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6 versus 76.6 mins, P= 0.449) on adjusted analysis. selleck Patients with LCO compared to open procedures had similar LOS (4 versus 4, P= 0.334) and morbidities (14.3% versus 16.6%, P= 0.358), but longer operative times (90.1 versus 76.6 mins, P= 0.002) on adjusted analysis. Patients with laparoscopic and LCO procedures had fewer unplanned intubations compared to open procedures (0.0% versus 0.0% versus 2.4%, P= 0.011) and lower mortality (0.0% versus 0.0% versus 1.7%, P= 0.046) on univariate analysis.

Laparoscopic MD resection has shorter LOS and similar complications and operative time compared to an open approach while LCO resection increases operative time but not LOS or morbidities.

Laparoscopic MD resection has shorter LOS and similar complications and operative time compared to an open approach while LCO resection increases operative time but not LOS or morbidities.

Machine learning (ML) has garnered increasing attention as a means to quantitatively analyze the growing and complex medical data to improve individualized patient care. We herein aim to critically examine the current state of ML in predicting surgical outcomes, evaluate the quality of currently available research, and propose areas of improvement for future uses of ML in surgery.

A systematic review was conducted in accordance with the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) checklist. PubMed, MEDLINE, and Embase databases were reviewed under search syntax “machine learning” and “surgery” for papers published between 2015 and 2020.

Of the initial 2677 studies, 45 papers met inclusion and exclusion criteria. Fourteen different subspecialties were represented with neurosurgery being most common. The most frequently used ML algorithms were random forest (n=19), artificial neural network (n=17), and logistic regression (n=17). Common outcomes included postoperative mortality, complications, patient reported quality of life and pain improvement. All studies which compared ML algorithms to conventional studies which used area under the curve (AUC) to measure accuracy found improved outcome prediction with ML models.

While still in its early stages, ML models offer surgeons an opportunity to capitalize on the myriad of clinical data available and improve individualized patient care. Limitations included heterogeneous outcome and imperfect quality of some of the papers. We therefore urge future research to agree upon methods of outcome reporting and require basic quality standards.

While still in its early stages, ML models offer surgeons an opportunity to capitalize on the myriad of clinical data available and improve individualized patient care. Limitations included heterogeneous outcome and imperfect quality of some of the papers. We therefore urge future research to agree upon methods of outcome reporting and require basic quality standards.

Unplanned hospital readmissions are associated with morbidity and high cost. Existing literature on readmission after trauma has focused on how injury characteristics are associated with readmission. We aimed to evaluate how psychosocial determinants of health and complications of hospitalization combined with injury characteristics affect risk of readmission after trauma.

We conducted a retrospective cohort study of adult trauma admissions from July 2015 to September 2017 to Harborview Medical Center in Seattle, Washington. We assessed patient, injury, and hospitalization characteristics and estimated associations between risk factors and unplanned 30-d readmission using multivariable generalized linear Poisson regression models.

Of 8916 discharged trauma patients, 330 (3.7%) had an unplanned 30-d readmission. Patients were most commonly readmitted with infection (41.5%). Independent risk factors for readmission among postoperative patients included public insurance (adjusted Relative Risk (aRR) 1.34, an injury characteristics. Improved social support and follow-up after discharge for high-risk patients may facilitate earlier identification of postdischarge complications.

It is difficult to distinguish between a tumor and its liver segment with traditional use of indocyanine green (ICG) alone. In the present study, a method was used to limit ICG to the liver segment adjacent to a tumor. A spectrally-distinct fluorescently-labeled tumor-specific antibody against human carcinoembryonic antigen-related cell-adhesion molecules was used to label the metastatic tumor in a patient-derived orthotopic xenograft mouse model to enable color-coded visualization and distinction of a colon-cancer liver metastases and its adjacent liver segment.

Nude mice received surgical orthotopic implantation in the liver of colon-cancer liver metastases derived from two patients. An anti- carcinoembryonic antigen-related cell-adhesion molecules monoclonal antibody (mAb 6G5j) was conjugated to a near-infrared dye IR700DX (6G5j-IR700DX). After three weeks, mice received 6G5j-IR700DX via tail-vein injection 48 hours before surgery. ICG was intravenously injected after ligation of the left or left lateral Glissonean pedicle resulting in labeling of the segment with preserved blood-flow in the liver. Imaging was performed with the Pearl Trilogy and FLARE Imaging Systems.

The metastatic liver tumor had a clear fluorescence signal due to selective tumor targeting by 6G5j-IR700DX, which was imaged on the 700 nm channel. The adjacent liver segment, with preserved blood-flow in the liver, had a clear fluorescence ICG 800 nm signal, while the left or left lateral segment had no fluorescence signal. Overlay of the images showed clear color-coded differentiation between the tumor fluorescing at 700 nm and the adjacent liver segment fluorescing at 800 nm.

Color-coding of a liver tumor and uninvolved liver segment has the potential for improved liver resection.

Color-coding of a liver tumor and uninvolved liver segment has the potential for improved liver resection.

The optimal laparoscopic appendectomy approach is not clear, comparing single site laparoscopic appendectomy (SILA) to conventional 3-port appendectomy (CLA). We investigated outcomes in pediatric patients comparing SILA to CLA length of operation, length of stay, time to resumption of regular diet, follow up, rehospitalization, and cost.

Data was collected from children 1 to 18 years with appendectomy at Loma Linda University from 2018 to 2020, operated by two surgeons. Analysis utilized two-sample T, chi-squared, and Fisher’s exact tests.

Of 173 patients, 77 underwent SILA and 96 had CLA. There was no gender, age, or race difference between groups. Mean WBC was 17.5×10

/mL in SILA group, compared to 15.3×10

/mL in CLA group (P=0.004). Operative time was 47.0 SILA compared to 49.5 minutes CLA (P=0.269). Of SILA cases, 55.8% were simple appendicitis, while 53.3% of the CLA cases were simple (P=0.857). Regular diet was resumed after 1.7 days in the SILA group, 1.1 days in CLA (P=0.018). Length of stay was 2.