***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Background — The aim of this study was to derive and vali date a risk score for rejection  after orthotopic heart transplantation . Methods and Results — The United Network for Organ Sharing registry was used to identify patients undergoing orthotopic heart transplantation between 1998 and 2008 . A total of 14 265 eligible patients were r and omly divided into derivation ( 80 % ; n=11 412 ) and validation ( 20 % ; n=2853 ) cohorts . The primary outcome was drug-treated rejection within 1 year of orthotopic heart transplantation . Covariates found to be associated ( exploratory univariate P<0.2 ) with rejection were entered into a multivariable logistic regression model . Inclusion of each variable in the model was assessed by improvement in the McFadden pseudo-R2 , likelihood ratio test , and c index . A risk score was then generated through the use of relative magnitudes of the odds ratios from the derivation cohort , and its ability to predict rejection was tested independently in the validation cohort . A 13-point risk score incorporating 4 variables ( age , race , sex , HLA matching ) was created . The mean scores in the derivation and validation cohorts were 8.3±2.2 and 8.4±2.1 , respectively . Predicted 1-year rejection rates based on the derivation cohort ranged from 16.2 % ( score=0 ) to 50.7 % ( score=13 ; P<0.001 ) . In weighted regression analysis , there was a strong correlation between these predicted rates of rejection and actual , observed rejection rates in the validation cohort ( r2=0.96 , P<0.001 ) . Logistic regression analysis also demonstrated a significant association ( odds ratio , 1.13 ; P<0.001 ) . The c index of the composite score was equivalent in both the derivation and validation cohorts ( c=0.67 ) . Conclusions — This novel 13-point risk score is highly predictive of clinical ly significant rejection episodes within 1 year of orthotopic heart transplantation . It has potential utility in tailoring immunosuppressive regimens and in research stratification in orthotopic heart transplantation OBJECTIVES The aim of this study was to develop a risk index specific to patients on mechanical circulatory support that accurately predicts 1-year mortality after orthotopic heart transplantation using the United Network for Organ Sharing data base . BACKGROUND Few clinical tools are available to aid in the decision between continuing long-term device support and performing transplantation in patients bridging with mechanical circulatory support . METHODS Using a prospect ively collected , open cohort , 6,036 patients receiving mechanical circulatory support who underwent orthotopic heart transplantation between 2000 and 2013 were evaluated and r and omly separated into derivation ( 80 % ) and validation ( 20 % ) groups . Multivariate logistic regression models were constructed using variables that improved the explanatory power of the model , which was determined using multiple methods . Points for a simple additive risk index were apportioned on the basis of relative effect on odds of 1-year mortality . RESULTS A 75-point scoring system was created from 9 recipient and 4 donor variables . The average score in the validation cohort was 14.4 ± 7.7 , and scores ranged from 0 to 57 ; these values were similar to those in the derivation cohort . Each 1-point increase predicted an 8.3 % increase in the odds of 1-year mortality ( odds ratio : 1.08 ; 95 % confidence interval : 1.06 to 1.11 ) . Low ( 0 to 10 ) , intermediate ( 11 to 20 ) , and high ( > 20 ) risk score cohorts were created , with predicted average 1-year mortalities of 8.6 % , 12.8 % , and 31 % , respectively , in the validation cohort . CONCLUSIONS The investigators present a novel , internally cross-vali date d risk index that accurately predicts mortality in bridge-to-transplantation patients Background —Risk factors for early mortality  after heart transplant ( HT )  have not been used for quantitative risk prediction . We sought to develop and vali date a risk prediction model for posttransplant in-hospital mortality in HT recipients . Methods and Results —We derived the model in subjects aged ≥18 years who underwent primary HT in the United States from January 2007 to June 2009 ( n=4248 ) and vali date d it internally using a bootstrapping technique ( 200 r and om sample s , n=4248 ) . We then assessed the model 's performance in patients receiving an HT from July 2009 to October 2010 ( external validation cohort , n=2346 ) . Posttransplant in-hospital mortality was 4.7 % in the model derivation cohort . The best-fitting model based on recipient characteristics at transplant had 6 variables : age , diagnosis , type of mechanical support , ventilator support , estimated glomerular filtration rate , and total serum bilirubin . Model discrimination for survivors versus nonsurvivors was acceptable during derivation and internal validation ( C statistic , 0.722 and 0.731 , respectively ) as was model calibration during derivation ( Hosmer Lemeshow [ HL ] P=0.47 ) . Model performance was reasonable in the external validation cohort ( predicted mortality , 4.9 % ; actual mortality , 4.3 % ; R2=0.95 ; C statistic , 0.68 ; HL P=0.48 ) . Adding the donor-related variables of age and ischemic time to the model improved its performance in both the model derivation ( C statistic , 0.742 ; HL P=0.70 ) and the external validation ( C statistic , 0.695 ; HL P=0.42 ) cohorts . Conclusions —The proposed model allows risk stratification of HT c and i date s for early posttransplant mortality and may be useful in counseling patients with regard to their posttransplant prognosis . The model with additional donor-related variables may be useful during donor selection Organ availability and acceptability limit  pediatric HTx .  What characteristics define an unacceptable or high-risk pediatric donor remains unclear . The purpose of this study was to characterize a large cohort of pediatric donors and determine the donor risk factors , including cumulative risk , that affect recipient survival . Data from the PHTS , a prospect i ve multicenter study , were used to examine the impact of donor factors on the outcomes of patients listed < 18 yr of age who received a HTx between 1993 and 2009 . Donor data were available for 3149 of 3156 HTx ( 99.8 % ) . Donor cause of death , need for inotropes , or CPR did not affect survival outcomes ( p = 0.05 ) . Ischemic time also did not have an impact on overall recipient survival ; however , longer ischemic times negatively impacted one-yr post-transplant survival ( p < 0.0001 ) . There was no impact of cumulative risk factors on survival ( p = 0.8 ) . Although used in a minority of cases , hormonal therapy in the donor positively impacted survival ( p = 0.03 ) . In multivariate analysis , the only donor factor associated with decreased survival was smaller donor BSA , the other factors being related to the recipient characteristics . When analyzed by recipient age , there were no donor-related factors that affected survival for those who received a transplant at < 6 months of age . Longer ischemic time ( p < 0.0001 ) and greater age difference between the recipient and donor ( p = 0.0098 ) were donor-related factors impacting early-phase survival for recipients who received a graft at ≥10 yr of age . Factors perceived to define a marginal or high-risk pediatric heart donor including inotrope use , CPR and donor cause of death may have less impact on outcomes than previously thought . Longer ischemic times did impact one yr , but not overall survival , and this impact was much greater with older donors . Parameters for accepting a donor heart can potentially be exp and ed , especially in the infant age group , but strong consideration should always be given to the interaction between ischemic time and donor age OBJECTIVE While there are numerous reports in the literature of risk factors for graft failure after heart transplantation , simple models for risk stratification are lacking . This study describes a simple method for risk stratification in adult heart transplantation that can be applied when the size of a data set is insufficient for formal regression modelling . METHODS Multi-centre prospect i ve cohort study . Fourteen risk factors documented in the literature as increasing post transplant graft failure were used to formulate a model . Risk factors included in the model were recipient age > 50 years , pre-operative ventilatory support , pre-operative circulatory support , > 1 previous sternotomy , pulmonary vascular resistance > 2.5 wood units , male with body surface area > 2.5 m2 , retransplant , ischaemic time > 3.5 h , donor age > 45 years , donor inotropic support > 10 microg/kg per min dopamine , female donor , ratio donor/recipient body surface area < 0.7 , donor with diabetes and history of donor drug abuse . Four risk groups were defined depending on the number of risk factors present : Low , none ; moderate , 1 ; high , 2 or 3 ; very high , 4 or more . Graft survival to 30 days was chosen as the primary outcome . The model was tested on 373 adult transplants performed in the UK between April 1995 and December 1996 . RESULTS Twenty eight transplants were low risk , 82 moderate , 201 high and 62 very high . The 30-day survival ( 70 % CI ) for the risk groups was low , 97 % ( 93 - 100 ) , moderate 95 % ( 92 - 98 ) , high 87 % ( 84 - 89 ) and very high 80 % ( 75 - 83 ) ( P = 0.02 ) . CONCLUSIONS This preliminary model enables some stratification of heart transplant procedures according to donor and recipient risk profile . Further work will be directed at refining and validating the model BACKGROUND Prolonged hospital length of stay ( PLOS ) after heart transplantation  increases cost and morbidity . To better inform care , we developed a risk score to identify patients at risk for PLOS after heart transplantation . METHODS We queried the United Network for Organ Sharing Scientific Registry of Transplant Recipients data base for adult patients who underwent isolated heart transplantation from 2003 to 2012 . The population was r and omly divided into a derivation cohort ( 80 % ) and a validation cohort ( 20 % ) . The outcome of interest was PLOS , defined as a posttransplant hospital length of stay of more than 30 days . Associated univariables ( p < 0.20 ) in the derivation cohort were included in a multivariable model , and a risk index was derived from the adjusted odds ratios of significant covariates . RESULTS During the study period , 16,723 patients underwent heart transplantation with an average PLOS of 19 ± 21 days , and 2,020 orthotopic heart transplant recipients ( 12 % ) had PLOS . Baseline characteristics were similar between the derivation and validation cohorts . Twenty-four recipient and nine donor variables , cold ischemic time , and center volume were tested as univariables . Seventeen covariates significantly affected PLOS and comprised the prolonged hospitalization after heart transplant risk score , which was stratified into three risk groups . The risk model was subsequently vali date d , and predicted rates of PLOS correlated well with observed rates ( R = 0.79 ) . Rates of PLOS in the validation cohort were 8.3 % , 11 % , and 22 % for low , moderate , and high risk groups , respectively . CONCLUSIONS The risk of PLOS after heart transplantation can be determined at the time of transplant . The prolonged hospitalization after heart transplant score may lead to individualized postoperative management strategies to reduce duration of hospitalization for patients at high risk BACKGROUND  Primary graft failure ( PGF ) is the leading cause of early mortality after heart transplantation ( HT ) . Our aim is to propose a working definition of PGF and to develop a predictive risk score . METHODS PGF was defined by four criteria reflecting significant myocardial dysfunction , severe hemodynamic impairment , early onset after HT , and absence of secondary causes of graft dysfunction . We identified independent risk factors for PGF  in a derivation series of 621 HTs and constructed a predictive model . After proving its internal consistency we tested the model in a prospect i ve validation series . RESULTS The incidence and lethality of PGF in our series were 9 % and 80 % , respectively . We identified 6 multivariate risk factors for PGF ( Right atrial pressure ≥ 10 mm Hg , recipient Age ≥ 60 years , Diabetes mellitus , Inotrope dependence , donor Age ≥ 30 years , Length of ischemic time ≥ 240 minutes -- i.e . , RADIAL ) . Analysis of isolated right ventricular failure showed similar predictors . The RADIAL score was obtained by adding 1 point for each of these factors present in a given HT . PGF incidence increased significantly as the RADIAL score increased ( p < 0.001 for trend ) . Rates of actual and predicted PGF incidence for RADIAL subgroups showed a good correlation ( C-statistic = 0.74 ) . In a prospect i ve validation cohort , RADIAL score kept its predictive ability . CONCLUSIONS PGF as defined by these criteria showed a high impact on early post-HT mortality in our series 
    Output:
    
In general , the data support that patients who could be easily agreed to be " sicker recipients " are at more risk compared to those who are clearly " healthier , " albeit still " sick enough " to need transplantation .
Given this variability in the literature , we were unable to define how being a " high-risk " recipient interplays with accepting a " marginal donor . "
Existing risk scores are described , but none were felt to adequately predict outcomes from factors available at the time of offer acceptance .
We could not determine what makes a donor " marginal , " a recipient " high-risk , " or how these factors interplay within the specific recipient-donor pair to determine outcomes .