Background: Good decision making is essential in surgery. In an emergency, the time for decision making is often short, and the information available is incomplete. The way experienced surgeons make decisions is often not well understood, and therefore is difficult to teach to trainees.
Methods: This paper examines how decisions are made, based on recent literature and the experience of the authors and their colleagues.
Discussion: An accurate assessment precedes decision making, and is directed towards the patient, the personnel and environment. Studies of other high-stakes professions have highlighted the existence of two distinct mental processing symptoms. One is fast and frugal, relying on pattern recognition or following a rule or protocol. This is often performed at a subconscious level. The other is a conscious, reasoned, analytical process. This requires adequate, available mental capacity. In reality, expert and experienced decision makers can adopt either or both approaches, and match their approach to the situation. Decisions made need to be constantly reviewed, particularly where there is mismatch between what was anticipated and what is encountered.
Conclusion: An algorithm of decision making in emergency surgery has been developed that is based on assessment, the decision required and the outcome of the decision. The decision must also consider the urgency of the situation and the likely outcome if the plan made fails.
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http://dx.doi.org/10.1111/ans.12193 | DOI Listing |
Ecohealth
January 2025
Health Services Academy, Chak Shahzad, Park Road, Islamabad, 44000, Pakistan.
One Health is an integrative approach aiming to achieve optimal health outcomes by recognizing the interconnection between humans, animals, and the environment. This study explores the understanding, perspectives, hurdles, and implications of intersectoral collaboration within Pakistan's human health system, focusing on One Health principles. A qualitative phenomenological approach was employed, involving 17 key informant interviews with purposively selected stakeholders from public health, agriculture, veterinary medicine, agriculture and environmental science.
View Article and Find Full Text PDFSci Rep
January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orthopaedic and Trauma Surgery, Musculoskeletal University Center Munich (MUM), Campus Grosshadern, Ludwig Maximilians University Munich, Munich, Germany.
In modern knee arthroplasty, surgeons increasingly aim for individualised implant selection based on data-driven decisions to improve patient satisfaction rates. The identification of an implant design that optimally fits to a patient's native kinematic patterns and functional requirements could provide a basis towards subject-specific phenotyping. The goal of this study was to achieve a first step towards identifying easily accessible and intuitive features that allow for discrimination between implant designs based on kinematic data.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Mathematics, Dambi Dollo University, Dambi Dollo, Oromia, Ethiopia.
A novel method for solving the multiple-attribute decision-making problem is proposed using the complex Diophantine interval-valued Pythagorean normal set (CDIVPNS). This study aims to discuss aggregating operations and how they are interpreted. We discuss the concept of CDIVPN weighted averaging (CDIVPNWA), CDIVPN weighted geometric (CDIVPNWG), generalized CDIVPN weighted averaging (CGDIVPNWA) and generalized CGDIVPN weighted geometric (CGDIVPNWG).
View Article and Find Full Text PDFJ Immunother Cancer
January 2025
Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Background: Immune checkpoint inhibitors (ICIs) in combination with antiangiogenic drugs have shown promising outcomes in the third-line and subsequent treatments of patients with microsatellite stable metastatic colorectal cancer (MSS-mCRC). Radiotherapy (RT) may enhance the antitumor effect of immunotherapy. However, the effect of RT exposure on patients receiving ICIs and targeted therapy remains unclear.
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