Hippokratia 2016, 20(1):38-43
Uzman S1, Yilmaz Y1, Toptas M1, Akkoc I1, Gul YG2, Daskaya H1, Toptas Y3
1Department of Anesthesiology and Reanimation, Haseki Training and Research Hospital, Istanbul, 2Department of Anesthesiology and Reanimation, Bilgi University Health Sciences School, Istanbul, 3Department of Anesthesiology and Reanimation, Sakarya Training and Research Hospital, Sakarya, Turkey
Background: The aim of this retrospective study was to evaluate postoperative patients admitted to the intensive care unit (ICU) and to describe their characteristics and outcomes. Methods: We performed a retrospective chart review of 1,756 postoperative patients admitted to the ICU of a tertiary referral hospital from January 2008 to December 2012. For each patient we recorded: demographic data, reason for admission to the ICU, duration of mechanical ventilation, elective versus emergency surgery, type of anaesthesia, American Society of Anesthesiologists (ASA) physical status, Acute Physiology and Chronic Health Evaluation (APACHE) II score, Glasgow Coma Score (GCS), and outcome. Results: During the study period, the rate of postoperative ICU admission increased each year, and the number of ICU beds was increased in order to perform a greater number of elective surgical procedures for patients who required postoperative ICU care. In 2008, 20.80 % of the patients were postoperatively admitted to the ICU; 58.97 % were in 2012. The mean ratio of five years was 46.97 %. Median age was 63 (1-94) years, and 57.4 % of the patients were male. The most common reasons for admission were major surgery (41.90 %) and comorbidities (34.10 %). Mortality rates were higher in patients that underwent emergency surgery, received general anesthesia, were operated on by a general surgeon, or had low GCS scores coupled with high ASA or APACHE II scores. Conclusions: The postoperative patients who had metabolic or hemodynamic instability, high ASA or APACHE II scores, and low GCS had higher mortality rates despite ICU care. Hippokratia 2016, 20(1): 38-43
Key words: Surgical intensive care, postoperative care, critical care, postoperative complications
Corresponding author: Sinan Uzman, MD, Haseki Training and Research Hospital, Department of Anesthesiology and Reanimation, Adnan Adivar C, Fatih, Istanbul, Turkey, tel: + 905055645271, fax: + 902125294453, e-mail: email@example.com
In developed countries, patients undergoing high-risk, noncardiac surgery constitute a significant part of intensive care unit (ICU) admissions1,2. Although some scoring systems such as POSSUM and P-POSSUM were used to identify patients who required ICU admission following surgery, it is difficult to determine accurately which postoperative patients are at high risk of complications or death3-5. Even though the high-risk surgical population comprises a small part of the population that undergoes surgical procedures, the majority of postoperative complications and deaths are observed among high-risk surgical patients, and only one-third of these cases are admitted to the ICU after surgery6.
Postoperative outcomes are related to patient factors and the nature of the surgery5,7. Previous studies suggest that postoperative care in the ICU may substantially reduce postoperative morbidity and mortality due to the early recognition and proper management of postoperative complications5-8.
ICU beds are a scarce hospital resource, and various factors affect the decision to admit a patient to the ICU, including severity of co-existing disease, need for ICU-specific interventions, or bed availability5,9. There are several guidelines for ICU admissions, but no universally accepted criteria for admitting surgical patients to the ICU8. We believe that characterizing the surgical patients in the ICU will help to identify those patients who require postoperative ICU treatment; however, we aimed to assess retrospectively ICU admissions following noncardiac surgery.
Material and methods
The study was performed in the medical-surgical ICU of the Haseki Research and Training Hospital, a referral hospital with 600 beds in Istanbul, Turkey. Before 2010, the ICU had 15 beds; after 2010, there were 26 beds. General, urologic, orthopedic, obstetric and gynecological, ear-nose-throat, neurological, ophthalmic, and peripheral vascular surgical procedures were carried out in the hospital. The study protocol was approved by the Local Hospital Ethics Committee (No 114/2-5-2014) and conducted according to the Declaration of Helsinki. Postoperative patients that were directly admitted to the ICU from the operating room (OR) from 1 January 2008 to 31 December 2012, were included in this retrospective study. Patients that were readmitted to the ICU were excluded, and only the first admission was considered for the analysis. Study data were obtained from medical chart review and the ICU audit database. Data extracted from the audit database were provided using hospital computer software (Probel, Probel Corp. Cankaya, Izmir, Turkey). Data were collected by all the researchers, and were organized by the first author. For each patient we recorded: demographic data, surgical service, reasons for admission to the ICU, duration of mechanical ventilation, emergency or elective status of surgery, type of anaesthesia, American Society of Anesthesiologists (ASA) physical status, Acute Physiology and Chronic Health Evaluation (APACHE) II score, Glasgow Coma Score (GCS), and outcome.
Statistical analysis was made with the Statistical Package for Social Sciences (SPSS) software, version 15.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics were given as numbers and percentages for categorical variables or as the mean ± standard deviation and median (minimum-maximum) for numeric variables. Comparisons between two independent groups were performed with Student’s t-test when the numeric variables were normally distributed or with the Mann-Whitney U test when they were not. Comparisons of numerical variables between more than two independent groups were performed with one-way ANOVA when the numeric variables were normally distributed or with Kruskal-Wallis test when they were not. The Kolmogorov-Smirnov test was used to assess whether the distribution was normal. When overall significance was observed, pairwise post hoc tests were performed using Tukey’s test or the Mann-Whitney U test with Bonferroni correction. The ratios of the categorical variables between the groups were analyzed with Chi-Square analysis. The relationships between numeric variables were evaluated with the Spearman correlation analysis because the parametric test condition could not be established. A p value <0.05 was considered statistically significant.
During the study period, 3,738 patients were admitted to the ICU, and 1,756 of them were postoperative patients (46.98 %). The number of intensive care beds (15 beds in 2008 and 26 beds in 2010 and thereafter) and the number of postoperative patients admitted to the ICU gradually increased over the years. Their percentages of the total patients were 21 % (n =77) in 2008, 22 % (n =164) in 2009, 47 % (n =444) in 2010, 50 % (n =409) in 2011, and 58 % (n =662) in 2012. Mean age was 60.4 ± 17.4 years, and 57.6 % of the patients were male (47.4 % were female). Mean age and sex did not show significant differences between the years (p =0.081 and p =0.056, respectively). Analysis of the patients by department showed that they most commonly underwent general surgery (36.8 %), neurosurgery (22.7 %), or orthopedic and traumatology surgical procedures (14.1 %). There were no significant differences between the years. Among all the postoperative patients admitted to the ICU, 16.3 % underwent emergency operations and 83.7 % elective operations. There was a statistically significant difference in the type of surgery between the years (p <0.001). The increase in the ratio of elective admissions was noteworthy. The operations were performed under general anesthesia in 85.8 % of the patients and regional anesthesia in 14.2 %. Comparison of anesthesia methods according to the years did not reveal a significant difference (p =0.067). There were no significant differences between the years with respect to indications for admission to the ICU (p =0.224). After the ICU, 85.4 % of the patients were discharged to the ward and 14.6 % died in the ICU (Table 1).
Mortality was higher in patients who underwent emergency operations, surgery under general anesthesia, developed perioperative arrest, or had hemodynamic or metabolic instability, high ASA or APACHE II scores, or low GCS scores. The ratios of patients who died were significantly higher in general surgery, neurosurgery, obstetric and gynecological operations (Table 2). The length of stay in the ICU and the duration of mechanical ventilation increased with higher APACHE II scores and ASA scores and with lower GCS scores. The Spearman’s rho coefficient of the length of stay for APACHE II, GCS, and ASA scores were 0.320 (p <0.001), -0.329 (p <0.001), and 0.117 (p <0.001), respectively. The Spearman’s rho coefficient of the duration of mechanical ventilation for APACHE II, GCS, and ASA scores were 0.227 (p <0.001), -0.354 (p <0.001), and 0.533 (p =0.015), respectively. The most common indications for being transferred to the ICU were hemodynamic instability in emergency operations (121 of 286; 42.3 %) and major surgery and comorbidity in elective operations (665 and 567 of 1,470; 45.2 and 36.8 %). In emergency operations, the mortality rate, length of stay, duration of mechanical ventilation, and APACHE II scores were significantly higher than in the elective operations (Table 3). Mortality rates were correlated with increased ASA scores (Spearman’s rho coefficient= -0.368 and p <0.001). The ASA II patient group was the most common grouping among the patients admitted to the ICU (Table 2).
According to the cause for admission, patients admitted due to comorbidities had the shortest length of stay [median (min-max): 1 (1-102) days], followed by patients undergoing major surgery [median (min-max): 1 (1-226) days), among the other indications (p <0.001) [median (min-max): 3 (1-418) days in hemodynamic instability; 5 (1-63) in metabolic instability; 4 (1-418) in perioperative cardiac arrest; 3 (1-304) in postoperative respiratory distress]. Duration of mechanical ventilation was significantly lower in the major surgery and comorbidity groups than the other groups [median (min-max): 1 (0-226) and 1 (0-102) days, respectively) compared to others (p <0.001) [median (min-max): 3 (0-418) days in hemodynamic instability; 5 (1-63) in metabolic instability; 4 (1-418) in perioperative cardiac arrest; 2 (0-302) in postoperative respiratory distress]. The perioperative cardiac arrest group had significantly lower GCS scores (10.5 ± 5.0) than the other groups (p <0.001) (13.0 ± 3.5 in hemodynamic instability, 14.7 ± 1.3 in major surgery, 14.7 ± 0.9 in metabolic instability, 13.8 ± 3.1 in postoperative respiratory distress, 14.9 ± 0.5 in co-existing disease). APACHE II scores were significantly lower in the major surgery group (10.7 ± 4.6) than in the other groups (p <0.001) (18.2 ± 6.1 in hemodynamic instability, 18.1 ± 3.7 in metabolic instability, 29.5 ± 3.4 in perioperative cardiac arrest, 14.7 ± 5.2 in postoperative respiratory distress, 13.3 ± 4.3 in co-existing disease).
The results of the present study showed that the ratio of ICU admissions from the OR to all ICU admissions increased 2.5-fold between 2008 and 2012. This increase is related to an increase in the number of ICU beds concurrent with an increase in the whole country10. The ratio of postoperative ICU admissions to all surgical operations was 1.99 % (1,756 of 87,954 patients) in the present study and comparable to other studies5,6,11,12. ICU admissions after surgery may vary from country to country, due to cultural, demographic, socioeconomic, and political differences between nations5.
The vast majority of patients admitted to the ICU after surgery was patients who underwent abdominal or cranial surgery and they had the highest mortality rates (Table 1, Table 2). It was previously reported that gastrointestinal and cranial surgical procedures were associated with higher postoperative morbidity and mortality than other types of surgery, such as gynecological or musculoskeletal surgery12-15. Another finding of the study was that regional anesthesia improved the mortality rate. We confirmed previous studies that showed better prognoses with regional anesthesia, compared to general anesthesia, for high-risk surgical patients16. However, regional anesthesia may be preferred for appropriate surgical procedures.
Most scoring systems help to estimate the mortality of patients admitted to the ICU17. Although the scoring systems were not developed solely for surgical patients, they may be used for postoperative patients and enable risk estimation of that population5,7,8,18. The APACHE II, developed by Knaus et al19, is one of the most common scoring systems. Numerous studies have been performed to show whether high APACHE II scores are related to mortality20,21. In our study, APACHE II scores were higher in patients who underwent emergency operations and died. Ipairment of consciousness level is practically evaluated with GCS22. In the present study, we found that lower GCS scores were associated with higher mortality. We also showed that length of stay and the duration of mechanical ventilation were also longer in patients who died (Table 2). These results were comparable to those of other studies23-25.
Numerous preoperative factors, such as comorbidities, may be assessed by various means, which helps in the estimation of the postoperative prognosis8. Despite the significant inter-observer variability, the ASA classification has been widely accepted in the estimation of postoperative morbidity and mortality5,7,8,26. Regardless of anesthesia application, mortality and morbidity are expected in patients in poor physical condition due to severe systemic illness21. Therefore, patients in bad health condition are expected to have higher rates of admission to the ICU2-8. Our study showed that mortality, length of stay in the ICU, and duration of mechanical ventilation increased as ASA scores increased. Although all these scoring systems are helpful for estimating patient prognoses, it should be remembered that prognoses may be different for every patient27.
Almost all studies have shown that the emergency nature of the operation is an additional risk5,6,26. Although emergency operations were more frequent in ICU admissions in some studies, the rate of elective operations was greater in our study12. Time, staff and the conditions provided for elective operations may not always be available for emergency operations. Insufficient preoperative workup and preparation result in a greater mortality rate in emergency patients. Our study showed that the mortality rates were higher in patients admitted to the ICU after emergency operations than after elective operations.
The ratio of low-risk postoperative patients admitted to the ICU to all postoperative patients is reported to be between 20 and 40 %11,12. In our study, 1,219 (69.4 %) patients were admitted in the ICU for only one day, and then discharged to the ward the next day. This figure is higher than the 20-40 % (that included only low-risk and follow-up admissions) reported by other ICUs11,12. It appears necessary to use the intermediate ICUs, rather than the general ICUs, for the care of these low-risk patients who also have low mortality rates11. Some authors disagree with this due to the possible late complications that may require early and efficient intervention; they also state that these patients should be taken into private sections inside the ICU, which can be utilized as intermediate ICUs11.
Studies emphasize that it is possible to follow-up high-risk patients outside the ICU, and suggest specific criteria for admission to the ICU28,29. As an alternative to the ICUs, level 2 ICUs [high-dependency unit (HDU)], which are more advanced than the regular ward, offer monitoring of low-risk patients30. When beds are unavailable in the ICU, post-anaesthetic care units (PACUs) may be used temporarily; however, those patients who will receive the greatest benefit from the ICU should be transferred to the ICU immediately31.
In a recent study, it was reported that only one-third of high-risk surgical patients was admitted to the ICU postoperatively31. Also, the study found that patients admitted to the ICU had higher survival rates than patients who were re-admitted to the ICU or admitted late to the ICU. In another study, Goldhill and Down9 reported that while some groups of patients were routinely admitted to the ICU, others were rarely admitted, and there were consistencies in ICU admission.
In our study, the most common reasons for admission to the ICU were major surgery and follow-up of patients with severe co-existing disease. The mortality rates, length of stay in the ICU, and duration of mechanical ventilation were shorter in these groups of patients. Perioperative cardiac arrest patients had the highest mortality rate, similar to previous studies32.
In conclusion, because of higher mortality rates, the patients with hemodynamic or metabolic instability, high ASA or APACHE II scores, or low GCS scores must be assessed carefully for postoperative ICU follow-up. Due to the increased number of ICU beds in our hospital, a greater number of high-risk surgical patients underwent elective non-cardiac surgery.
Conflict of interest
Authors declare no conflicts of interest.
This work was presented as a poster at 48th National Turkish Anesthesiology and Reanimation Congress on 25-29 October 2014, in Ankara, Turkey.
1. Nathanson BH, Higgins TL, Kramer AA, Copes WS, Stark M, Teres D. Subgroup mortality probability models: are they necessary for specialized intensive care units? Crit Care Med. 2009; 37: 2375-2386.
2. Harrison DA, Lone NI, Haddow C, MacGillivray M, Khan A, Cook B, et al. External validation of the Intensive Care National Audit & Research Centre (ICNARC) risk prediction model in critical care units in Scotland. BMC Anesthesiol. 2014; 14: 116.
3. Cavaliere F, Conti G, Costa R, Masieri S, Antonelli M, Proietti R. Intensive care after elective surgery: a survey on 30-day postoperative mortality and morbidity. Minerva Anestesiol. 2008; 74: 459-468.
4. Chieng TH, Roslan AC, Chuah JA. Risk-adjusted analysis of patients undergoing laparotomy usimg POSSUM and P-POSSUM score in Queen Elizabeth Hospital, Sabah. Med J Malaysia. 2010; 65: 286-290.
5. Pearse RM, Moreno RP, Bauer P, Pelosi P, Metnitz P, Spies C, et al; European Surgical Outcomes Study (EuSOS) group for the Trials groups of the European Society of Intensive Care Medicine and the European Society of Anesthesiology. Mortality after surgery in Europe: a 7 day cohort study. Lancet. 2012; 380: 1059-1065.
6. Pearse RM, Harrison DA, James P, Watson D, Hinds C, Rhodes A, et al. Identification and characterisation of the high-risk surgical population in the United Kingdom. Crit Care. 2006; 10: R81.
7. Minto G, Biccard B. Assesment of the high-risk perioperative patient. Contin Educ Anaest Crit Care Pain. 2014; 14: 12-17.
8. Sobol JB, Wunsch H. Triage of high-risk surgical patients for intensive care. Crit Care. 2011; 15: 217.
9. Goldhill DR, Down JF. Are we operating as well as we can? Critical care to minimise postoperative mortality and morbidty. Anesthesia. 2008; 63: 689-692.
10. Health Statistics Yearbook 2012, Ankara, Ministery of Health of Turkey, General directorate of Health Research, 2013, 69-71. Available at: http://ekutuphane.sagem.gov.tr/kitaplar/health_statistics_yearbook__2012.pdf.
11. Swann D, Houston P, Goldberg J. Audit of intensive care unit admissions from the operating room. Can J Anesth. 1993; 40: 137-141.
12. Satyawan B, Shinde V, Chaudhari L. Audit of intensive care unit admissions from operating room. Indian J Anaesth. 2006; 50: 193-200.
13. Yadav K, Singh M, Griwan M, Mishra Ts, Kumar N, Kumar H. Evaluation of POSSUM and P-POSSUM as a tool for prediction of surgical outcomes in the Indian population. Australas Med J. 2011; 4: 366-373.
14. Scott S, Lund JN, Gold S, Elliott R, Vater M, Chakrabarty MP, et al. An evaluation of POSSUM and P-POSSUM scoring in predicting post-operative mortality in a level 1 critical care setting. BMC Anesthesiol. 2014; 14: 104.
15. Mercer S, Guha A, Ramesh V. The P-POSSUM scoring systems for predicting the mortality of neurosurgical patients undergoing craniotomy: Further validation of usefulness and application across healthcare systems. Indian J Anaesth. 2013; 57: 587-591.
16. Guay J, Choi PT, Suresh S, Albert N, Kopp S, Pace NL. Neuroaxial anesthesia for the prevention of postoperative mortality and major morbidity: an overview of cochrane systematic reviews. Anesth Analg. 2014; 119: 716-725.
17. Rapsang AG, Shyam DC. Scoring system in the intensive care unit: A compendium. Indian J Crit Care Med. 2014; 18: 220-228.
18. Gilani MT, Razavi M, Azad AM. A comparison of Simplified Acute Physiology Score II, Acute Physiology and Chronic Health Evaluation II and Acute Physiology and Chronic Health Evaluation III scoring system in predicting mortality and lenght of stay at surgical intensive care unit. Niger Med J. 2014; 55: 144-147.
19. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985; 13: 818-829.
20. Naved SA, Siddiqui S, Khan FH. APACHE-II score correlation with mortality and length of stay in an intensive care unit. J Coll Physicians Surg Pak. 2011; 21: 4-8.
21. Zali AR, Seddighi AS, Seddighi A, Ashrafi F. Comparison of the acute physiology and chronic health evaluation score (APACHE) II with GCS in predicting hospital mortality of neurosurgical intensive care unit patients. Glob J Health Sci. 2012; 4: 179-184.
22. Teasdale G, Maas A, Lecky F, Manley G, Stocchetti N, Murray G. The Glasgow Coma Scale at 40 years: standing the test of time. Lance Neurol. 2014; 13: 844-854.
23. Balestreri M, Czosnyka M, Chatfield DA, Steiner LA, Schmidt EA, Smielewski P, et al. Predictive value of Glasgow Coma Scale after brain trauma: change in trend over the past ten years. J Neurol Neurosurg Psychiatry. 2004; 75: 161-162.
24. Saatman KE, Duhaime AC, Bullock R, Maas AI, Valadka A, Manley GT; Workshop Scientific Team and Advisory Panel Members. Classification of traumatic brain injury for targeted therapies. J Neurotrauma. 2008; 25: 719-738.
25. Bickenbach J, Fries M, Rex S, Stitz C, Heussen N, Rossaint R, et al. Outcome and mortality risk factors in long-term treated ICU patients: a retrospective analysis. Minerva Anestesiol. 2011; 77: 427-438.
26. Pignaton W, Braz JR, Kusano PS, Módolo MP, de Carvalho LR, Braz MG, et al. Perioperative and Anesthesia-Related Mortality: An 8-Year Observational Survey From a Tertiary Teaching Hospital. Medicine (Baltimore). 2016; 95: e2208.
27. Higgins TL. Quantifying risk and benchmarking performance in the adult intensive care unit. J Intensive Care Med. 2007; 22: 141-156.
28. Teli M, Morris-Stiff G, Rees JR, Woodsford PV, Lewis MH. Vascular surgery, ICU and HDU: a 14-year observational study. Ann R Coll Surg Engl. 2008; 90: 291-296.
29. Dahm P, Tuttle-Newhall JE, Nimjee SM, Byrne RR, Yowell CW, Price DT. Indications for admission to the surgical intensive care unit after radical cystectomy and urinary diversion. J Urol. 2001; 166: 189-193.
30. Nasraway SA, Cohen IL, Dennis RC, Howenstein MA, Nikas DK, Warren J, et al. Guidelines on admission and discharge for adult intermediate care units. American College of Critical Care Medicine of the Society of Critical Care Medicine. Crit Care Med. 1998; 26: 607-610.
31. Jhanji S, Thomas B, Ely A, Watson D, Hinds CJ, Pearse RM. Mortality and utilisation of critical care resources amongst high-risk surgical patients in a large NHS trust. Anaesthesia. 2008; 63: 695-700.
32. Kazaure HS, Roman SA, Rosenthal RA, Sosa JA. Cardiac arrest among surgical patients: an analysis of incidence, patient characteristics, and outcomes in ACS-NSQIP. JAMA Surg. 2013; 148: 14-21.