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Creation and Validation of a Novel Sex-Specific Mortality Risk Score in LVAD Recipients.

ABSTRACT: Background Prior studies have shown that women have worse 3-month survival after receiving a left ventricular assist device compared with men. Currently used prognostic scores, including the Heartmate II Risk Score, do not account for the increased residual risk in women. We used the IMACS (International Society for Heart and Lung Transplantation Mechanically Assisted Circulatory Support) registry to create and validate a sex-specific risk score for early mortality in left ventricular assist device recipients. Methods and Results Adult patients with a continuous-flow LVAD from the IMACS registry were randomly divided into a derivation cohort (DC; n=9113; 21% female) and a validation cohort (VC; n=6074; 21% female). The IMACS Risk Score was developed in the DC to predict 3-month mortality, from preoperative candidate predictors selected using the Akaike information criterion, or significant sex × variable interaction. In the DC, age, cardiogenic shock at implantation, body mass index, blood urea nitrogen, bilirubin, hemoglobin, albumin, platelet count, left ventricular end-diastolic diameter, tricuspid regurgitation, dialysis, and major infection before implantation were retained as significant predictors of 3-month mortality. There was significant ischemic heart failure × sex and platelet count × sex interaction. For each quartile increase in IMACS risk score, men (odds ratio [OR], 1.86; 95% CI, 1.74-2.00; P<0.0001), and women (OR, 1.93; 95% CI, 1.47-2.59; P<0.0001) had higher odds of 3-month mortality. The IMACS risk score represented a significant improvement over Heartmate II Risk Score (IMACS risk score area under the receiver operating characteristic curve: men: DC, 0.71; 95% CI, 0.69-0.73; VC, 0.69; 95% CI, 0.66-0.72; women: DC, 0.73; 95% CI, 0.70-0.77; VC, 0.71 [95% CI, 0.66-0.76; P<0.01 for improvement in receiver operating characteristic) and provided excellent risk calibration in both sexes. Removal of sex-specific interaction terms resulted in significant loss of model fit. Conclusions A sex-specific risk score provides excellent risk prediction in LVAD recipients.

SUBMITTER: Nayak A

PROVIDER: S-EPMC8174331 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: The coronavirus disease 2019 (COVID-19) pandemic has found the whole world unprepared for its correct management. Italy was the first European country to experience the spread of the SARS-CoV-2 virus at the end of February 2020. As a result of hospital overcrowding, the quality of care delivered was not always optimal. A substantial number of patients admitted to non-ICU units could have been treated at home. It would have been extremely useful to have a score that, based on personal and clinical characteristics and simple blood tests, could have predicted with sufficient reliability the probability that a patient had or did not have a disease that could have led to their death. This study aims to develop a scoring system to identify which patients with COVID-19 are at high mortality risk upon hospital admission, to expedite and enhance clinical decision making. Methods: A retrospective analysis was performed to develop a multivariable prognostic prediction model. Results: Derivation and external validation cohorts were obtained from two Italian University Hospital databases, including 388 (10.31% deceased) and 1357 (7.68% deceased) patients with confirmed COVID-19, respectively. A multivariable logistic model was used to select seven variables associated with in-hospital death (age, baseline oxygen saturation, hemoglobin value, white blood cell count, percentage of neutrophils, platelet count, and creatinine value). Calibration and discrimination were satisfactory with a cumulative AUC for prediction mortality of 0.924 (95% CI: 0.893-0.944) in derivation cohorts and 0.808 (95% CI: 0.886-0.828) in external validation cohorts. The risk score obtained was compared with the ISARIC 4C Mortality Score, and with all the other most important scores considered so far, to evaluate the risk of death of patients with COVID-19. It performed better than all the above scores to evaluate the predictability of dying. Its sensitivity, specificity, and AUC were higher than the other COVID-19 scoring systems when the latter were calculated for the 388 patients in our derivation cohort. Conclusions: In conclusion, the CZ-COVID-19 Score may help all physicians by identifying those COVID-19 patients who require more attention to provide better therapeutic regimens or, on the contrary, by identifying those patients for whom hospitalization is not necessary and who could therefore be sent home without overcrowding healthcare facilities. We developed and validated a new risk score based on seven variables for upon-hospital admission of COVID-19 patients. It is very simple to calculate and performs better than all the other similar scores to evaluate the predictability of dying.

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Creation and Validation of a Novel Sex-Specific Mortality Risk Score in LVAD Recipients.

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