Monitoring the performance of intensive care units using the variable life-adjusted display: a simulation study to explore its applicability and efficiency

Rationale, aims and objectives  Graphical monitoring tools are needed for real-time quality evaluation in intensive care unit. The variable life-adjusted display (VLAD) provides a directly interpretable assessment indicating whether the overall performance is better or worse than expected on the basis of the predicted risk of failure. The aim of this study is to quantify the ability of VLAD charts to early recognize a worsening in clinical performance.
Methods  A Monte Carlo experiment simulating the sequence of successes and failures of an intensive care unit is performed; the predicted mortality is calculated by means of the Simplified Acute Physiology Score 3 admission score. From a given position in the admissions sequence, we increased the probability of death; we calculated: (i) the surveillance system delay in responding to the mortality increase; (ii) the percentage of cases where the VLAD has been able to give an alarm within the first 5, 10, 20 and 60 deaths occurred after the increase of probability of death; and (iii) the percentage of false declarations of increase (anticipated alarms).
Results  The frequency distribution of the alarm delays shows VLAD was not always able to early detect mortality increase. Only a very small number of anticipated alarms were given.
Conclusions  Variable life-adjusted display ability to signal is mild and strictly correlated with the institution volume of activity. Therefore, the use of VLAD seems to be not always advisable, and an integration between VLAD and other well-documented tools as CUSUM charts could be preferable.     

Understanding coronary atherosclerosis in relation to obesity: is getting the distribution of body fatness using dual‐energy X‐ray absorptiometry worth the effort? A novel perspective using Bayesian Networks

Aim A relative excess of fat in the upper body region has been proven to be associated with increased coronary artery disease (CAD) risk. Dual‐energy X‐ray absorptiometry (DXA) is probably the most accurate and precise method available to study fat regional distribution and to directly measure total body fat and lean soft tissue mass. However, while several studies have investigated the abilities of obesity anthropometric measures in predicting CAD, only few studies have evaluated DXA as CAD predictor; particularly, a comparison between a model including information coming from anthropometric measurements and a model in which fat is precisely measured by DXA, is still lacking. In order to verify if CAD severity, as measured by Gensini score, is better predicted when a prognostic model includes DXA measurements rather than anthropometric measures, we compared performance obtained by two Bayesian Networks (BNs) including standard anthropometric measures and DXA, respectively. Methods Data come from 58 consecutive patients, 79% of them having suspected and 21% known CAD. Two BNs were implemented: input variables include anamnestic information, biochemical data and obesity measures. In the first model (BN1) obesity was measured by body mass index and waist‐to‐hip ratio, while in the second one (BN2) it is quantified by DXA‐derived parameters. Results Network graphs and results coming from sensitivity analysis show that in both models lipoproteins and biomarkers of inflammation act as proximal node, while obesity (independently of the chosen measure) appears to be a distal node acting by the intermediation of other variables. Both models show high predictive abilities, the mean percentage classification errors being, respectively, 14.13 and 18.87. Conclusions In our study, the BN predictive ability is slightly superior when obesity is measured using anthropometric data instead of DXA measurements. The reason probably relies on the fact that in the BN the obesity role in predicting CAD is mediated by the action of other factors that appear to be more directly influencing the outcome. Thus, the necessity to dispose of a perfect measure becomes less compulsory and the huge effort to precisely estimate body composition with complex methods as DXA could be avoided when using expert system such as BN as predictive tool.     

Application of variable life adjusted display (VLAD) in early detection of deficiency in trauma care

Early detection of deficient care is an increasingly important element of trauma audit. We aimed to assess the feasibility and demonstrate the use of a variable life adjusted display (VLAD) in trauma audit. Data from the Trauma Audit and Research Network database of Sheffield Teaching Hospitals NHS Trust were used to create a VLAD. A cumulative display of survival was plotted in which survivors were incorporated as a positive value equal to 1 minus the probability of survival, and deaths were incorporated as a negative value equal to the probability of survival. Downward deflections of the display thus indicated potentially deficient trauma care. Data from 191 consecutive patients over 1 year were plotted and displayed. The first 2 months of this period were characterised by a downward trend in the line, which may indicate suboptimum performance and provides an example of a trend that would prompt detailed review. The VLAD chart is a potentially useful "early warning" system for poor performance in trauma care. Further work should to be carried out to evaluate VLAD prospectively as an audit tool, perhaps involving comparison of VLAD charts from different institutions.     

Evaluation of short-term consequences of hypoglycemia in an intensive care unit

BACKGROUND: Introduction of strict glycemic control has increased the risk for hypoglycemia in the intensive care unit. Little is known about the consequences of hypoglycemia in this setting. We examined short-term consequences (seizures, coma, and death) of hypoglycemia in the intensive care unit. PATIENTS AND METHODS: All occurrences of hypoglycemia (glucose of <45 mg/dL) in our intensive care unit between September 1, 2002, and September 1, 2004, were identified. Patients with hypoglycemia (n = 156) were matched for time to hypoglycemia with control patients drawn from the at-risk population (nested case control method). Seizures observed within 8 hrs after hypoglycemia were scored. Discharge summaries for cases and controls were reviewed for occurrence of possible hypoglycemia-associated coma and death. A hazard ratio for in-hospital death was calculated with Cox regression analysis. RESULTS: The hazard ratio for in-hospital death was 1.03 (95% confidence interval, 0.68-1.56; p = .88) in patients with a first occurrence of hypoglycemia relative to the controls without hypoglycemia, corrected for duration of intensive care unit admittance before hypoglycemia, age, sex, and Acute Physiology and Chronic Health Evaluation II score at admission. No cases of hypoglycemia-associated death were reported. Hypoglycemic coma was reported in two patients. Seizures after hypoglycemia were observed in one patient. CONCLUSIONS: In this study, no association between incidental hypoglycemia and mortality was found. However, this data set is too small to definitely exclude the possibility that hypoglycemia is associated with intensive care unit mortality. In three patients with possible hypoglycemia-associated coma or seizures, a causal role for hypoglycemia seemed likely but could not fully be established.     

Integrating stress-related ventricular functional and angiographic data in preventive cardiology: a unified approach implementing a Bayesian network

Background Identification of key factors associated with the risk of adverse cardiovascular events and quantification of this risk using multivariable prediction algorithms are among the major advances made in preventive cardiology and cardiovascular epidemiology. Methods In the present paper, we examined clinical predictors of adverse cardiovascular events among 228 individuals with symptoms suggestive of coronary artery disease (CAD) undergoing functional (stress echocardiography) and anatomical (coronary angiography) assessment of CAD. Particularly, we evaluate the possibility to integrate simple measures that have known prognostic value and more recently discovered predictors of risk, such as stress‐related ventricular function data and angiographic data, in a unique model implementing a Bayesian network (BN). Moreover, we compared the performance of BN and the covariates hierarchy with those obtained from logistic regression model and from a set of alternative tools becoming popular in various clinical settings, including random forest classification tree analysis, artificial neural networks and support vector machine. Results Network graph and results coming from sensitivity analysis, where variables are ranked according to the gain they provided in variance reduction, seem have an easily intuitive lecture: variables that are measure of ventricular disfunction or of the extent of CAD show a greater impact in predicting event. On the other hand, anamnestic data such as diabetes, dyslipidaemia, hypertension, smoke habits, which are related to the outcome throughout a process of intermediate variables, per se have a small role in outcome prediction. BNs are able to explain a relevant part of variance (70%) and have discrimination ability superior or comparable with those to random forest classification tree analysis, artificial neural networks and support vector machine. Discussion Despite the complexity of interactions, model obtained implementing a BN seems to be able to adequately describe the relationships existing among the analysed variables. BN, being able to predict scenarios in which new variables can be incorporated as health process evolves, can measure individual's risks for adverse cardiovascular events, providing a permanent second opinion to the medical practitioner and assisting diagnostic and therapeutic process.     

How will we know patients are safer? An organization-wide approach to measuring and improving safety

OBJECTIVE: Our institution, like many, is struggling to develop measures that answer the question, How do we know we are safer? Our objectives are to present a framework to evaluate performance in patient safety and describe how we applied this model in intensive care units. DESIGN: We focus on measures of safety rather than broader measures of quality. The measures will allow health care organizations to evaluate whether they are safer now than in the past by answering the following questions: How often do we harm patients? How often do patients receive the appropriate interventions? How do we know we learned from defects? How well have we created a culture of safety? The first two measures are rate based, whereas the latter two are qualitative. To improve care within institutions, caregivers must be engaged, must participate in the selection and development of measures, and must receive feedback regarding their performance. The following attributes should be considered when evaluating potential safety measures: Measures must be important to the organization, must be valid (represent what they intend to measure), must be reliable (produce similar results when used repeatedly), must be feasible (affordable to collect data), must be usable for the people expected to employ the data to improve safety, and must have universal applicability within the entire institution. SETTING: Health care institutions. RESULTS: Health care currently lacks a robust safety score card. We developed four aggregate measures of patient safety and present how we applied them to intensive care units in an academic medical center. The same measures are being applied to nearly 200 intensive care units as part of ongoing collaborative projects. The measures include how often do we harm patients, how often do we do what we should (i.e., use evidence-based medicine), how do we know we learned from mistakes, and how well do we improve culture. Measures collected by different departments can then be aggregated to provide a hospital level safety score card. CONCLUSION: The science of measuring patient safety is immature. This article is a starting point for developing feasible and scientifically sound approaches to measure safety within an institution. Institutions will need to find a balance between measures that are scientifically sound, affordable, usable, and easily applied across the institution.     

Use of the Sequential Organ Failure Assessment score as a severity score

Objective To evaluate whether the SOFA score can be used to develop a model to predict intensive care unit (ICU) mortality in different countries.Design and setting Analysis of a prospectively collected database. Patients with ICU stay longer than 2 days were studied to develop a mortality prediction model based on measurements of organ dysfunction.Patients 748 patients from six countries.Measurements and results Two logistic regression models were constructed, one based on the SOFA maximum (SOFA Max model) and the other on variables identified by multivariate regression (SOFA Max-infection model). The H and C statistics had a p value above 0.05 for both models, but the D statistics showed a poor performance on the SOFA Max model when stratified for the presence of infection. Subsequent analysis was performed with SOFA Max-infection model. The area under the curve was 0.853. There were no statistically significant differences in observed and predicted mortalities except for one country which had a higher than predicted ICU mortality both in the overall population (28.3 vs. 19.1%) and in the noninfected patients (21.4 vs. 12.6%).Conclusions The SOFA Max adjusted for age and the presence of infection can predict mortality in this population, but in one country the ICU mortality was higher than expected. Our data do not allow us to determine the reasons behind these differences, and further studies to detect differences in mortality between countries and to elucidate the basis for these differences should be encouraged.     

Identifying quality outliers in a large,multiple-institution database by using customized versions of the Simplified Acute Physiology Score II and the Mortality Probability Model II0

OBJECTIVE: To assess whether customized versions of the Simplified Acute Physiology Score (SAPS) II and the Mortality Probability Model (MPM) II0 agree on the identity of intensive care unit quality outliers within a multiple-center database. DESIGN: Retrospective database analysis. SETTING AND PATIENTS: Patient subset of the Project IMPACT database consisting of 39,617 adult patients admitted to surgical, medical, and mixed surgical-medical intensive care units at 54 hospitals between 1995 and 1999 who met inclusion criteria for SAPS II and MPM II0. INTERVENTIONS: Customized versions of SAPS II and MPM II0 were obtained by fitting new logistic regressions to the data by using the risk score as the independent variable and outcome at hospital discharge as the dependent variable. The data set was divided randomly into a training set and a validation set. Each model was customized by using the training set; model performance was then assessed in the validation set by using the area under the receiver operating characteristic curve and the Hosmer-Lemeshow statistic. The final models were based on the entire data set. The level of agreement between the customized models on the identity of quality outliers was evaluated by using kappa analysis. MEASUREMENTS AND MAIN RESULTS: Both customized models exhibited good discrimination and good calibration in this database. The area under the receiver operating characteristic curve was 0.83 for MPM II0 and 0.872 for SAPS II following model customization. The Hosmer-Lemeshow statistic was 12.3 ( >.14) for MPM II0, and 8.17 (p >.42) for SAPS II, after customization. Kappa analysis showed only fair agreement between the two customized models with regard to the identity of the quality outliers: kappa = 0.44 (95% confidence interval, 0.24, 0.65). CONCLUSIONS: Customization of SAPS II and MPM II0 to the Project IMPACT database resulted in well-calibrated models. Despite this, the models exhibited only a moderate level of agreement in which hospitals were designated as quality outliers. Seventeen of the 54 hospitals were categorized differently depending on which of the two scoring systems was used. Therefore, the rating of quality of care appears, in part, to be a function of the prediction model used.     

对回肠造口患者主要照顾者实施家庭赋权的效果观察

目的 探讨家庭赋权在回肠造口患者主要照顾者中的应用效果。方法 选取2019年8月—2020年8月实施回肠造口手术患者的主要照顾者74例为研究对象,按随机数字表法分为观察组和对照组,每组各37例。对照组接受常规健康教育,观察组实施基于家庭赋权的健康教育。观察比较2组患者主要照顾者的照顾准备度、照顾负担及照顾能力情况。结果 经干预后,2组患者主要照顾者的照顾准备度评分较同组干预前上升,照顾负担和照顾能力评分较同组干预前均下降,且观察组的照顾准备度评分高于对照组,照顾负担及照顾能力评分低于对照组,差异均有统计学意义（P<0.05）。结论 家庭赋权护理应用于术后健康指导中,可有效帮助回肠造口患者主要照顾者提高照顾准备度、照顾能力及积极感受,减轻负担水平。     

以授课为基础的学习法和以问题为基础教学法双轨教学法在ICU临床教学中的应用

目的探讨以授课为基础的学习法（LBL）和以问题为基础的教学法（PBL）双轨教学法在实践中的互补性,以及在重症监护室临床教学中应用的效果。方法将2007-2010年在监护室轮转的学习生70人随机分成对照组和实验组,每组35人,对照组采用传统的LBL教学模式;实验组采用LBL结合PBL教学模式。并用闭卷考试和问卷调查评价教学效果。结果实验组考试总成绩、理论成绩、综合分析题成绩、护理病历书写成绩均明显高于对照组,差异有统计学意义（P〈0．01）,且实验组学生在激发学习兴趣、提高团队合作精神等方面有明显提高,差异有统计学意义（P〈0．05或P〈0．01）。结论LBL和PBL双轨教学模式对提高重症监护室临床教学具有积极的意义。     

Intensive care admission decisions for a patient with limited survival prospects: a questionnaire and database analysis

Objective To explore the concept of futility by asking clinicians for estimates of survival and admission decisions for an intensive care unit patient with little chance of survival, and to compare these estimates with results from an intensive care database.Design Questionnaire based on the presenting features of a genuine patient. It asked for estimated hospital survival, decision on intensive care admission, resuscitation status and importance of family views. Analysis of a regional intensive care database.Setting Physicians working in British intensive care unitsParticipants We received 169 replies, 146 from consultants.Measurements and results Median estimated hospital survival was 5%; 60% of consultants and 76% of trainees would have admitted the patient, with 9% and 14%, respectively, prepared to perform further cardiopulmonary resuscitation. Among those estimating survival probability as less than 1%, 17.2% would have admitted the patient. Family opinions were vital to 4.3% of respondents and unimportant to 9.8%. There were 251 patients in the database with similar physiological derangements. Their observed hospital mortality was 91%. At intensive care admission an admitting physician assessed 111 of these patients as expected to die. Mortality in this group was 99.1% (one survivor).Conclusions Experienced intensivists did not agree on estimated survival. Even when estimates agreed, admission decisions varied. Database analysis suggested that clinical judgement is relevant when assessing the risk of dying. Lack of consensus on survival estimates and admission decisions suggests that it would be difficult to achieve agreement on appropriate use of intensive care resources and on what constitutes futile treatment.     

The development and evaluation of a paramedic-staffed mobile intensive care unit for inter-facility patient transport

OBJECTIVE: As the role of paramedics evolves, evaluation of their ability to accomplish an expanded scope of practice is necessary. The objective of this study was to determine whether specially trained paramedics can monitor and treat patients appropriately during interfacility transports that traditionally have required the use of supplemental, hospital-based personnel. METHODS: A paramedic-staffed mobile intensive care unit was developed as a cooperative program between Huron Valley Ambulance and the Washtenaw/Livingston County Medical Control Authority. This prospective observational study involved 111 patients requiring interfacility transport, conveyed by a paramedic-staffed mobile intensive care unit. A change in the Acute Physiologic and Chronic Health Evaluation (APACHE II) score components of mean arterial pressure, heart rate, and respiratory rate at the beginning and end of the transport was used to evaluate the ability of the paramedics to accomplish the transfer appropriately. RESULTS: APACHE II scores increased in 20 patients, decreased in 16, and were unchanged in 75. The mean value for the change in APACHE score was 0.11 (95% confidence interval: -0.11-0.33). CONCLUSION: Specially trained paramedics can monitor and treat patients appropriately during interfacility transfers that traditionally would have required supplementation with additional hospital staff.     

Comparison of Linear and Sector Array Probe for Handheld Lung Ultrasound in Invasively Ventilated ICU Patients

International guidelines do not recommend a specific probe for assessment of lung aeration using lung ultrasound (LUS). The aim of this study was to assess the concordance between linear and sector array probes of a handheld ultrasound device in assessment of lung aeration in invasively ventilated intensive care unit patients. This study included intensive care unit patients who were expected to be ventilated for longer than 24 h. A 12-region LUS exam was performed with a linear and a sector array probe. In each image, the LUS aeration score and number of B-lines were determined. Adding the LUS aeration scores of all regions resulted in a global LUS aeration score. Agreement between the two probes was calculated using intra-class correlation coefficients (ICCs). A total of 30 LUS exams were performed in 19 patients, resulting in a total of 328 pairs of images. Twenty-nine pairs of images were excluded from analysis because the images from the linear probe could not be scored. ICCs calculated for the remaining images revealed good concordance the LUS aeration scores for individual images (ICC = 0.73, 95% confidence interval 0.67–0.78), number of B-lines (ICC = 0.79, 95% confidence interval 0.72–0.83) and global LUS aeration score (ICC = 0.74, 95% confidence interval 0.52–0.87). In conclusion, there is good concordance between linear and sector array probes of a handheld ultrasound device in assessment of lung aeration patterns in mechanically ventilated intensive care unit patients. However, in roughly 10% of the images acquired using the linear probe, the aeration pattern could not be scored.     

Internal and external validation of the NOSEP prediction score for nosocomial sepsis in neonates

OBJECTIVE: To evaluate the performance of a scoring system (NOSEP) to predict nosocomial sepsis in neonates at the hospital where the score was developed (internal validation) and in an independent data set from other centers (external validation). DESIGN: Multiple center prospective cohort study. SETTING: Six neonatal intensive care units from the Flanders in Belgium. PATIENTS: We analyzed two groups of patients: 62 episodes of presumed nosocomial sepsis in the internal validation cohort and 93 episodes of presumed nosocomial sepsis in a multiple center external validation cohort. INTERVENTIONS: Assessment of the predictive power of the NOSEP score 24 hrs preceding sepsis workup and the patients' basic demographic characteristics and co-morbidity was performed. Diagnosis of nosocomial sepsis and the microbiology results were registered. MAIN RESULTS: The NOSEP score's discriminative capability was very good in the internal validation (area under receiver operating characteristic curve = 0.73 +/- 0.08 [sem]). The NOSEP score performed satisfactory in the external validation (area under receiver operating characteristic curve = 0.66 +/- 0.06). The calibration capability in both validation sets as measured by goodness-of-fit tests (internal validation, p =.56; external validation, p =.48) was good. An improvement of the NOSEP score was obtained for the external centers by redefining the cut-off of the items of the NOSEP score (area under receiver operating characteristic curve for NOSEP-NEW-I = 0.71 +/- 0.05) or adding co-morbidity factors (area under receiver operating characteristic curve for NOSEP-NEW-II = 0.82 +/- 0.04), with good calibration performance (goodness-of-fit test, p >.50). Finally, the fit of the NOSEP score demonstrated no significant variation across subgroups of patients. CONCLUSIONS: The predictive power of the original NOSEP score is very good in neonates at the original neonatal intensive care unit. In other neonatal intensive care units, its discriminatory performance is satisfactory but could be improved after modification of the variables in the model or adding additional variables. To use such a NOSEP score in other neonatal intensive care units, its accuracy has to be validated and adjusted if necessary.     

Pediatric Index of Mortality 2 score in Italy: a multicenter,prospective, observational study

Objectives To assess the performance of the Pediatric Index of Mortality (PIM) 2 score in Italian pediatric intensive care units (PICUs). Design Prospective, observational, multicenter, 1-year study. Setting Eighteen medical–surgical PICUs. Patients Consecutive patients (3266) aged 0–16 years admitted between 1 March 2004 and 28 February 2005. Interventions None. Measurements and main results To assess the performance of the PIM2 score, discrimination and calibration measures were applied to all children admitted to the 18 PICUs, in the entire population and in different groups divided for deciles of risk, age and admission diagnosis. There was good discrimination, with an area under the receiver operating characteristic (ROC) curve of 0.89 (95% CI 0.86–0.91) and good calibration of the scoring system [non-significant differences between observed and predicted deaths when the population was stratified according to deciles of risk (χ² 9.86; 8 df, p = 0.26) for the whole population]. Conclusions The PIM2 score performed well in this sample of the Italian pediatric intensive care population. It may need to be reassessed in the injury and postoperative groups in larger studies. The members of the SISPe group are listed in the appendix.     

The pregnant woman with a myocardial infarction: nursing diagnosis

Critical care nurses in emergency, cardiac, or medical intensive care units may care for women who have experienced a myocardial infarction during pregnancy. Nursing management of the pregnant patient with a myocardial infarction (MI) requires an understanding of the normal physiology of pregnancy, the deviations from health with an MI, and an ability to integrate this knowledge to provide skillful care to unique and very ill patients. Here the authors describe caring for a pregnant patient in cardiac care, while a later article in this tissue focuses on the critical care nurse's role in teaching obstetric nurses arrhythmia interpretation when the patient remains on an obstetric unit. Collaboration between the critical care nurse and obstetric nurse is essential to care for these complex patients.     

The utility of scoring systems in critically ill cirrhotic patients admitted to a general intensive care unit

Purpose

This study aimed to establish which prognostic scoring tool provides the greatest discriminative ability when assessing critically ill cirrhotic patients in a general intensive care unit (ICU) setting.

Methods

This was a 12-month, single-centered prospective cohort study performed in a general, nontransplant ICU. Forty clinical and demographic variables were collected on admission to calculate 8 prospective scoring tools. Patients were followed up to obtain ICU and inhospital mortality. Receiver operating characteristic curve analysis was used to determine the discriminative ability of the scores. Univariate and multivariate analyses were used to identify any independent predictors of mortality in these patients. The incorporation of any significant variables into the scoring tools was assessed.

Results

Fifty-nine cirrhotic patients were admitted over the study period, with an ICU mortality of 31%. All scores other than the renal-specific Acute Kidney Injury Network score had similar discriminative abilities, producing area under the curves of between 0.70 and 0.76. None reached the clinically applicable level of 0.8. The Sequential Organ Failure Assessment score was the best performing score.Lactate and ascites were individual predictors of ICU mortality with statistically significant odds ratios of 1.69 and 5.91, respectively. When lactate was incorporated into the Child-Pugh score, its prognostic accuracy increased to a clinically applicable level (area under the curve, 0.86).

Conclusions

This investigation suggests that established prognostic scoring systems should be used with caution when applied to the general, nontransplant ICU as compared to specialist centers. Our data suggest that serum arterial lactate may improve the prognostic ability of these scores.     

Review of a large clinical series: Predicting death for patients with abdominal septic shock

This paper reports the result of the MEDAN project that analyzes a multicenter septic shock patient data collection. The mortality prognosis based on 4 scores that are often used is compared with the prognosis of a trained neural network. We built an alarm system using the network classification results. Method. We analyzed the data of 382 patients with abdominal septic shock who were admitted to the intensive care unit (ICU) from 1998 to 2002. The analysis includes the calculation of daily sepsis-related organ failure assessment (SOFA), Acute Physiological and Chronic Health Evaluation (APACHE) II, simplified acute physiology score (SAPS) II, multiple-organ dysfunction score (MODS) scores for each patient and the training and testing of an appropriate neural network. Results. For our patients with abdominal septic shock, the analysis shows that it is not possible to predict their individual fate correctly on the day of admission to the ICU on the basis of any current score. However, when the trained network computes a score value below the threshold during the ICU stay, there is a high probability that the patient will die within 3 days. The trained neural network obtains the same outcome prediction performance as the best score, the SOFA score, using narrower confidence intervals and considering three variables only: systolic blood pressure, diastolic blood pressure and the number of thrombocytes. We conclude that the currently best available score for abdominal septic shock may be replaced by the output of a trained neural network with only 3 input variables.     

Prospective validation of the International Society of Thrombosis and Haemostasis scoring system for disseminated intravascular coagulation

OBJECTIVES: A diagnosis of disseminated intravascular coagulation (DIC) is hampered by the lack of an accurate diagnostic test. Based on the retrospective analysis of studies in patients with DIC, a scoring system (0-8 points) using simple and readily available routine laboratory tests has been proposed. The aim of this study was to prospectively validate this scoring system and assess its feasibility, sensitivity, and specificity in a consecutive series of intensive care patients. DESIGN: Prospective cohort of intensive care patients. SETTING: Adult intensive care unit in a tertiary academic center. PATIENTS: Consecutive patients with a clinical suspicion of disseminated intravascular coagulation. INTERVENTIONS: Patients were followed during their admission to the intensive care unit, and the DIC score was calculated every 48 hrs and compared with a "gold standard" based on expert opinion. In addition, an activated partial thromboplastin time (aPTT) waveform analysis, which has been reported to be a good predictor for the absence or presence of DIC, was performed. MEASUREMENTS AND MAIN RESULTS: We analyzed 660 samples from 217 consecutive patients. The prevalence of DIC was 34%. There was a strong correlation between an increasing DIC score and 28-day mortality (for each 1-point increment in the DIC score, the odds ratio for mortality was 1.25). The sensitivity of the DIC score was 91% and the specificity 97%. An abnormal aPTT waveform was seen in 32% of patients and correlated well with the presence of DIC (sensitivity 88%, specificity 97%). In 19% of patients, the aPTT waveform-based diagnosis of DIC preceded the diagnosis based on the scoring system. CONCLUSIONS: A diagnosis of DIC based on a simple scoring system, using widely available routine coagulation tests, is sufficiently accurate to make or reject a diagnosis of DIC in intensive care patients with a clinical suspicion of this condition. An aPTT waveform analysis is an interesting and promising tool to assist in the diagnostic management of DIC.