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ORIGINAL ARTICLE
Year : 2019  |  Volume : 8  |  Issue : 2  |  Page : 139-143

Evaluation of acute physiology and chronic health evaluation II system in a rural critical care setting: Correlating mortality and length of stay


1 Department of Critical Care, Rural Development Trust Hospital, Ananthapuramu, Andhra Pradesh, India
2 Poison and Drug Information Center, Rural Development Trust (RDT) Hospital; Division of Pharmacy Practice, Raghavendra Institute of Pharmaceutical Education and Research (RIPER), Ananthapuramu, Andhra Pradesh, India
3 Division of Pharmacy Practice, Raghavendra Institute of Pharmaceutical Education and Research (RIPER), Ananthapuramu, Andhra Pradesh, India

Date of Web Publication14-May-2019

Correspondence Address:
Dr. Mohanraj Rathinavelu Mudaliar
Division of Pharmacy Practice, Raghavendra Institute of Pharmaceutical Education and Research, Anantapuramu - 515 721, Andhra Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijhas.IJHAS_28_18

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  Abstract 


BACKGROUND: Severity scoring systems are needed to assess quality of care, treatment efficacy, and may facilitate auditing and optimization of departmental resource utilization, with the aim of reducing health-care cost, providing better care, and improving outcomes.
MATERIALS AND METHODS: The current retrospective study of 6 months' duration was performed to correlate Acute Physiology and Chronic Health Evaluation II (APACHE II) score with mortality and length of stay (LOS) in a seven bedded rural critical care setting, with 242 medical records of patients, admitted for 1 year. Demographic data, indication of intensive care unit (ICU) admission, and presence and absence of any chronic illness were obtained retrospectively from the patient records and documented in data collection form. At the completion of the first 24 h after the admission into ICU, APACHE II score was calculated using 12 physiological variables. Final outcome of the patient (shift out or death) and total length of critical care unit stay were recorded.
RESULTS: In our study, the mean age of the patient was 38.5 ± 1.05 ranging from 18 to 85 years, in whom 59.50% of patients had medical indications for ICU admission and increase in age was known to be associated with mortality (69.23%) in relation to APACHE II Score >34, and mean LOS in ICU was found to be 5.3 days ± 0.36.
CONCLUSION: APACHE II system will be of more priority in determining risk population for whom optimum care to be delivered, by which mortality in ICU could be minimized in rural critical care settings.

Keywords: Acute physiology and chronic health evaluation II scoring system, critical care unit, length of stay, outcome, severity index


How to cite this article:
Handyal H, Gouni GK, Mudaliar MR, Veeraballi S, Tejashwani PP, Uppara V. Evaluation of acute physiology and chronic health evaluation II system in a rural critical care setting: Correlating mortality and length of stay. Int J Health Allied Sci 2019;8:139-43

How to cite this URL:
Handyal H, Gouni GK, Mudaliar MR, Veeraballi S, Tejashwani PP, Uppara V. Evaluation of acute physiology and chronic health evaluation II system in a rural critical care setting: Correlating mortality and length of stay. Int J Health Allied Sci [serial online] 2019 [cited 2019 May 21];8:139-43. Available from: http://www.ijhas.in/text.asp?2019/8/2/139/258182




  Introduction Top


Due to limited health resources and an increase in the cost of health management, prognosis from the disease has become a very important area of health sciences.[1] The clinical assessment of severity of illness is an essential component of medical practice, including intensive care unit (ICU) to predict mortality and morbidity of critically ill patient.[2]

In the last quarter of the 20th century, advances in medical expertise and technologies in critical care medicine have outpaced the development of good judgment for the decision-making and prediction of patient outcome for critically ill patients. The pursuit for accurate and practical scoring systems that might be used to standardize severity of illness and accurately predict survival has been one focus of critical illness researchers in the 1990s, particularly from the perspective of intensivists.[3]

Prognostication of critically ill patients, in a systematic way, based on definite objective data is an integral part of the quality of care in ICU. Conventionally, ICU physicians have been able to differentiate survivors and nonsurvivors based on their clinical experience. The development of severity of illness scoring system has transformed the approach into a more objective and reliable process.[4] In addition to estimating the prognosis, the severity of illness scoring systems also help in resource allocation and compare the performance of ICUs.[5]

The assessment of medical treatment outcome was started in 1863. Florence Nightingale was the first person who addressed this issue.[6] Developed in 1981 at George Washington University Medical Center, the Acute Physiology and Chronic Health Evaluation (APACHE) scoring system[7] was demonstrated to provide accurate and reliable measures of severity of illness in critically ill patients.[8] Its use was very complex and in 1984 Le Gall et al.[9] published a simplified version of this model, known as the Simplified Acute Physiology Score (SAPS), widely used since then, especially in Europe. In 1985, Knaus et al.,[6] published a simplified version of the APACHE system, the APACHE II. This system soon became the scoring system used most worldwide and has been used in administration, planning, quality assurance, comparison of ICUs,[10] and even to assess comparability of groups in clinical trials.[11] The third version, APACHE III,[12] this has limited its use, especially outside the United States. In 1993, Le Gall et al., published a new system, SAPS II based on a European/North American multicenter study.[13]

The APACHE II severity score has shown a good calibration and discriminatory value across a range of disease processes and remains the most commonly used international severity scoring system worldwide.[14] It has been found to have the best Youden index, highest positive predictive value, and best specificity in predicting mortality outcome.[15]

APACHE II showed a good correlation between predicted and observed outcomes in studies from the USA,[6] Canada,[10] New Zealand,[16] and Singapore.[17] A disproportion in observed and predicted hospital mortality in individual ICUs was also reported from Brazil,[18] Denmark,[19] Saudi Arabia,[20] Cuba,[21] and India.[22] Despite noncorrelation with mortality, studies have acknowledged the utility of APACHE II score in the selection of triage patients for ICU admission.[23]

The utilization of score has been suggested to result in management decisions that could salvage costly ICU resources scantily available in developing world. Thus, there is a need, not only to provide patients with quality care but also utilize available resources optimally,[24] for example, through the usage of prediction model like APACHE II. However, Indian literature on this subject is scarcely available. Thus, the current research study was designed to assess the APACHE II score correlation with mortality and length of stay (LOS) in a rural critical care setting of south India.


  Materials and Methods Top


The current retrospective study, of 6 months' duration (December 2015–May 2016) was performed in a seven bedded, general ICU of a 340-bed nonprofit referral health-care setting in south India. Patients admitted to ICU of both genders, age of 18 years and above with a LOS of 24 h and greater were included, and patients with incomplete set of physiological variables, readmissions, and discharged on medical request were excluded from the study. The retrospective study was approved by the ethical committee of hospital.

Study procedure

The study included 242 medical records of patients admitted to rural critical care setting for 1 year (January–December 2015). The current research on correlating mortality and LOS using APACHE II score performed in all patients (general medicine, general surgery, and obstetrics and gynecology) admitted to a seven bedded rural critical care setting for more than 24 h, for 1 year (January–December 2016) was approved by Institutional Review Board of RIPER (RIPER/IRB/2016/013) and approved by the Ethical Committee of the Rural Development Trust (RDT) hospital. Demographic data, indication of ICU admission, presence and absence of any chronic illness were obtained retrospectively from the patient records, and documented in data collection form. At the completion of the first 24 h after the admission to ICU, APACHE II score was calculated using 12 physiological variables. Points were allocated to the worst values of each variable as per APACHE II scoring system calculation. The final outcome of the patient (shift out or death) and total length of critical care unit stay was recorded into Excel spreadsheet and assessed statistically using Instat graphpad (V 3.0) (GraphPad Software, San Diego, California, USA), one-way ANOVA was used to compare the APACHE II score with age distribution. Numeric response variables including APACHE II score versus mortality, gender versus mortality, age versus mortality, and APACHE II score versus ICU LOS were presented as mean ± standard deviation all categorical variables including APACHE II score, age groups, and outcomes in terms of either death or discharge were presented by frequencies and percentages. Tukey–Kramer multiple comparison test was applied to compute significance in the association of APACHE II score and age with patient's outcome. Pearson's correlation coefficient was computed to determine the correlation of APACHE II score with age and length of hospital stay. P < 0.05 was considered statistically significant.


  Results Top


In our retrospective study of 6 months' duration, data of a year were collected and documented on mortality and LOS in a 6 bedded ICU of a secondary care referral health-care settings using APACHE II.

In our study, 242 patients were included out of which 124 were male and 118 were female. The average age of study patients was 38.5 ± 1.05 ranging from 18 to 85 years; 28.51% of patients were within the age group of 18–25 years, in which female were 68.11% results of which are thoroughly analyzed and reported in [Table 1].
Table 1: Demography distribution of study participants (age group vs. gender)

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One hundred and forty-four patients had medical indications for ICU admission, 69 had surgical indications for ICU admission and 29 patients had obstetrics and gynecology indications for ICU admission.

Sixty-nine patients were aged between 18 and 25 years. Out of those 63 patients, majority (89.85%) survived and were discharged from the ICU. Fifty-seven patients were aged between 26 and 35 years, out of whom 51 (89.47%) survived while 6 (10.53%) died. Thirty-eight patients were aged between 36 and 45 years, out of those 30 (78.95%) survived and 8 (21.05%) died. Twenty-eight patients were aged between 46 and 55 years, out of those 25 (89.28%) survived and 3 (10.72%) died. Thirty-five patients were aged between 56 and 65 years, of those 28 (80%) survived and 7 (20%) died. Ten patients were aged between 66 and 75 years, of those 6 (60%) survived and 4 (40%) died. Five patients were aged between 76 and 85 years, of those 1 (20%) survived and 4 (80%) died. A significant association (P = 0.001) of age with outcome was therefore revealed, and the mean APACHE-II score of the study patients was 18.64.

On the basis of APACHE-II score, the patients were divided into eight groups.[5] The first group patients had APACHE-II score of 0–4, second group had 5–9, third group had 10–14, fourth group had 15–19, fifth group had 20–24, sixth group had 25–29, seventh group had 30–34, and eighth group scored >34, results of which are thoroughly assessed and the relationship between the APACHE II score and the mortality (observed and predicted) was reported in [Table 2]. There were 13 patients in Group VIII, with APACHE II score above 34, out of which four patients (30.77%) were discharged and 9 (69.23%) died. This revealed that there might be more chances of death in case of high APACHE-II score (P = 0.001, and more chances of getting out from the ICU in case of low APACHE scores. Mean ICU stay in survivors was found to be 5.3 days ± 0.36. The statistical interpretations of APACHE II score with ICU LOS and mortality was thoroughly analyzed and reported in [Table 3].
Table 2: Acute Physiology and Chronic Health Evaluation II score and outcomes of patients (n=242)

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Table 3: Statistical interpretations of Acute Physiology and Chronic Health Evaluation II score with ICU length of stay mortality

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  Discussion Top


The APACHE II score combines a variety of physiologic variables, age, and chronic health variables, according to which a numeric score is allotted.[25],[26] The APACHE II is used widely for predicting the probability of hospital mortality[27] and LOS in the ICU. Although outcome prediction scoring systems have been widely used and accepted throughout the world, the differences between health-care facilities, providers and patient populations make it important to evaluate their validity in different settings.[28],[29]

In the current study, mortality and ICU LOS of 242 patients admitted to a six bedded, general ICU of a secondary referral health-care setting in south India was assessed using APACHE II system retrospectively.

The mean age of the patient was 38.5 ± 1.05 ranging from 18 to 85 years, findings of which are similar to the study performed by van der Merwe et al., 2005.[30] Of 242 patients 124 (51.24%) were male and 118 (48.76%) were female. In our study majorly, 59.50% of patients had medical indications for ICU admission results of which are similar to the study performed by Naved et al., 2011.[31] In our study, increasing age is known to be associated with mortality. Five patients were aged between 76 and 85 years, of those 1 (20%) survived and 4 (80%) died. Significant association (P = 0.001) of age with outcome was therefore revealed, results of which were found to be similar to that of study performed by Naved et al., 2011[31],[32] and Mahul et al., 1991.[32]

APACHE II Scores estimate risk based on data available within first 24 h of ICU stay. The lack of intensive care beds has emerged as a serious public health problem. The APACHE system is the only validated ICU risk-adjustment model that provides performance information about two separate outcomes of care, for example, mortality and ICU LOS. Prediction of the duration of a patient's stay in the ICU, however, is difficult and less studied than the prediction of mortality.[33] Prolonged stay in the ICU not only increases the overall costs and consumes more resources but also limits the number of beds available for use. A key factor determining such policy initiatives is a prediction of average LOS in ICUs for patients.

In our study, the observed mortality was found more (69.23%), were the APACHE II Score range lies >34 the results of which are found to be same in a study carried by Abbott et al., 1991.[34]

The summary of 24 h APACHE II score in our study was 18.64 in a population of 242, the results of which found to be similar in the study performed by Haidri et al., 2011[35] were the mean APACHE II score of study in first 24 h was 18.6 ± 0.6.

In our study, the mean LOS in ICU was found to be 5.3 days ± 0.36 results of which are similar to study performed by Knaus et al., 1993[36] which was 5 days.

The application of APACHE II instrument in the United States, Canada, New Zealand, and Singapore has confirmed the correlation between the mortality rate predicted and the real rate of death. However, contradictory results have been brought about by researches in Britain and Ireland.[37] In our study also, there is a positive correlation between the APACHE II score and observed mortality and LOS, which was statistically significant (P < 0.001).


  Conclusion Top


APACHE II score prognostic index is useful for stratifying patients according to the severity of their health condition, but in rural critical care setting with limited number of beds APACHE II system will be of more priority in identifying and determining the risk population for whom optimum care to be delivered, by which mortality in ICU could be minimized.

Acknowledgment

The authors would like to thank the management and staff members, and ethical committee members of RDT Hospital, Bathalapalli, Anantapuramu, Andhra Pradesh., India.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Tables

  [Table 1], [Table 2], [Table 3]



 

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