Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Analysis on the Constitution of Systemic Diseases and the Causes of Death in 154 Cases of Post-Operative Death of Patients in a Hospital
0
Zitationen
3
Autoren
2013
Jahr
Abstract
Objective. To analyze the constitution of systemic diseases and the causes of death in 154 cases of patients who died after operation in a hospital, and provide evidence for decreasing the post-operative death rate of patients. The HIS system was adopted to collect the hospitalization information of 154 cases of patients who died after operation, for retrospective investigation. Result. In the 154 cases of patients who died post-operatively, there were more males than females (P < 0.01); the main systemic diseases of these patients were circulatory system disease, injury, poisoning and other consequences of external causes, malignant tumors and digestive system diseases; the reasons for post-operative death were that complications occurred after operation and the relatives gave up post-operative treatment after. Conclusion. Of the deceased patients, the number of male patients was more than that of female patients; the death rates due to circulatory system disease, injury, poisoning and other consequences of external causes were higher than death caused by other systemic diseases. Complications after operation and abandonment of treatment were the main reasons. The medical staff should research and attach great importance to the challenges of avoiding and dealing with complications immediately and correctly, increase the surgical survival rate and long term survival rate and guarantee excellent survival quality; one of the most important measures to guarantee the health of the people of a nation or region is to continuously increase the medical investment in health care.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.391 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.257 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.685 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.501 Zit.