Criteria for patient admission to an intensive care unit and related mortality rates

Complexity measure based on sensitivity analysis applied to an intensive care unit system

This work proposes a system complexity metric and its application to Intensive Care Unit (ICU) system. The methodology for applying said complexity metric comprises: (i) parameters sensitivity indices calculation, (ii) mapping connections dynamics between system components, and (iii) system's complexity calculation. After simulating the ICU computer model and using the proposed methodology, we obtained results regarding: number of admissions, number of patients in the queue, length of stay, beds in use, ICU performance, and system complexity values (in regular or overloaded operation). As the number of patients in the queue increased, the ICU system complexity also increased, indicating a need for policies to promote system robustness.

Referral to immediate postoperative care in an intensive care unit from the perspective of anesthesiologists, surgeons, and intensive care physicians: a cross-sectional questionnaire

Introduction and objective

Due to the high cost and insufficient offer, the request for Intensive Care (ICU) beds for postoperative recovery needs adequate criteria. Therefore, we studied the characteristics of patients referred to postoperative care at an ICU from the perspective of anesthesiologists, surgeons, and intensive care physicians.

Methods

A questionnaire on referrals to postoperative intensive care was applied to physicians at congresses in Brazil. Anesthesiologists, surgeons, and intensive care physicians who agreed to fill out the questionnaire were included. The questionnaire consisted of hypothetical clinical scenarios and cases for participants to choose which would be the priority for referral to the ICU.

Results

360 physicians participated in the study, with median time of 10 (5–18) years after graduation. Of the interviewees, 36.4% were anesthesiologists, 30.0% surgeons, and 33.6% intensive care physicians. We found that anesthesiologists were more conservative, and surgeons less conservative in ICU referrals. As to patients with risk of bleeding, 75.0% of the surgeons would refer them to the ICU, in contrast with 52.1% of the intensive care physicians, and 43.5% of the anesthesiologists (p < 0.001). As to elderly persons with limited reserve, 62.0% of the surgeons would refer them to the ICU, in contrast with 47.1% of the intensive care physicians, and 22.1% of the anesthesiologists (p < 0.001). As to patients with risk of respiratory complications, 64.5% of the surgeons would recommend the ICU, versus 43.0% of the intensive care physicians, and 32.1% of the anesthesiologists (p < 0.001). Intensive care physicians classified priorities better in indicating ICU, and the main risk indicator was the ASA physical status in all specialties (p < 0.001). There was no agreement among the specialties and surgeries on prioritizing post-operative intensive care.

Conclusion

Anesthesiologists, surgeons, and intensive care physicians presented different perspectives on postoperative referral to the ICU.

Use of intensive care unit priority model in directing intensive care unit admission in Sudan: A prospective cross-sectional study

Background:

The shortage of specialized intensive care beds is one of the principal factors that limit intensive care unit (ICU) admissions. This study explores the utilization of priority criteria in directing ICU admission and predicting outcomes.

Methods:

This was a prospective cross-sectional study conducted in two ICUs in Sudan from April to December 2018. Patients were assessed for ICU admission and were ranked by priority into Groups 1, 2, 3, and 4 (1 highest priority and 4 lowest priority), and these groups were compared using independent t-test, Chi-square, and ANOVA.

Results:

A total of 180 ICU admitted patients were enrolled, 53% were male. The prioritization categories showed that 86 (47.8%), 50 (27.8%), 13 (7.2%), and 31 (17.2%) were categorized as priority 1, 2, 3, and 4, respectively. Patients in priority groups 3 and 4had significantly higher ICU mortality rates compared to those in groups 1 and 2 (P < 0.001), were likely to be older (P < 0.001), had significantly more comorbidities (P = 0.001), were more likely to be dependent (P < 0.001), and had longer ICU length of stay (P = 0.028).

Conclusion:

Patients classified as priority 3 and 4 were predominantly older and had many comorbidities. They were likely to be dependent, stay longer in ICU, and exhibit mortality.

Developing an intervention around referral and admissions to intensive care: a mixed-methods study

Background

Intensive care treatment can be life-saving, but it is invasive and distressing for patients receiving it and it is not always successful. Deciding whether or not a patient will benefit from intensive care is a difficult clinical and ethical challenge.

Objectives

To explore the decision-making process for referral and admission to the intensive care unit and to develop and test an intervention to improve it.

Methods

A mixed-methods study comprising (1) two systematic reviews investigating the factors associated with decisions to admit patients to the intensive care unit and the experiences of clinicians, patients and families; (2) observation of decisions and interviews with intensive care unit doctors, referring doctors, and patients and families in six NHS trusts in the Midlands, UK; (3) a choice experiment survey distributed to UK intensive care unit consultants and critical care outreach nurses, eliciting their preferences for factors used in decision-making for intensive care unit admission; (4) development of a decision-support intervention informed by the previous work streams, including an ethical framework for decision-making and supporting referral and decision-support forms and patient and family information leaflets. Implementation feasibility was tested in three NHS trusts; (5) development and testing of a tool to evaluate the ethical quality of decision-making related to intensive care unit admission, based on the assessment of patient records. The tool was tested for inter-rater and intersite reliability in 120 patient records.

Results

Influences on decision-making identified in the systematic review and ethnographic study included age, presence of chronic illness, functional status, presence of a do not attempt cardiopulmonary resuscitation order, referring specialty, referrer seniority and intensive care unit bed availability. Intensive care unit doctors used a gestalt assessment of the patient when making decisions. The choice experiment showed that age was the most important factor in consultants’ and critical care outreach nurses’ preferences for admission. The ethnographic study illuminated the complexity of the decision-making process, and the importance of interprofessional relationships and good communication between teams and with patients and families. Doctors found it difficult to articulate and balance the benefits and burdens of intensive care unit treatment for a patient. There was low uptake of the decision-support intervention, although doctors who used it noted that it improved articulation of reasons for decisions and communication with patients.

Limitations

Limitations existed in each of the component studies; for example, we had difficulty recruiting patients and families in our qualitative work. However, the project benefited from a mixed-method approach that mitigated the potential limitations of the component studies.

Conclusions

Decision-making surrounding referral and admission to the intensive care unit is complex. This study has provided evidence and resources to help clinicians and organisations aiming to improve the decision-making for and, ultimately, the care of critically ill patients.

Future work

Further research is needed into decision-making practices, particularly in how best to engage with patients and families during the decision process. The development and evaluation of training for clinicians involved in these decisions should be a priority for future work.

Study registration

The systematic reviews of this study are registered as PROSPERO CRD42016039054, CRD42015019711 and CRD42015019714.

Funding

The National Institute for Health Research Health Services and Delivery Research programme. The University of Aberdeen and the Chief Scientist Office of the Scottish Government Health and Social Care Directorates fund the Health Economics Research Unit.

The predictive power of SAPS-3 and SOFA scores and their relations with patient outcomes in the Surgical Intensive Care Unit

Objectives

Individual risk of surgical patients is more often underestimated and there is not an absolute criterion demonstrating which patient deserves intensive care. Since a nominative assessment of these patients to quantify the intensity of critical illness is not appropriate, prognostic scores are used to assess the mortality rate and prognosis for critical patients including surgical ones. This study aimed to test the calibration power of SAPS-3 score and SOFA score of surgical patients undergoing gastrointestinal surgery, and identify any relation with patient outcomes in the department of surgical ICU.

Material and Methods

This retrospective observational study was conducted during the period between August 2017 and December 2017. It was performed at a Gastroenterological Surgical ICU, a tertiary care hospital in Ankara, Türkiye. To calculate SAPS-3 and SOFA score, physiological data and laboratory analysis on the day of ICU admission were used. Records were reviewed from hospitalization to medical discharge or hospital mortality. Statistical analysis included Mann Whitney U-test and ROC-curves to predict 30-day mortality.

Results

A total of 233 patients admitted to the Gastroenterological Surgical ICU were included into the study and the main reason for ICU admission was surgical problems. Mortality rate was 2.6 % (6 patients). Average SAPS -3 score was 32.5 and SOFA score was 30.1. A significant correlation was observed with the SAPS-3 score, but not with the SOFA score statistically in mortality as a dependent factor. The discriminative power, assessed using the AUC and the probability of death estimation, was satisfactory with the SAPS-3 scores (AUC 0.754) while it was lower with the SOFA score (AUC 0.631).

Conclusion

We found that SAPS-3 score was significantly correlated not only with mortality rate, but also with LOS in the ICU. Nonetheless, SOFA score was not related to mortality, but related to LOS in the ICU. Prognostic score systems are used to estimate mortality but they may be used to identify LOS in the ICU and postoperative complications. It can be concluded that SAPS-3 and SOFA scores may be used to prognosticate postoperative ICU requirement.

Critical Care Utilization in Patients with Diabetic Ketoacidosis, Stroke, and Gastrointestinal Bleed: Two Hospitals Experience

Introduction: Intensive Care Units (ICUs) are among the most expensive components of hospital care. Experts believe that ICUs are overused; however, hospitals vary in their ICU admission rate. Our hypothesis is based on clinical observations that many patients with diabetic ketoacidosis (DKA), stroke, and gastrointestinal (GI) bleeding admitted to the ICU don’t really need it and could be managed safely in a non-ICU level of care. Reducing inappropriate admissions would reduce healthcare costs and improve outcomes. Our primary objective was to determine the frequency of inappropriate ICU admissions. Secondary objectives were to evaluate which diagnoses were more unnecessarily admitted to the ICU, evaluate different variables and comorbidities, and determine the mortality rates during ICU admissions.

Methods: Patients admitted to the ICU, from the Emergency Department (ED) or transferred from the floor, during a one-year period were evaluated in this retrospective study. Patients 18-years old and above who had an admitting diagnosis of DKA, GI bleed, ischemic stroke, or hemorrhagic stroke were included. Patients in a comatose state, intubated, on vasopressors, hemodynamically unstable or had an unstable comorbid disease, subarachnoid hemorrhage, surgery during hospitalization prior to the ICU admission were excluded. Patients were categorized as having an appropriate or inappropriate ICU admission based on our institutional ICU admission criteria and data from available literature and guidelines.

Results: A total of 95 patients were included in our cohort. Seventy-two out of 95 (76%) were considered as inappropriate ICU admissions. When comparing each of the four admitting diagnoses, a significantly higher proportion of DKA patients were considered inappropriate ICU admissions when compared to the other diagnoses (P = 0.001). The overall mortality rate of ICU admissions was 16%, 15 patients out of 95 study population. When comparing each of the four admitting diagnoses, there was a significant difference in mortality rate with DKA having the lowest mortality (3%) and GI bleed having the highest mortality (43%). Out of the 15 patients who died, only 1 patient was categorized as an inappropriate ICU admission.

Conclusions: More than three-quarters of our study population was admitted to the ICU inappropriately. Incorporating severity scores in ICU admission criteria could improve the appropriateness of ICU admission and financial feasibility.

This article is based on a poster: Alsamman S, Alsamman MA, Castro M, Koselka H, Steinbrunner J: ICU admission patterns in patients with DKA, stroke and GI bleed: do they all need ICU? J Hosp Med. March 2015.

A decision-aid tool for ICU admission triage is associated with a reduction in potentially inappropriate intensive care unit admissions

PURPOSE

Intensive care unit (ICU) admission triage occurs frequently and often involves highly subjective decisions that may lead to potentially inappropriate ICU admissions. In this study, we evaluated the effect of implementing a decision-aid tool for ICU triage on ICU admission decisions.

METHODS

This was a prospective, before-after study. Urgent ICU referrals to ten ICUs in a tertiary hospital in Brazil were assessed before and after the implementation of the decision-aid tool. Our primary outcome was the proportion of potentially inappropriate ICU referrals (defined as priority 4B or 5 referrals, accordingly to the Society of Critical Care Medicine guidelines of 1999 and 2016, respectively) admitted to the ICU within 48 h. We conducted multivariate analyses to adjust for potential confounders and evaluated the interaction between phase and triage priority.

RESULTS

Of the 2201 patients analyzed, 1184 (53.8%) patients were admitted to the ICU. After adjustment for confounders, implementation of the decision-aid tool was associated with a reduction in potentially inappropriate ICU admissions using either the 1999 [adjOR (95% CI) = 0.36 (0.13-0.97)] or 2016 [adjOR (95%CI) = 0.35 (0.13-0.96)] definitions.

CONCLUSION

Implementation of a decision-aid tool for ICU triage was associated with a reduction in potentially inappropriate ICU admissions.

Effect of Emergency Department and ICU Occupancy on Admission Decisions and Outcomes for Critically Ill Patients

OBJECTIVES

ICU admission delays can negatively affect patient outcomes, but emergency department volume and boarding times may also affect these decisions and associated patient outcomes. We sought to investigate the effect of emergency department and ICU capacity strain on ICU admission decisions and to examine the effect of emergency department boarding time of critically ill patients on in-hospital mortality.

DESIGN

A retrospective cohort study.

SETTING

Single academic tertiary care hospital.

PATIENTS

Adult critically ill emergency department patients for whom a consult for medical ICU admission was requested, over a 21-month period.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patient data, including severity of illness (Mortality Probability Model III on Admission), outcomes of mortality and persistent organ dysfunction, and hourly census reports for the emergency department, for all ICUs and all adult wards were compiled. A total of 854 emergency department requests for ICU admission were logged, with 455 (53.3%) as "accept" and 399 (46.7%) as "deny" cases, with median emergency department boarding times 4.2 hours (interquartile range, 2.8-6.3 hr) and 11.7 hours (3.2-20.3 hr) and similar rates of persistent organ dysfunction and/or death 41.5% and 44.6%, respectively. Those accepted were younger (mean ± SD, 61 ± 17 vs 65 ± 18 yr) and more severely ill (median Mortality Probability Model III on Admission score, 15.3% [7.0-29.5%] vs 13.4% [6.3-25.2%]) than those denied admission. In the multivariable model, a full medical ICU was the only hospital-level factor significantly associated with a lower probability of ICU acceptance (odds ratio, 0.55 [95% CI, 0.37-0.81]). Using propensity score analysis to account for imbalances in baseline characteristics between those accepted or denied for ICU admission, longer emergency department boarding time after consult was associated with higher odds of mortality and persistent organ dysfunction (odds ratio, 1.77 [1.07-2.95]/log10 hour increase).

CONCLUSIONS

ICU admission decisions for critically ill emergency department patients are affected by medical ICU bed availability, though higher emergency department volume and other ICU occupancy did not play a role. Prolonged emergency department boarding times were associated with worse patient outcomes, suggesting a need for improved throughput and targeted care for patients awaiting ICU admission.

Post-operative outcomes in older patients: a single-centre observational study

BACKGROUND

Improved life-expectancies have seen increased rates of older patients undergoing surgery worldwide. These patients are at increased risk of post-operative complications. Australian evidence is limited regarding the association between age and post-operative outcomes, especially rapid response calls (RRCs) as indicators of adverse outcomes. The aim was to compare the post-operative outcomes of older patients (≥80 years) to younger patients. Specifically, 30-day in-hospital mortality; unplanned intensive care unit (ICU) admission; and RRC activation within 72 h post-operatively.

METHODS

Single-centre retrospective observational study conducted over 12 months in a metropolitan Australian hospital. All adult patients (≥16 years) undergoing surgical procedures were included, excluding cardiac and obstetric/gynaecological surgeries. Patient co-morbidities were quantified using Charlson co-morbidity index (CCI) and American Society of Anesthesiologists physical status classification.

RESULTS

Seven thousand four hundred and seventy-nine patients met inclusion criteria, 14.5% (n = 1086) aged ≥80 years. Most procedures (65%) were elective; and general surgical procedures were most common (24.2%). Compared to younger patients, older patients had significantly higher 30-day mortality (2.3% versus 0.2%; P < 0.001), increased post-operative RRC rates (7.3% versus 1.2%; P < 0.001), and unplanned ICU admissions (3.2% versus 1.6%; P < 0.001). Increasing age was associated with increased risk of post-operative RRC, unplanned ICU admission, and in-hospital mortality (all P < 0.01), with associations remaining significant after controlling for surgery type and CCI.

CONCLUSION

Older patients are at increased risk of adverse post-operative outcomes, including post-operative RRC, unplanned ICU admission, and mortality, especially if they underwent emergency procedures. This has implications for preoperative risk stratification and post-operative management. Incidence of post-operative RRCs may be an important indicator of post-operative care.

Multi-drug resistant Acinetobacter species: a seven-year experience from a tertiary care center in Lebanon

Background

Acinetobacter species have become increasingly common in the intensive care units (ICU) over the past two decades, causing serious infections. At the American University of Beirut Medical Center, the incidence of multi-drug resistant Acinetobacter baumannii (MDR-Ab) infections in the ICU increased sharply in 2007 by around 120%, and these infections have continued to cause a serious problem to this day.

Methods

We conducted a seven-year prospective cohort study between 2007 and 2014 in the ICU. Early in the epidemic, a case-control study was performed that included MDR-Ab cases diagnosed between 2007 and 2008 and uninfected controls admitted to the ICU during the same time.

Results

The total number of patients with MDR-Ab infections diagnosed between 2007 and 2014 was 128. There were also 99 patients with MDR-Ab colonization without evidence of active infection between 2011 and 2014. The incidence of MDR-Ab transmission was 315.4 cases/1000 ICU patient-days. The majority of infections were considered hospital-acquired (84%) and most consisted of respiratory infections (53.1%). The mortality rate of patients with MDR-Ab ranged from 52% to 66%.

Conclusion

MDR-Ab infections mostly consisted of ventilator-associated pneumonia and were associated with a very high mortality rate. Infection control measures should be reinforced to control the transmission of these organisms in the ICU.

Decision-making in intensive care medicine - A review

Decision-making by intensivists around accepting patients to intensive care units is a complex area, with often high-stakes, difficult, emotive decisions being made with limited patient information, high uncertainty about outcomes and extreme pressure to make these decisions quickly. This is exacerbated by a lack of clear guidelines to help guide this difficult decision-making process, with the onus largely relying on clinical experience and judgement. In addition to uncertainty compounding decision-making at the individual clinical level, it is further complicated at the multi-speciality level for the senior doctors and surgeons referring to intensive care units. This is a systematic review of the existing literature about this decision-making process and the factors that help guide these decisions on both sides of the intensive care unit admission dilemma. We found many studies exist assessing the patient factors correlated with intensive care unit admission decisions. Analysing these together suggests that factors consistently found to be correlated with a decision to admit or refuse a patient from intensive care unit are bed availability, severity of illness, initial ward or team referred from, patient choice, do not resuscitate status, age and functional baseline. Less research has been done on the decision-making process itself and the factors that are important to the accepting intensivists; however, similar themes are seen. Even less research exists on referral decision and demonstrates that in addition to the factors correlated with intensive care unit admission decisions, other wider variables are considered by the referring non-intensivists. No studies are available that investigate the decision-making process in referring non-intensivists or the mismatch of processes and pressure between the two sides of the intensive care unit referral dilemma.

The Ability of the Acute Physiology and Chronic Health Evaluation (APACHE) IV Score to Predict Mortality in a Single Tertiary Hospital

Background

The Acute Physiology and Chronic Health Evaluation (APACHE) II model has been widely used in Korea. However, there have been few studies on the APACHE IV model in Korean intensive care units (ICUs). The aim of this study was to compare the ability of APACHE IV and APACHE II in predicting hospital mortality, and to investigate the ability of APACHE IV as a critical care triage criterion.

Methods

The study was designed as a prospective cohort study. Measurements of discrimination and calibration were performed using the area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test respectively. We also calculated the standardized mortality ratio (SMR).

Results

The APACHE IV score, the Charlson Comorbidity index (CCI) score, acute respiratory distress syndrome, and unplanned ICU admissions were independently associated with hospital mortality. The calibration, discrimination, and SMR of APACHE IV were good (H = 7.67, P = 0.465; C = 3.42, P = 0.905; AUROC = 0.759; SMR = 1.00). However, the explanatory power of an APACHE IV score >93 alone on hospital mortality was low at 44.1%. The explanatory power was increased to 53.8% when the hospital mortality was predicted using a model that considers APACHE IV >93 scores, medical admission, and risk factors for CCI >3 coincidentally. However, the discriminative ability of the prediction model was unsatisfactory (C index <0.70).

Conclusions

The APACHE IV presented good discrimination, calibration, and SMR for hospital mortality.

Epidemiological profile of ICU patients at Faculdade de Medicina de Marília

OBJECTIVE

To characterize the epidemiological profile of the hospitalized population in the ICU of Hospital das Clínicas de Marília (Famema).

METHOD

A retrospective, descriptive and quantitative study. Data regarding patients admitted to the ICU Famema was obtained from the Technical Information Center (Núcleo Técnico de Informações, NTI, Famema). For data analysis, we used the distribution of absolute and relative frequencies with simple statistical treatment.

RESULTS

2,022 ICU admissions were recorded from June 2010 to July 2012 with 1,936 being coded according to the ICD-10. The epidemiological profile comprised mostly males (57.91%), predominantly seniors ≥ 60 years (48.89%), at an average age of 56.64 years (±19.18), with limited formal education (63.3% complete primary school), mostly white (77.10%), Catholic (75.12%), from the city of Marília, state of São Paulo, Brazil (53.81%). The average occupancy rate was 94.42%. The predominant cause of morbidity was diseases of the circulatory system with 494 admissions (25.5%), followed by traumas and external causes with 446 admissions (23.03%) and neoplasms with 213 admissions (11.00%). The average stay was 8.09 days (±10.73). The longest average stay was due to skin and subcutaneous tissue diseases, with average stay of 12.77 days (±17.07). There were 471 deaths (24.32%), mainly caused by diseases of the circulatory system (30.99%). The age group with the highest mortality was the range from 70 to 79 years with 102 deaths (21.65%).

CONCLUSION

The ICU Famema presents an epidemiological profile similar to other intensive care units in Brazil and worldwide, despite the few studies available in the literature. Thus, we feel in tune with the treatment of critical care patients.

SAPS 3 score as a predictive factor for postoperative referral to intensive care unit

BACKGROUND

Patients undergoing intermediate-risk surgery are typically taken to the ward postoperatively. However, some may develop complications requiring intensive care later. We aimed to evaluate the characteristics of patients undergoing intermediate-risk surgery who required late postoperative admission to the intensive care unit (ICU) and determine the predictors for this.

METHODS

The study included patients undergoing intermediate-risk surgery with preoperative indication for ICU but who were taken to the ward postoperatively, because they appeared to be responding well. However, they required late ICU admission. ICU care and preoperative SAPS 3 score were evaluated. Palliative surgeries and patients readmitted to ICU were excluded.

RESULTS

The study included 100 patients, 27 % of whom had late postoperative admission to the ICU. The preoperative SAPS 3 score was higher (45.4 ± 7.8 vs. 35.9 ± 7.4, P < 0.001) in patients who required delayed admission to the ICU postoperatively. Furthermore, they had undergone longer surgery (4.2 ± 1.9 vs. 2.7 ± 1.5 h, P < 0.001), and a greater proportion were gastrointestinal surgeries (14.8 vs. 5.5 %, P = 0.03) and intraoperative transfusion (18.5 vs. 5.5 % P = 0.04). In multivariate analysis, preoperative SAPS 3 and surgery duration independently predicted postoperative ICU admission, respectively (OR 1.25; 95 % CI 1.1-1.4 and OR 3.33; 95 % CI 1.7-6.3).

CONCLUSION

The identification of high-risk surgical patients is essential for proper treatment; time of surgery and preoperative SAPS 3 seem to provide a useful indication of risk and may help better to characterize patients undergoing intermediate-risk surgery that demand ICU care.

Qualitative Analysis of Surveyed Emergency Responders and the Identified Factors That Affect First Stage of Primary Triage Decision-Making of Mass Casualty Incidents

Introduction: After all large-scale disasters multiple papers are published describing the shortcomings of the triage methods utilized. This paper uses medical provider input to help describe attributes and patient characteristics that impact triage decisions.

Methods: A survey distributed electronically to medical providers with and without disaster experience. Questions asked included what disaster experiences they had, and to rank six attributes in order of importance regarding triage.

Results: 403 unique completed surveys were analyzed. 92% practiced a structural triage approach with the rest reporting they used “gestalt”.(gut feeling) Twelve per cent were identified as having placed patients in an expectant category during triage. Respiratory status, ability to speak, perfusion/pulse were all ranked in the top three. Gut feeling regardless of statistical analysis was fourth. Supplies were ranked in the top four when analyzed for those who had placed patients in the expectant category.

Conclusion: Primary triage decisions in a mass casualty scenario are multifactorial and encompass patient mobility, life saving interventions, situational instincts, and logistics.

Development of an algorithm to aid triage decisions for intensive care unit admission: a clinical vignette and retrospective cohort study

BACKGROUND

Intensive care unit (ICU) admission triage is performed routinely and is often based solely on clinical judgment, which could mask biases. A computerized algorithm to aid ICU triage decisions was developed to classify patients into the Society of Critical Care Medicine's prioritization system. In this study, we sought to evaluate the reliability and validity of this algorithm.

METHODS

Nine senior physicians evaluated forty clinical vignettes based on real patients. The reference standard was defined as the priorities ascribed by two investigators with full access to patients' records. Agreement of algorithm-based priorities with the reference standard and with intuitive priorities provided by the physicians were evaluated. Correlations between algorithm prioritization and physicians' judgment of the appropriateness of ICU admissions in scarcity and nonscarcity settings were also evaluated. Validity was further assessed by retrospectively applying this algorithm to 603 patients with requests for ICU admission for association with clinical outcomes.

RESULTS

Agreement between algorithm-based priorities and the reference standard was substantial, with a median κ of 0.72 (interquartile range [IQR] 0.52-0.77). Algorithm-based priorities demonstrated higher interrater reliability (overall κ 0.61, 95% confidence interval [CI] 0.57-0.65; median percentage agreement 0.64, IQR 0.59-0.70) than physicians' intuitive prioritization (overall κ 0.51, 95% CI 0.47-0.55; median percentage agreement 0.49, IQR 0.44-0.56) (p = 0.001). Algorithm-based priorities were also associated with physicians' judgment of appropriateness of ICU admission (priorities 1, 2, 3, and 4 vignettes would be admitted to the last ICU bed in 83.7%, 61.2%, 45.2%, and 16.8% of the scenarios, respectively; p < 0.001) and with actual ICU admission, palliative care consultation, and hospital mortality in the retrospective cohort.

CONCLUSIONS

This ICU admission triage algorithm demonstrated good reliability and validity. However, more studies are needed to evaluate a difference in benefit of ICU admission justifying the admission of one priority stratum over the others.

Septic shock: a major cause of hospital death after intensive care unit discharge

Objective

To assess the causes and factors associated with the death of patients between intensive care unit discharge and hospital discharge.

Methods

The present is a pilot, retrospective, observational cohort study. The records of all patients admitted to two units of a public/private university hospital from February 1, 2013 to April 30, 2013 were assessed. Demographic and clinical data, risk scores and outcomes were obtained from the Epimed monitoring system and confirmed in the electronic record system of the hospital. The relative risk and respective confidence intervals were calculated.

Results

A total of 581 patients were evaluated. The mortality rate in the intensive care unit was 20.8% and in the hospital was 24.9%. Septic shock was the cause of death in 58.3% of patients who died after being discharged from the intensive care unit. Of the patients from the public health system, 73 (77.6%) died in the intensive care unit and 21 (22.4%) died in the hospital after being discharged from the unit. Of the patients from the Supplementary Health System, 48 (94.1%) died in the intensive care unit and 3 (5.9%) died in the hospital after being discharged from the unit (relative risk, 3.87%; 95% confidence interval, 1.21 - 12.36; p < 0.05). The post-discharge mortality rate was significantly higher in patients with intensive care unit hospitalization time longer than 6 days.

Conclusion

The main cause of death of patients who were discharged from the intensive care unit and died in the ward before hospital discharge was septic shock. Coverage by the public healthcare system and longer hospitalization time in the intensive care unit were factors associated with death after discharge from the intensive care unit.

Admissions of critically ill patients to the ED intensive care unit

INTRODUCTION

Many emergency departments (EDs) have established units capable of providing critical care because of increasing need for critical care, called as ED intensive care unit (EDICU). However, prolonged critical care leads to crowding, resulting in poor quality of care and high mortality rates. We aimed to determine which type of critically ill patients play a main role for crowding in the EDICU, and how to manage these patients.

METHOD

Patients aged older than 18 years who presented to the ED and presented for consultation to the ICU were eligible for inclusion in this study. Patients were classified into 4 priority groups by the Society of Critical Care Medicine.

RESULT

Four hundred medical patients were enrolled in the study. Sixty-one patients were not admitted to hospital (15.2% of all patients) and were treated in the EDICU. These patients were older (mean age, 66.6 years) and had a higher percentage belonging to the priority 3 group (82.0%-unstable with reduced likelihood of recovery due to chronic illness) in comparison with other ICUs patients (mean age, 60.4 years and 11.9%, respectively) (P < .05). In priority 3 patients, the length of stay was median 120 hours, and also, length of invasive mechanical ventilations duration was median 19 hours in the EDICU.

CONCLUSIONS

Emergency department intensive care unit occupancy appears driven by categorized as "reduced benefit" patients, and these units tend to become alternative dumping grounds for palliative care services. Hospitals and health care administrators should take special care to develop policies for improving the management of these patients.

Circulatory disease mortality rates in the elderly and exposure to PM(2.5) generated by biomass burning in the Brazilian Amazon in 2005

The aim of this study was to analyze the association between the exposure to fine particulate matter and circulatory disease mortality rates in the elderly living in the Brazilian Amazon. An ecological study of circulatory disease, acute myocardial infarction and cerebrovascular disease mortality rates in micro areas of the Brazilian Amazon was carried out. The environmental exposure indicator used was percentage hours of PM(2.5) concentrations > 25µg/m(3) divided by the total number of estimated hours of PM(2.5) in 2005. The association between exposure and circulatory disease mortality rates was strongest in the oldest age group. No significant statistical association was found between cerebrovascular disease mortality rates and exposure. Circulatory disease mortality rates in the elderly living in the Amazon have been influenced by atmospheric pollution from emissions caused by forest fires.

Factors influencing triage decisions in patients referred for ICU admission

Background

Few data is available on triage of critically ill patients. Because the demand for ICU beds often exceeds their availability, frequently intensivists need to triage these patients in order to equally and efficiently distribute the available resources based on the concept of potential benefit and reasonable chance of recovery. The objective of this study is to evaluate factors influencing triage decisions among patients referred for ICU admission and to assess its impact in outcome.

Methods

A single-center, prospective, observational study of 165 consecutive triage evaluations was conducted in patients referred for ICU admission that were either accepted, or refused and treated on the medical or surgical wards as well as the step-down and telemetry units.

Results

Seventy-one patients (43.0%) were accepted for ICU admission. Mean Acute Physiology and Chronic Health Evaluation (APACHE)-II score was 15.3 (0 - 36) and 13.9 (0 - 30) for accepted and refused patients, respectively. Three patients (4.2%) had active advance directives on admission to ICU. Age, gender, and number of ICU beds available at the time of evaluation were not associated with triage decisions. Thirteen patients (18.3%) died in ICU, while the in-hospital mortality for refused patients was 12.8%.

Conclusion

Refusal of admission to ICU is common, although patients in which ICU admission is granted have higher mortality. Presence of active advance directives seems to play an important role in the triage decision process. Further efforts are needed to define which patients are most likely to benefit from ICU admission. Triage protocols or guidelines to promote efficient critical care beds use are warranted.