Background: Methods for improving the safety of medical treatments for patients, reducing the occurrence of postoperative complications and optimizing medical resources for primary hip replacement are needed. Previous literature has mostly analysed the risk factors and constructed and models to predict a transfer to the ICU after surgery, and no reports on preoperative ICU reservations have been found. This study evaluated the risk factors for preoperative ICU reservation and considered the necessity of preoperative ICU reservations to optimize preoperative communication, enable a seamless transfer between the operating room and ICU, reduce postoperative complications and shorten hospital stays.
Methods: We extracted the data of 1488 patients who underwent hip replacement from the hospital case database from November 2017 to May 2021 and used the case-control test to divide the patients into the case group (scheduled ICU admission, 134 cases) and the control group (Not scheduled ICU admission, 213 cases). The general conditions of the patients before surgery, including sex, age, Charlson comorbidity index, laboratory test results, and anaesthesia methods, were collected and used as independent variables. The t test, rank sum test, and X test were used to analyse and identify significant factors with a P < 0.05. Then, these factors were entered into binary logistic regression analysis, and a ROC curve was used to test the efficacy of the regression model.
Results: In the data we collected, 134 patients were planned to be transferred to the ICU, and 213 patients were not transferred to the ICU. The two groups of data were analyzed by logistic regression. We defined the risk factors for preoperative ICU appointment in patients with primary hip arthroplasty, including age. (odds ratio (OR) 1.066, 95% (confidence interval) CI (1.039, 1.093), P < 0.001), general anesthesia ( (OR) 1.821, 95%CI (1.165, 2.845), P = 0.008), preoperative C-reactive protein ((OR) 1.016, 95%CI (1.010, 1.022), P < 0.05), preoperative alanine aminotransferase ((OR) 1.042, 95%CI ((1.016, 1.070)), P = 0.002). These were promoting factors for preoperative ICU appointment,and preoperative albumin ((OR) 0.0839, 95%CI (0.792, 0.889)), P < 0.05) was a protective factor for ICU appointment.
Conclusion: For patients requiring primary hip replacement. Age, general anesthesia, preoperative C-reactive protein, preoperative alanine aminotransferase and preoperative albumin are the key points of our preoperative assessment. Paying attention to the changes of these indicators will help surgeons assess the patient's condition and contact the ICU in advance.These data can be fully understood by the patients' families, reduce the unnecessary use of medical resources, and optimize perioperative management.
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http://dx.doi.org/10.1186/s12871-022-01737-y | DOI Listing |
J Perioper Pract
January 2025
Department of Nursing, Nippon Kokan Hospital, Kanagawa, Japan.
Intensive care unit patients often experience memory disturbances, including missing or delusional memories. These memory distortions can contribute to the development of psychiatric disorders, such as anxiety and depression. In addition, distorted memories may adversely affect long-term quality of life.
View Article and Find Full Text PDFNurs Crit Care
January 2025
College of Health Sciences, American University of the Middle East, Kuwait, Kuwait.
Background: In healthcare settings, particularly in intensive care units, nurses face significant stress due to the high demands of their job. This stress can impact their job satisfaction, mental health, and overall quality of life. Emotional intelligence has been identified as a crucial factor that can mitigate workplace stress and enhance job satisfaction.
View Article and Find Full Text PDFJ Med Syst
January 2025
Department of Anesthesiology and Pain Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.
Optimizing operating room (OR) utilization is critical for enhancing hospital management and operational efficiency. Accurate surgical case duration predictions are essential for achieving this optimization. Our study aimed to refine the accuracy of these predictions beyond traditional estimation methods by developing Random Forest models tailored to specific surgical departments.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
ETH Zurich, Zurich, Switzerland.
Background: The escalating global scarcity of skilled health care professionals is a critical concern, further exacerbated by rising stress levels and clinician burnout rates. Artificial intelligence (AI) has surfaced as a potential resource to alleviate these challenges. Nevertheless, it is not taken for granted that AI will inevitably augment human performance, as ill-designed systems may inadvertently impose new burdens on health care workers, and implementation may be challenging.
View Article and Find Full Text PDFCurr Opin Clin Nutr Metab Care
December 2024
Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital.
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Recent Findings: Research comparing different feeding schedules in critically ill adults remains limited.
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