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spital mortality of patients who remained in ICU for more than 10 days (5.4% of the whole population) was 33%, compared to 1.5% of patients who had been transferred earlier than 10 days. Holmes’s data (27), show that hospital mortality is 33.3% for patients hospitalised in intensive care unit for over 48 hours (7.2% of the whole population). In our experience, by increasing the threshold of length of stay in intensive care, we observed that the rate of patients decreases (21.3% were in ICU for over 48 hours, 6.1% for over 5 days and 3.3% for over 10 days) and hospital and follow-up mortality increases (0.8% for patients for ICU stay less than 48 hours, 12.5% for hospitalisations longer than 48 hours, 36.6% for stay longer than 5 days and 50% for stay longer than 10 days). In a more recent study, Stricker(24) has observed an in-hospital mortality of 9.8% with 7-days ICU-LOS (A). For surviving patients, a greater incidence of complications, which involves a prolonged hospitalisation, affects post-discharge quality of life; two months after coronary surgery, the Duke Activity Status Index‘s median value on the 50 patients who were discharged after 10 days of intensive care was 26 against 58 expected value (17). Resources consumption by patients with a prolonged stay in intensive care unit The prolongation of a patient’s stay in intensive care involves a remarkable increase in costs per single hospitalisation and a disproportionately high use of reanimation beds for a long period of time versus non complicated patients [Table 11]. Lahey observed that even though patients hospitalised for over 14 days are only 10% of the population, they cost, on the whole, more than the remaining 90% of patients, hospitalised for less than 14 days (11,480,000 US $ against 10,735,000 US$). Bashour’s study (17) shows that 5.4% of the patients hospitalised in Intensive Care Unit (ICU) for over 10 days consume almost half of the total resources used in ICU and 23% of the overall resources spent for the postoperative stay. If patients are classified according to the occurrence [Table 12] of complications during the postoperative period, Magovern (28) in 1996 observed that 48% of patients has no complications and uses 32% of resources, 40% has at least one minor complication but no major complications and uses 41% of resources and 12% has at least one major complication and consumes 27% of resources. In our experience [Table 13], a direct cost analysis performed only on the population of 288 patients who underwent coronary artery bypass surgery demonstrated that whereas 233 patients (81%) with less than 2 days of ICU-LOS consumed 69.6% of costs, 55 patients (19%) who stayed in intensive care for over 2 days consumed 30.4% of costs. LOS POPULATION TOTAL COST US$ 14 D 10% 11,480,000 COMPLICATIONS % OF PATIENTS % RESOURCES CONSUMPTION None 48 32 1 minor 40 41 1 major 12 27 ICU-LOS (DAYS) TOTAL NO. PTS = 288 % RESOURCES 2 55 (19%) 30,4 (A) In these studies, care in ICU is offered for all types of surgical and medical patients, not only for cardiac surgery patients. P. Pinna Pintor et al. Risk prediction in heart surgery Tab. 11 Relationship between length of stay and total costs. Lahey 1992 (22). Tab. 12 Relationship between complications occurred during intervention and resource consumption. Magovern 1996 (26). Tab. 13 Relationship between ICU-LOS and % of total direct costs. Personal data. 13
14 Giornale Italiano di Cardiologia Pratica It J Practice Cardiol Ottobre 2003 Tab. 14 Correlation between logistic EuroSCORE and both Costs and ICU-LOS. Personal data. For a unit rise of EuroSCORE: 2.6% of costs increase and 4.5 hours increase of LOS-ICU Risk factors of prolongation of intensive care and in-hospital stay Considering the unfavourable course and the disproportionately high consumption of resources by the patients with a long stay in intensive care, research into preoperative and intraoperative risk factors predicting the risk of complications and the length of stay well deserves the attention of heart surgeons and Health administrators. Some au- Costs (€) 25000 20000 15000 10000 5000 0 COSTS ICU-LOS thors demonstrated a correlation between Parsonnet’s mortality risk scores or other models and the duration of stay in hospital or intensive care. Other authors preferred to develop original models after proving the poor accuracy of mortality risk models to the purpose of predicting the length of stay. More recently we have demostrated that EuroSCORE can predict both LOS and Costs [Table 14]. p
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