Cross-validation of a modified score to predict mortality in cancer patients admitted to the intensive care unit

Purpose

The aim of this study was to cross-validate an automated and customized severity of illness score as a means of predicting death among adult cancer patients admitted to the intensive care unit (ICU).

Materials and Methods

We conducted a retrospective study of ICU discharges between January 1, 2001, and December 31, 2005, in a university comprehensive cancer center. We randomly selected training and validation samples in 2 ICU groups (medical and surgical patients). We used logistic regression to calculate the probabilities of death in the ICU and in-hospital death in training samples and applied these probabilities to the validation samples to calculate sensitivity and specificity, construct curves, and determined the areas under the receiver operating characteristic curve (AUC).

Results

We included 6880 patients. In predicting ICU mortality, the AUC was 0.77 (95% confidence interval [CI], 0.73-0.82) for the medical validation group and 0.8207 (95% CI, 0.7304-0.9109) for the surgical validation group. For in-hospital mortality, the AUCs for the groups of medical and surgical patients were 0.73 (95% CI, 0.69-0.76) and 0.77 (95% CI, 0.73-0.80), respectively.

Conclusions

The modified Sequential Organ Failure Assessment score is a good and valid predictor of cancer patients' risk of dying in the ICU and/or hospital despite the modifications needed to automate the score using existing electronic data.     

Prognosis of hematologic malignancies does not predict intensive care unit mortality

OBJECTIVE: To evaluate the correlation between specific prognosis of hematologic malignancies on the one hand and intensive care unit and hospital mortality in critically ill patients with hematologic malignancies on the other hand. DESIGN: Observational study during a 10-yr period. SETTING: A 22-bed medical-surgical intensive care unit. PATIENTS: A total of 84 consecutive patients with nonterminal hematologic malignancies with medical complications requiring intensive care. INTERVENTIONS: None. MEASUREMENTS: Demographic factors, acute physiology and organ dysfunction scores, microbiology, therapeutic support, and hematologic factors data on admission and during the intensive care unit stay were collected, together with mortality follow-up. Based on specific-disease prognostic factors and related published survival curves, the prognosis of hematologic malignancies was assessed and defined as good, intermediate, or poor according to a 3-yr survival probability of >50%, 20-50%, or <20%, respectively. MAIN RESULTS: Prognosis of hematologic malignancies does not predict intensive care unit or hospital mortality and almost reaches significance for 6-mo mortality (53%, 71%, and 84% rate for patients with good, intermediate, and poor prognosis, respectively, p =.058), but it determines long-term survival (p =.008). Intensive care unit, hospital, and 6-mo overall mortality rates were 38%, 61%, and 75%, respectively. Using multivariate analysis, intensive care unit mortality was best predicted on admission by respiratory failure and fungal infection, whereas hospital mortality was predicted by the number of organ failures, the bone marrow transplant status, and the presence of fungal infection. The Acute Physiology and Chronic Health Evaluation II and the Simplified Acute Physiology Score II had no prognostic value, whereas the difference of the Multiple Organ Dysfunction Score between at the time of admission and at day 5 allowed quick prediction of hospital mortality. Diseases with the poorest 6-mo prognosis were acute myeloid leukemia and non-Hodgkin lymphoma.CONCLUSION The severity of the underlying hematologic malignancies does not influence intensive care unit or hospital mortality. Short-term prognosis is exclusively predicted by acute organ dysfunctions and by a pathogen's aggressiveness. Therefore, reluctance to admit patients with nonterminal hematologic malignancies to the intensive care unit based only on the prognosis of their underlying hematologic malignancy does not seem justified.     

Serum adiponectin upon admission to the intensive care unit may predict mortality in critically ill patients

Purpose

Adiponectin has been proposed as an important regulator of glucose metabolism influencing obesity and insulin resistance, which are important risk factors for the outcome of critically ill patients. Moreover, experimental models of inflammation suggest protective anti-inflammatory properties of adiponectin. We therefore investigated the potential pathogenic role and prognostic value of circulating adiponectin levels in critical illness.

Materials and methods

One hundred seventy critically ill patients (122 with sepsis and 48 without sepsis) were prospectively studied at admission to the medical intensive care unit (ICU) and compared with 60 healthy controls. Patients' survival was followed for approximately 3 years.

Results

Adiponectin serum concentrations did not differ between healthy controls and critically ill patients, neither in patients with nor in patients without sepsis. However, patients with decompensated liver cirrhosis had significantly elevated serum adiponectin levels. Likewise to non-critically ill subjects, ICU patients with preexisting diabetes or obesity displayed significantly reduced circulating adiponectin. Inflammatory cytokines did not correlate with serum adiponectin. Interestingly, low adiponectin levels at ICU admission were an independent positive predictor of short-term and overall survival.

Conclusions

Although serum concentrations did not differ in critically ill patients from controls, low adiponectin levels at admission to ICU have been identified as an independent predictor of survival.     

Predictors of mortality in stroke patients admitted to an intensive care unit

OBJECTIVE: Improved pathophysiologic insight and prognostic information regarding in-hospital risk of mortality among stroke patients admitted to an intensive care unit. DESIGN: Retrospective analysis. SETTING: Neurology/neurosurgery intensive care unit in a tertiary care university medical center. PATIENTS: A total of 63 consecutive ischemic stroke patients. INTERVENTIONS: Patients were classified according to in-hospital mortality. Charts were reviewed to retrospectively generate an admitting Acute Physiology and Chronic Health Evaluation (APACHE) II score. The APACHE II score and its individual components were assessed for predicting subsequent death. MEASUREMENTS AND MAIN RESULTS: Of 63 patients, 13 died and 50 survived to either discharge or surgical intervention. The mean admitting APACHE II score of survivors (6.9) was lower than that of patients who died (17.2; p < .0001). None of the 33 patients with a score <9 died, compared with 43% of those with a score > or =9. A score > or =18 was uniformly associated with fatal outcome (n = 8). Univariate analysis identified APACHE II total score, Glasgow Coma Scale score, temperature, pH, and white blood cell count as significant predictors of death. Among multivariate logistic regression models examining the components of the APACHE II score, the model containing white blood cells, temperature, and creatinine best predicted death. CONCLUSIONS: Several features of the APACHE II score are associated with risk of death in this patient population. The findings suggest particular physiologic derangements that are associated with, and may contribute to, increased mortality in critically ill patients with acute ischemic stroke.     

Clinician predictions of intensive care unit mortality

OBJECTIVE: Predicting outcomes for critically ill patients is an important aspect of discussions with families in the intensive care unit. Our objective was to evaluate clinical intensive care unit survival predictions and their consequences for mechanically ventilated patients. DESIGN: Prospective cohort study. SETTING: Fifteen tertiary care centers. PATIENTS: Consecutive mechanically ventilated patients > or = 18 yrs of age with expected intensive care unit stay > or = 72 hrs. INTERVENTIONS: We recorded baseline characteristics at intensive care unit admission. Daily we measured multiple organ dysfunction score (MODS), use of advanced life support, patient preferences for life support, and intensivist and bedside intensive care unit nurse estimated probability of intensive care unit survival. MEASUREMENTS AND MAIN RESULTS: The 851 patients were aged 61.2 (+/- 17.6, mean + SD) yrs with an Acute Physiology and Chronic Health Evaluation (APACHE) II score of 21.7 (+/- 8.6). Three hundred and four patients (35.7%) died in the intensive care unit, and 341 (40.1%) were assessed by a physician at least once to have a < 10% intensive care unit survival probability. Independent predictors of intensive care unit mortality were baseline APACHE II score (hazard ratio, 1.16; 95% confidence interval, 1.08-1.24, for a 5-point increase) and daily factors such as MODS (hazard ratio, 2.50; 95% confidence interval, 2.06-3.04, for a 5-point increase), use of inotropes or vasopressors (hazard ratio, 2.14; 95% confidence interval, 1.66-2.77), dialysis (hazard ratio, 0.51; 95% confidence interval, 0.35-0.75), patient preference to limit life support (hazard ratio, 10.22; 95% confidence interval, 7.38-14.16), and physician but not nurse prediction of < 10% survival. The impact of physician estimates of < 10% intensive care unit survival was greater for patients without vs. those with preferences to limit life support (p < .001) and for patients with less vs. more severe organ dysfunction (p < .001). Mechanical ventilation, inotropes or vasopressors, and dialysis were withdrawn more often when physicians predicted < 10% probability of intensive care unit survival (all ps < .001). CONCLUSIONS: Physician estimates of intensive care unit survival < 10% are associated with subsequent life support limitation and more powerfully predict intensive care unit mortality than illness severity, evolving or resolving organ dysfunction, and use of inotropes or vasopressors.     

Long-term mortality of patients admitted to the intensive care unit for gastrointestinal bleeding

OBJECTIVES: Long-term mortality data for gastrointestinal (GI) bleeders is scarce in the literature. The aim of this prospective study was to determine the long-term mortality of patients admitted to two intensive care units with a primary diagnosis of GI bleeding. METHODS: The charts of patients admitted to the medical intensive care unit (MICU) with GI bleeding were reviewed and the data of the patients' first day in the MICU was used to calculate APACHE III and Charlson scores. A GI bleeding score was computed by combining endoscopic findings and units of blood transfused during patients' MICU stay. Mortality data was obtained from the Vital Statistics Department of Montgomery County, Dayton, OH. Survival data and predictability of mortality based on these scores were assessed. RESULTS: Mean age of the 66 patient cohort was 58.6 years. Twenty-six of 51 patients with upper GI bleeding, five of seven patients with lower GI bleeding, and four of eight patients with unknown site of bleeding died within 7 years. Charlson score correlated significantly with the mortality prediction, whereas the APACHE III and bleeding scores did not. CONCLUSIONS: All-cause and GI bleeding-related 7-year mortality for patients admitted to the MICU with GI bleeding was lower than the rates cited in the literature. The Charlson score was helpful in predicting mortality.     

The feasibility of measuring frailty to predict disability and mortality in older medical intensive care unit survivors

Purpose

To determine whether frailty can be measured within 4 days prior to hospital discharge in older intensive care unit (ICU) survivors of respiratory failure and whether it is associated with post-discharge disability and mortality.

Materials and Methods

We performed a single-center prospective cohort study of 22 medical ICU survivors age 65 years or older who had received noninvasive or invasive mechanical ventilation for at least 24 hours. Frailty was defined as a score of ≥ 3 using Fried’s 5-point scale. We measured disability with the Katz Activities of Daily Living. We estimated unadjusted associations between Fried’s frailty score and incident disability at 1-month and 6-month mortality using Cox proportional hazard models.

Results

The mean (SD) age was 77 (9) years, mean Acute Physiology and Chronic Health Evaluation II score was 27 (9.7), mean frailty score was 3.4 (1.3), and 18 (82%) were frail. Nine subjects (41%) died within 6 months, and all were frail. Each 1-point increase in frailty score was associated with a 90% increased rate of incident disability at 1-month (rate ratio: 1.9, 95% CI 0.7-4.9) and a threefold increase in 6-month mortality (rate ratio: 3.0, 95% CI 1.4-6.3).

Conclusions

Frailty can be measured in older ICU survivors near hospital discharge and is associated with 6-month mortality in unadjusted analysis. Larger studies to determine if frailty independently predicts outcomes are warranted.     

Markers of inflammation as determinants of mortality in intensive care unit patients

In this study, the investigators explored the relationship between mortality rate and serum levels of C-reactive protein (CRP), erythrocyte sedimentation ratio (ESR), albumin, and hemoglobin, leukocyte, and platelet counts of patients at the time of first admission to the intensive care unit (ICU). A total of 123 patients were admitted to 2 different ICUs. In the emergency departments, serum levels of CRP, ESR, and albumin and hematologic parameters of 81 patients who died and 42 patients who survived were compared. A Studentt test and the χ² test were used for statistical analyses. Mean CRP and ESR levels and leukocyte counts were higher in nonsurvivor than in survivor groups (P<.001 for all). Additionally, serum CRP and ESR elevations and leukocyte counts were determined to be individually related to mortality (P<.001, P<.05, and P<.05, respectively). The investigators concluded that initial serum levels of CRP and ESR and leukocyte counts can be used as determinants of mortality in ICU patients.     

Short-term and long-term mortality in very elderly patients admitted to an intensive care unit

Objective To report short-term and long-term mortality of very elderly ICU patients and to determine independent risk factors for short-term and long-term mortalityDesign and setting Retrospective cohort study in the medical/surgical ICU of a tertiary university teaching hospital.Patients 578 consecutive ICU patients aged 80 years or older.Results Demographic, physiological, and laboratory values derived from the first 24 h after ICU admission. ICU mortality of unplanned surgical (34.0%) and medical patients (37.7%) was higher than that of planned surgical patients (10.6%), as was post-ICU hospital mortality (26.5% and 29.7% vs. 4.4%). Mortality 12 months after hospital discharge, including ICU and hospital mortality, was 62.1% in unplanned surgical and 69.2% in medical patients vs. 21.6% in planned patients. Only median survival of planned surgical patients did not differ from survival in the age- and gender-matched general population. Independent risk factors for ICU mortality were lower Glasgow Coma Scale score, higher SAPS II score, the lowest urine output over 8 h, abnormal body temperature, low plasma bicarbonate levels, and higher oxygen fraction of inspired air. High urea concentrations and admission type were risk factors for hospital mortality, and high creatinine concentration was an independent risk factor for 12-month mortality.Conclusion Mortality in very elderly patients after unplanned surgical or medical ICU admission is higher than after planned admission. The most important factors independently associated with ICU mortality were related to the severity of illness at admission. Long-term mortality was associated with renal function.This article is discussed in the editorial available at:     

Sagittal abdominal diameter may effectively predict future complications and increased mortality in intensive care unit patients with severe sepsis

Purpose

To investigate whether increased visceral adipose tissue is a risk factor for increased morbidity and mortality in intensive care patients with severe sepsis.

Materials and Methods

In this prospective cohort study, body mass index (BMI) and sagittal abdominal diameter (SAD) were measured in all patients with severe sepsis immediately after admission in the intensive care unit (ICU). The patients were followed up until death or discharge from ICU. The study’s primary outcome measure was mortality until day 60 after admission, while secondary outcomes were morbidity, length of stay, and length of ventilation in ICU.

Results

Of the 30 patients, 24 (80%) developed septic shock, 6 (20%) multiple organ dysfunction syndrome, 13 (43.3%) necessitated continuous venovenous hemodiafiltration, while 6 (20%) of them died. BMI and SAD had a statistically significant positive linear correlation with ICU length of stay (P < .001) and length of ventilation (P ≤ .001). However, only SAD was significantly correlated with the development of multiple organ dysfunction syndrome (P = .033), the need for continuous venovenous hemodiafiltration (P = .004), and death (P = .033).

Conclusion

An increased SAD may effectively predict future complications and increased mortality in intensive care unit patients with severe sepsis.     

Objective assessment of changing mortality risks in pediatric intensive care unit patients

OBJECTIVE: To develop and validate a mortality risk predictor based on physiologic data that estimates daily the probability of a patient dying within the next 24 hrs as that probability changes with disease and recovery. SETTING: Nine pediatric ICUs in tertiary care centers. Patients: Data from 1,401 patients (116 deaths, 5,521 days of care) were used for predictor development, and 1,227 patients (105 deaths, 4,597 days of care) provided data for predictor validation. METHODS: The predictor was developed by logistic regression analysis using the Pediatric Risk of Mortality scores of all previous days as potential predictor variables. Performance was measured by the area under the receiver operating characteristic curve (Az), and by the comparison of the daily predicted vs. observed patient status in five mortality risk groups (less than 0.01, 0.01 to 0.05, 0.05 to 0.15, 0.15 to 0.3, greater than 0.3) using chi-square goodness-of-fit tests. MEASUREMENTS AND MAIN RESULTS: Only the most recent and the admission day Pediatric Risk of Mortality scores (with a weighting ratio of 3:1) contributed significantly (p less than .05) to the prediction. The overall prediction attained an accuracy of Az = 0.904. The daily number and distribution of survivors and nonsurvivors in the five mortality risk groups were well predicted in the total sample (chi 2 [5 degrees of freedom] = 2.51; p greater than .75), and each ICU separately (chi 2 [5 degrees of freedom] range 2.41 to 7.96; all p greater than .15). This dynamic predictor improved (p less than .01) ICU outcome prediction over an admission-day predictor and, in the opinion of the authors, is essential for pediatric ICU efficiency analysis. CONCLUSIONS: The predictor is valid for assessing the 24-hr mortality risk in pediatric ICU patients hospitalized in other tertiary care institutions, different from those used for predictor development. The predicted mortality risks allow prospective patient stratification into risk groups. The ability of this predictor to follow risk changes over time expands its applicability over static predictors by enabling the charting of patient courses, and permitting ICU efficiency analysis.     

Delayed treatment of delirium increases mortality rate in intensive care unit patients

Delirium in the intensive care unit (ICU) is a serious complication associated with a poor outcome in critically ill patients. In this prospective observational study of the effect of a delay in delirium therapy on mortality rate, 418 ICU patients were regularly assessed using the Delirium Detection Score (DDS). The departmental standard required that if delirium was diagnosed (DDS >7), therapy should be started within 24 h. In total, 204 patients (48.8%) were delirious during their ICU stay. In 184 of the delirious patients (90.2%), therapy was started within 24 h; in 20 patients (9.8%), therapy was delayed. During their ICU stay, patients whose delirium treatment was delayed were more frequently mechanically ventilated, had more nosocomial infections (including pneumonia) and had a higher mortality rate than patients whose treatment was not delayed. Thus, it would appear that a delay in initiating delirium therapy in ICU patients was associated with increased mortality.     

Impact of secondary sepsis on mortality in adult intensive care unit patients

RationaleSeptic patients admitted to the intensive care unit (ICU) suffer from immune dysregulation, potentially leading to a secondary sepsis episode. This study aims to (i) assess the secondary sepsis rate, (ii) compare the second with the first episodes in terms of demographics, clinical and laboratory characteristics, and outcomes, and iii) evaluate the outcome of secondary sepsis.MethodsA single-center, retrospective study (2014–2017) was conducted in a Greek ICU, including consecutive cases of adult patients admitted to the ICU for at least 48 h with a principal admission diagnosis of sepsis and stayed for at least 48 h. We searched for a secondary episode of sepsis following the primary-one. We performed survival analyses with Cox proportional hazard, Fine-Gray, and multistate models.ResultsIn this study, 121 patients that fulfilled the eligibility criteria were included. The secondary sepsis group included 28 (23.1 %) patients, with episode onset, median (interquartile range), 9.5 (7.7–16.2) days after ICU admission, who had less frequently had a medical admission diagnosis, a microbiologically confirmed first episode, and the C-reactive protein was lower. The overall ICU mortality of the cohort was 44.6 %. The group that developed secondary sepsis had higher mortality, but significance was lost in Cox regression [Hazard ratio (95 % CI) 0.59(0.31–1.16)]. However, after multistate modeling adjustment, the attributable mortality was estimated at 43.9 % (95 %CI ± 14.8 %).ConclusionSecondary sepsis was evident in a quarter of the study participants and may be associated with an increased risk of death.     

Admitting cancer patients to the intensive care unit

The allocation of critical care resources must follow criteria of distributive justice. Because most societies cannot indefinitely expand medical care costs, difficult decisions on the quality and quantity of care that can be rendered to each patient are inevitable. Data on which objective decisions can be based are currently being gathered at many levels. It is reasonable to anticipate that over the next few years regulations will be formulated to decide which patients can be admitted to the ICU. Critical care physicians have the right and obligation to be involved in all aspects of these decision-making processes.     

Prediction of mortality in an Indian intensive care unit

Objective To compare hospital outcome prediction using an artificial neural network model, built on an Indian data set, with the APACHE II (Acute Physiology and Chronic Health Evaluation II) logistic regression model.Design Analysis of a database containing prospectively collected data.Setting Medical-neurological ICU of a university hospital in Mumbai, India.Subjects Two thousand sixty-two consecutive admissions between 1996 and1998.Interventions None.Measurements and results The 22 variables used to obtain day-1 APACHE II score and risk of death were recorded. Data from 1,962 patients were used to train the neural network using a back-propagation algorithm. Data from the remaining 1,000 patients were used for testing this model and comparing it with APACHE II. There were 337 deaths in these 1,000 patients; APACHE II predicted 246 deaths while the neural network predicted 336 deaths. Calibration, assessed by the Hosmer-Lemeshow statistic, was better with the neural network (=22.4) than with APACHE II (=123.5) and so was discrimination (area under receiver operating characteristic curve =0.87 versus 0.77, p=0.002). Analysis of information gain due to each of the 22 variables revealed that the neural network could predict outcome using only 15 variables. A new model using these 15 variables predicted 335 deaths, had calibration (=27.7) and discrimination (area under receiver operating characteristic curve =0.88) which was comparable to the 22-variable model (p=0.87) and superior to the APACHE II equation (p<0.001).Conclusion Artificial neural networks, trained on Indian patient data, used fewer variables and yet outperformed the APACHE II system in predicting hospital outcome.Electronic Supplementary Material Supplementary material is available in the online version of this article at Part of this work was presented at the Sixth Annual Critical Care Congress of the Indian Society for Critical Care Medicine, Bangalore, India     

A comparison of the opinions of intensive care unit staff and family members of the treatment intensity received by patients admitted to an intensive care unit: A multicentre survey

BackgroundAchieving shared decision-making in the intensive care unit (ICU) is challenging because of limited patient capacity, leading to a reliance on surrogate decision-makers. Prior research shows that ICU staff members often perceive that patients receive inappropriate or futile treatments while some surrogate decision-makers of patients admitted to the ICU report inadequate communication with physicians. Therefore, understanding the perceptions of both ICU staff and surrogate decision-makers around wishes for ICU treatments is an essential component to improve these situations.ObjectivesThe objectives of this study were to compare perceptions of ICU staff with surrogate decision-makers about the intensity and appropriateness of treatments received by patients and analyse the causes of any incongruence.MethodsA multicentred, single-day survey of staff and surrogate decision-makers of ICU inpatients was conducted across four Australian ICUs in 2014. Patients were linked to a larger prospective observational study, allowing comparison of patient outcomes.ResultsTwelve of 32 patients were identified as having a mismatch between staff and surrogate decision-maker perceptions. For these 12 patients, all 12 surrogate decision-makers believed that the treatment intensity the patient was receiving was of the appropriate intensity and duration. Mismatched patients were more likely to be emergency admissions to ICU compared with nonmismatched patients (0.0% vs 42.1%, p = 0.012) and have longer ICU admissions (7.5 vs 3, p = 0.022). There were no significant differences in perceived communication (p = 0.61).ConclusionsFamily members did not share the same perceptions of treatment with ICU staff. This may result from difficulty in prognostication; challenges in conveying poor prognoses to surrogate decision-makers; and the accuracy of surrogate decision-makers.     

Severe acidosis does not predict fatal outcomes in intensive care unit patients: A retrospective analysis

Purpose

Severe acidosis is a potentially life-threatening acid-base imbalance. The outcome of patients with severe acidosis has only been anecdotally described. We therefore assessed the discharge rate of such patients from the intensive care unit (ICU) and survival time after the event.

Methods

A retrospective evaluation of medical records of patients admitted to the ICU of Tel Aviv Medical Center between 2005 and 2010, in whom arterial blood pH less than 6.8 was documented during their ICU stay, was performed.

Results

Twenty-eight patients were suitable for study entry. Septic shock was the most common underlying medical condition (33%). Nine (32.1%) patients were either discharged alive or survived for at least 30 days in the ICU after their arterial blood pH measurement was less than 6.8. More than a quarter of the patients with life-threatening acidosis (n = 8; 28.6%) were discharged home and returned to their prehospitalization daily activity. Mean follow-up period for these patients was 132 ± 111 weeks. Multivariate analysis identified hyperkalemia, Acute Physiology and Chronic Health Evaluation II score, and Glasgow Coma Scale as determinants for ICU death after severe acidosis.

Conclusions

A significant number of patients can outlast severe acidosis and return to their prehospitalization status. Larger studies are needed to define the patient population most likely to benefit from aggressive resuscitation efforts during severe acidosis.     

Platelet indices are novel predictors of hospital mortality in intensive care unit patients

Background and objective

Platelet volume indices (PVIs) are inexpensive and readily available in intensive care units (ICUs). However, their association with mortality has never been investigated in a critical care setting. Our study aimed to investigate the association of PVI and mortality in unselected ICU patients.

Methods

This was a retrospective study conducted in a mixed 24-bed ICU from September 2010 to December 2012. Platelet indices including mean platelet volume (MPV), platelet distribution width (PDW), platelet count, and plateletcrit were measured on ICU entry. Univariable analyses were performed to screen for variables that were associated with mortality. Variables with P < .1 were incorporated into a regression model to adjust for the odds ratio of platelet indices.

Results

A total of 1556 patients were included during the study period, including 1113 survivors and 443 nonsurvivors (mortality rate: 28.47%). Platelet distribution width and MPV were significantly higher in nonsurvivors than in survivors. Platelet distribution width greater than 17% and MPV greater than 11.3 fL were independent risk factors for mortality (adjusted odds ratio: 1.92 and 1.84, respectively) and survival time (hazards ratio: 1.77 and 1.75, respectively).

Conclusion

Higher MPV and PDW are associated with increased risk of death, whereas the decrease in plateletcrit is associated with increased mortality risk.