Distal pancreatectomy (DP) represents the best therapeutic option for patients with body-tail pancreatic neoplasms (PNs). The enhanced recovery after surgery protocol is widely used for treating patients with PN to speed up postoperative recovery. This study aims to describe our institute's experience in the application of fast recovery protocol in a cohort of patients treated with DP, identifying predictors facilitating a decrease in the length of hospital stay. Were retrospectively enrolled 60 consecutive cases of DP performed from January 2016 to June 2022 in patients treated with enhanced recovery protocol, 25% of them were treated with spleen preserving procedure. Single-variable logistic regression models were used to evaluate the potential association between patient characteristics and the probability of postoperative complications. Standard linear regression models were used for length of stay, number of postoperative days (PODs) from surgery to full bowel function recovery, and PODs to the interruption of intravenous analgesia administration. Thirty-four (57%) patients underwent open surgery and 26 (43%) laparoscopic surgery. Patients who underwent laparoscopic surgery and spleen-preserving procedures experienced a lower complication rate ( = .037), shorter length of stay, and time of analgesic requirements. With single-variable logistic regression models patients treated with laparoscopic surgery had statistically significant higher recovery times in terms of nasogastric tube removal ( = .004) and early enteral nutrition ( = .001). Continual refinement with enhanced recovery protocol for treating PN patients based on perioperative counseling and surgical decision-making is crucial to reduce patient morbidity and time for recovery.
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http://dx.doi.org/10.1089/lap.2023.0445 | DOI Listing |
Background: Alzheimer's disease is the most dreaded multifactorial neurological illness for which there is currently no known treatment. Although the exact cause of AD is still unknown, several factors related to lifestyle, genetics, and environment are known to have a significant role in the disease's development. Alzheimer's disease is characterized by neuronal loss, neurofibrillary tangles, and senile plaques.
View Article and Find Full Text PDFBackground: A 73-year-old female with a 3 year history of Alzheimer's disease was treated within the protocol of The Alzheimer's Autism and Cognitive Impairment Stem Cell Treatment Study (ACIST), an IRB approved clinical study registered with clinicaltrials.gov NCT03724136.
Method: The procedure consists of bone marrow aspiration, cell separation using an FDA cleared class 2 device, and intravenous and intranasal administration of the stem cell fraction.
Ann Surg
January 2025
Division of Colorectal Surgery, Department of Surgery, Brigham and Women's Hospital, Harvard Medical School; Boston, MA, USA.
Objective: To explore the association of socioeconomic status (SES) and race/ethnicity with perioperative metrics within the Enhanced Recovery After Surgery (ERAS) framework to identify gaps for equity-informed improvements.
Summary Background Data: Although ERAS pathways improve perioperative outcomes through standardized care, disparities in protocol adherence and postoperative outcomes persist, particularly for vulnerable populations.
Methods: We conducted a retrospective cohort study using a single-institution database of elective colorectal surgeries (2018-2021).
J Magn Reson Imaging
January 2025
Department of Radiology, Fortis Memorial Research Institute, Gurugram, India.
Background: Isocitrate dehydrogenase (IDH) wild-type (IDH) glioblastomas (GB) are more aggressive and have a poorer prognosis than IDH mutant (IDH) tumors, emphasizing the need for accurate preoperative differentiation. However, a distinct imaging biomarker for differentiation mostly lacking. Intratumoral thrombosis has been reported as a histopathological biomarker for GB.
View Article and Find Full Text PDFJ Surg (Lisle)
November 2024
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Purpose: Appropriate opioid management is crucial to reduce opioid overdose risk for ICU surgical patients, which can lead to severe complications. Accurately predicting postoperative opioid needs and understanding the associated factors can effectively guide appropriate opioid use, significantly enhancing patient safety and recovery outcomes. Although machine learning models can accurately predict postoperative opioid needs, lacking interpretability hinders their adoption in clinical practice.
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