Predictors of In-hospital Mortality and Acute Myocardial Infarction in Thrombotic Thrombocytopenic Purpura

Balasubramaniyam, Nivas; Kolte, Dhaval; Palaniswamy, Chandrasekar; Yalamanchili, Kiran; Aronow, Wilbert S.; McClung, John A.; Khera, Sahil; Sule, Sachin; Peterson, Stephen J.; Frishman, William H.

doi:10.1016/j.amjmed.2013.03.021

Cited by 32 publications

(35 citation statements)

References 25 publications

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“…Increasing age was an important predictor of survival with older patients showing worse outcomes. In particular, patients with age of 60 years or more were most susceptible to increased mortality even after adjusting for other comorbidities, as also shown in other studies . PLT transfusions were also an independent risk factor for mortality.…”

Section: Discussionsupporting

confidence: 81%

“…Renal failure (acute or chronic and with dialysis dependence) was also associated with worse outcome in TTP patients and higher adjusted odds of death. Varying degrees of renal dysfunction ranging from elevated creatinine to renal failure warranting dialysis have previously been reported as being associated with adverse outcomes in TTP patients but not death . In our data, renal failure was seen in the sickest TTP patients with more than three‐quarters of the subjects being in the highest grade of severity of illness by the APR‐DRG severity scoring and was identified as a significant independent predictor of death.…”

Section: Discussionsupporting

confidence: 54%

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Prognostic risk‐stratified score for predicting mortality in hospitalized patients with thrombotic thrombocytopenic purpura: nationally representative data from 2007 to 2012

Goel

King

Takemoto³

et al. 2016

Transfusion

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Background Despite proven efficacy and increased availability of therapeutic plasma exchange (TPE), mortality for patients with thrombotic thrombocytopenic purpura (TTP) remains high with a limited understanding of those at highest risk of death. Study Design and Methods This study utilized the Nationwide Inpatient Sample (2007–2012) to derive a prognostic score for mortality in hospitalized TTP patients. Odds ratios of death with various putative risk factors adjusted for age, gender and race were calculated (adjOR). Weighted average of adjOR estimates were incorporated in a risk stratified score. Results Among 8203 hospitalizations with TTP as primary admission diagnosis who underwent TPE, 613 deaths were identified (all-cause mortality 7.5%, median time-to-death 9 days with interquartile range 4–14 days). In multivariable logistic regression, arterial thrombosis (adjOR 6.7, 95%CI=1.1–40.9), intra-cranial hemorrhage (adjOR 6.1, 95%CI=1.6–23.2), age >=60 years (adjOR 3.5, 95%CI=2.1–5.6), renal failure (adjOR 2.6, 95%CI=1.5–4.5), ischemic stroke (adjOR 2.4, 95%CI=1.2–5.0), platelet transfusions (adjOR 2.2, 95%CI=1.2–4.1) and myocardial infarction (adjOR 2.3, 95%CI=1.2–4.6) were significant independent predictors of mortality in TTP patients who underwent TPE. A prognostic weighted mortality prediction scoring system incorporating arterial thrombosis, intracranial hemorrhage, age, renal failure, ischemic stroke, platelet transfusion and myocardial infarction showed very good discrimination and was predictive of 78.6% deaths. Conclusions Early and targeted therapy for high risk individuals should be used to guide management of TTP patients for improved survival outcomes.

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Section: Discussionsupporting

confidence: 81%

Section: Discussionsupporting

confidence: 54%

Prognostic risk‐stratified score for predicting mortality in hospitalized patients with thrombotic thrombocytopenic purpura: nationally representative data from 2007 to 2012

Goel

King

Takemoto³

et al. 2016

Transfusion

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“…CCS codes are diagnosis categories with more clinical meanings, which can sometimes be more useful for presenting descriptive statistics than individual ICD-10 codes for relatively specific conditions. They are now widely used in many study scenarios for identifying comorbidities and outcomes [33–35], predicting mortality and risk [36, 37], and estimating hospital utilization and costs [38]. …”

Section: Methodsmentioning

confidence: 99%

Comorbidity in Adult Patients Hospitalized with Type 2 Diabetes in Northeast China: An Analysis of Hospital Discharge Data from 2002 to 2013

Chen

Zhang

et al. 2016

BioMed Research International

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This study aims to evaluate the comorbidity burden and patterns among adult patients hospitalized with a diagnosis of type 2 diabetes mellitus (T2DM) in Northeast China using hospital discharge data derived from the electronic medical record database between 2002 and 2013. 12.8% of 4,400,892 inpatients aged ≥18 had a diagnosis of T2DM. Sex differences in prevalence varied among those aged <50, 50–59, and ≥60. Twenty-seven diseases were determined as major comorbidities of T2DM. Essential hypertension was the most common comorbidity of T2DM (absolute cooccurrence risk, 58.4%), while T2DM was also the most popular comorbidity of essential hypertension. Peripheral and visceral atherosclerosis showed the strongest association (relative cooccurrence risk, RCoR 4.206). For five leading comorbidities among patients aged ≥40, male patients had a stronger association with disorders of lipid metabolism than female patients (RCoR 2.779 versus 2.099), and female patients had a stronger association with chronic renal failure than male patients (RCoR 2.461 versus 2.155). Leading comorbidities, except chronic renal failure, had declining associations with T2DM with increased age. Collectively, hospital discharge data can be used to estimate disease prevalence and identify comorbidities. The findings provided comprehensive information on comorbidity patterns, helping policy makers and programs in public health domains to estimate and evaluate the epidemic of chronic diseases.

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“…To date the correlation between ADAMTS13 and smoking has not been examined except in extreme deficiencies of ADAMTS13, such as those observed in patients with acute acquired or congenital thrombotic thrombocytopenic purpura. 37 A genome-wide study has been conducted for plasma ADAMTS13 activity 14 but not for ADAMTS13 protein concentrations. Although we expected these 2 traits to be highly correlated and identified similar associations, our top signal was not detected in the GWAS for ADAMTS13 activity.…”

Section: Discussionmentioning

confidence: 99%

Genetic variants in ADAMTS13 as well as smoking are major determinants of plasma ADAMTS13 levels

Ma¹,

Jacobi

Emmer³

et al. 2017

Blood Advances

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Key Points• Three independent association signals at ADAMTS13 and smoking were identified as major predictors of plasma ADAMTS13 levels.• Evidence was presented that 2 nonsynonymous ADAMTS13 variants were driving the variation of plasma ADAMTS13 concentrations. P 5 1.2E-30) and rs3124762 (b, 3.5%; P 5 8.9E-9) close to ADAMTS13 and rs4075970 (b, 2.4%; P 5 6.8E-9) on 21q22.3. Linkage analysis also identified the region around ADAMTS13 (9q34.2) as the top signal (LOD 3.5), consistent with our SNP association analyses. Two nonsynonymous ADAMTS13 variants in the top 2 independent linkage disequilibrium blocks (Q448E and A732V) were identified and characterized in vitro. This study uncovered specific common genetic polymorphisms that are key genetic determinants of the variation in plasma ADAMTS13 levels in healthy individuals.

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Predictors of In-hospital Mortality and Acute Myocardial Infarction in Thrombotic Thrombocytopenic Purpura

Cited by 32 publications

References 25 publications

Prognostic risk‐stratified score for predicting mortality in hospitalized patients with thrombotic thrombocytopenic purpura: nationally representative data from 2007 to 2012

Prognostic risk‐stratified score for predicting mortality in hospitalized patients with thrombotic thrombocytopenic purpura: nationally representative data from 2007 to 2012

Comorbidity in Adult Patients Hospitalized with Type 2 Diabetes in Northeast China: An Analysis of Hospital Discharge Data from 2002 to 2013

Genetic variants in ADAMTS13 as well as smoking are major determinants of plasma ADAMTS13 levels

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