الفهرس 
Acknowledgement
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Abstract
Summary
Severity scoring systems are designed to provide an estimate of the probability of hospital mortality for critically ill patients. Measuring the severity of illness enables hospital administrators to describe ICU populations and can be helpful in clinical decision-making and guiding resource allocation. Severity adjusted outcomes should not be used only to measure individual ICU performance, but can also be used to compare between ICU. Severity scoring systems have been around for many years now. The Simplified Acute Physiology Score (SAPS) was among the first introduced model, Modified versions of the model has been created since then; SAPS II is the most popular current scales due to its reliability and relative ease of use. Therefore, the aim was firstly to predict mortality rates among critically ill patient admitted to the intensive care units at Assuit University Hospital over a period of one year and secondly, to identify predisposing factors that affect mortality rate in intensive care units. A descriptive research design was used to conduct this study. A convenient sample of all adults critically ill patients over a period of one year started from January 2016 to December 2016. Tools used in this study consisted of three main tools:
Tool one: ”Personal and medical data sheet” Including: - this tool was developed by the researcher after reviewing the related literature’s to assess patient’s demographic data and health relevant data it comprised two parts
A: - Socio-demographic date: which include unit of admission, patient’s code, age, sex, marital status and level of education, date of admission and date of discharge.
B: -Medical data: include history of past medical and surgical problems, causes of ICU admission (respiratory, cardiovascular, trauma, neurology, gastrointestinal, or post-operative cause).
Second tool: - Predisposing factors for hospital mortality of the critically ill patient assessment tool (tool two):
This tool developed by the researcher to assess predisposing factors and causes of death among critically ill patients, including (cardiovascular system disorder, Acute Renal failure, Malignancy, respiratory cause, shock, post-operative complications, and sepsis ….etc.)
Third tool: Hospital mortality prediction scale” using the Simplified Acute Physiology scale (SAPS II score) (tool three)
SAPS II was developed in 1993 to provide a method of converting the obtained score to a probability of hospital mortality. It is the most widely used version and like its predecessor, calculates a severity score using the worst values measured during the initial 24 hours of ICU admission for 17 variables (12 physiologic variable, age, type of admission (scheduled surgical, unscheduled surgical, or medical) and 3 underlying dichotomous disease variables (AIDS, metastatic cancer and hematologic malignancy). SAPS II can be entered into a mathematical formula, which predicts hospital mortality. It has excellent discrimination and calibration and may be suitable for use in the intermediate care unit settings.
The main results:
The study results revealed that more than one third of the study sample were in the age group of (50 ≥ 65 years) and more than half of the samples were male patients (64.0%). Regarding causes of ICU admission, results revealed that Trauma is a major cause of admission followed by elective post-operative admission and respiratory causes (40.3%, 25.7% and 13.7% respectively). As regards discharge criteria more than one third of the study sample were die on discharge while about half of the sample were alive on discharge (274 Vs 326). When comparing both a live and death group related to laboratory data on admission there was a significant difference on serum sodium and creatinine (p value < 0.001) Regard causes of death current study results showed, postoperative complication is 1st leading cause more than one third (33.5%), shock mainly septic shock is 2nd cause of death (32.5%) and respiratory failure is the 3rd most common cause (26.2%). Using SAPS to predict mortality risk on 1st day of admission it founded that the mean score was (33.82 ± 29.28). Regard SAPS II score in predicting discharge outcomes was found that the prediction power of the SAPS II was 79.9%, 86.2%, and 85.6% respectively higher prediction power.
It can be concluded that using SAPS II as a mortality prediction model is very sensitive and beneficial for resource allocation and evaluating nursing care. Based on the finding of the current study, the following recommendations are suggested:
- Use SAPS II as a mortality prediction model among the critically ill patients during ICU stay is strongly recommended.
- Further researches should be conducted in a separated diagnostic group of patients (trauma, cardiology, postoperative patients)