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Esophageal perforations manifest in various clinical forms, influenced by factors such as the perforation's cause and location (cervical, intrathoracic, or intra-abdominal), the extent of contamination, and potential injury to adjacent mediastinal structures. The timing between the perforation occurrence and treatment initiation also affects the clinical presentation.
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Individuals with Barrett's esophagus are often asymptomatic, but they may experience symptoms commonly associated with GERD, such as heartburn and acid regurgitation. Additional symptoms can include difficulty swallowing, chest pain, unintentional weight loss, blood in the stool (which may appear black, tarry, or bloody), and episodes of vomiting.
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Esophageal varices often manifest as gastrointestinal bleeding episodes, presenting symptoms like hematemesis (vomiting of blood), hematochezia (passing fresh blood via the rectum), and melena (black, tarry stools). Other signs can include weight loss, anorexia, abdominal discomfort, jaundice, pruritus, altered mental status, and muscle cramps.
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Patients with esophageal strictures often experience a range of symptoms. Initially, they may have difficulty swallowing solid foods, which can progress to include liquids. Additional symptoms may involve chest pain or discomfort, regurgitating food and fluids, heartburn, unintentional weight loss, coughing or choking during meals, and hoarseness.
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Acute pancreatitis presents a complex medical emergency characterized by rapid onset inflammation of the pancreas, demanding timely diagnosis and management to prevent complications. The condition primarily manifests through severe upper abdominal pain that often radiates to the back. This pain intensifies following the consumption of fatty foods. Accompanying symptoms such as nausea, vomiting, abdominal distention, fever, dyspnea, cyanosis, and jaundice can vary in intensity but significantly...
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Related Experiment Video

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Clinical decision support tool for Co-management signalling.

Alexandra Bayão Horta1, Cátia Salgado2, Marta Fernandes2

  • 1NOVA Medical School, Faculdade de Ciências Médicas, Campo Mártires da Pátria, 130, 1169-056 Lisboa, Portugal; Hospital da Luz-Lisboa, Av. Lusíada, 100, 1600-650 Lisboa, Portugal.

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|April 1, 2018
PubMed
Summary

A new decision tool aids in selecting surgical patients for co-management, improving care objectivity. This predictive model uses four preoperative variables to identify patients benefiting from internist-surgeon collaboration.

Keywords:
Co-managementDecision support toolFailure to rescueHigh risk patientsInternal MedicineMultistage modelling

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Area of Science:

  • Clinical Medicine
  • Surgical Oncology
  • Health Informatics

Background:

  • Co-management between internists and surgeons is crucial for modern hospital patient care.
  • Identifying suitable candidates for co-management is essential for optimizing clinical outcomes.

Purpose of the Study:

  • To develop a decision support tool for offering co-management services to selected surgical patients.
  • To utilize real-world preoperative patient data for creating a predictive model.

Main Methods:

  • Retrospective analysis of electronic health records from colorectal surgery patients (2012-2014).
  • Inclusion criteria: adult patients (≥18 years) with specific colorectal surgery ICD-9 codes, excluding those with multiple procedures.
  • Development of predictive models using logistic regression and Takagi-Sugeno fuzzy modeling.

Main Results:

  • A cohort of 344 adult patients undergoing 398 surgeries was analyzed, with 54 exclusions.
  • Four key preoperative variables were identified as most predictive of co-management need.
  • The validated model demonstrated strong performance: 0.81 AUC, 77% accuracy, 74% sensitivity, 78% specificity, and 93% NPV.

Conclusions:

  • A prediction model based on preoperative characteristics was developed to guide co-management decisions.
  • The tool is a simple, bedside decision aid utilizing only four numerical variables.
  • The findings suggest that co-management decisions can be made more objective and potentially automated.