partners’ ages, day-3 FSH, stimulation, and sperm score (poor, fair, good, excellent). Sub-analysis limited cohort to first-cycles only.   Main results and the role of chance Groups were comparable in patient [age (maternal, paternal), BMI, day-3 FSH, infertility diagnosis], and cycle characteristics [follicular response (measured as number of preovulatory follicles), and endometrial thickness]. Preprocessing sperm parameters differed slightly with higher mean sperm concentrations and lower total motility among SW cycles (75.3 + 57.0 vs. 71.0 + 51.3 million, p = 0.02; 48.6 + 19.6 vs. 52.5 + 20.2, p < 0.001, for SW and DG, respectively). posHCGR, CPR, SABR, and LBR per cycle did not differ between groups (15.8% vs. 15.4%, p = 0.76;13.7% vs. 13.2%, p = 0.62;18.1% vs. 18.5%, p = 0.93; 9.5 vs. 8.9%, p = 0.56; for SW and DG, respectively). Odds for posHCG, CP, SAB, or LB did not differ between groups [adjOR(95%CI): 1.05(0.87-1.26), p = 0.65; 1.10(0.67-1.83), p = 0.71; 0.98(0.60-1.60), p = 0.94; 1.08(0.85-1.37), p = 0.66, respectively]. When cycles were stratified by type of ovarian stimulation, rather than adjusted for it, no difference was seen in any of the clinical outcomes within individual strata{adjOR(95%CI): [Oral OI: 1.00(0.74-1.37), p = 0.98; 1.78(0.68-4.61), p = 0.25; 0.97(0.40-2.38), p = 0.95; 1.05(0.72-1.53), p = 0.81], [Gonadotropins: 0.99(0.78-1.28), p = 0.96; 0.93(0.49-1.77), p = 0.83; 0.97(0.52-1.80), p = 0.96; 1.03(0.75-1.41), p = 0.87], [Natural: 2.36(0.97-5.76), p = 0.06; 0.08(0.001-6.84), p = 0.26; 0.20(0.003-11.02), p = 0.43; 2.52(0.63-10.00), p = 0.19], for posHCG, CP, SAB, and LB, respectively}. Similarly, no difference was seen in any of the clinical outcomes when cycles were stratified by sperm score or when analysis was limited to first-cycles only. Limitations, reasons for caution LBR were calculated excluding pregnancies with no information after discharge to obstetrics (approximately 16%). Although not significant, there might be minor variations in individual provider’s practices between time frames in which these techniques were implemented. Wider implications of the findings SW is a much simpler, time-efficient, and cost-effective sperm processing technique for IUI compared to DG, however remains infrequently utilized. Adoption of SW, over DG, could yield comparable clinical efficacy, yet optimize teamwork flow and lower healthcare costs, due to its non-labor-intensive and inexpensive nature. Trial registration number not applicable

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