The changing landscape of geriatric care in acute myeloid leukemia: a 5-year analysis of inpatient mortality predictors, trends in mortality, and chemotherapy use.

Background: This study examined inpatient mortality factors in geriatric patients with acute myeloid leukemia (AML) using data from the 2016 to 2020 National Inpatient Sample. Methods: Identifying patients through ICD-10 codes, a total of 127,985 individuals with AML were classified into age categories as follows: 50.58% were 65 to 74 years, 37.74% were 75 to 84 years, and 11.68% were 85 years or older. Statistical analysis, conducted with STATA, involved Fisher's exact and Student's t tests for variable comparisons. Mortality predictors were identified through multivariate logistic regression. Results: Various hospital and patient-level factors, including an increase in age, race, a higher Charlson Comorbidity Index score, insurance status, and specific comorbidities such as atrial fibrillation and protein-calorie malnutrition, independently elevated the risk of inpatient mortality. Asthma, hyperlipidemia, and inpatient chemotherapy were linked to lower mortality. Although there was no statistically significant mortality rate change from 2016 to 2020, a decline in chemotherapy use in the eldest age group was noted. Conclusion: This study highlights the complexity of factors influencing inpatient mortality among geriatric patients with AML, emphasizing the need for personalized clinical approaches in this vulnerable population.

Double Trouble: COVID-19 Infection Exacerbates Sickle Cell Crisis Outcomes in Hospitalized Patients-Insights from National Inpatient Sample 2020.

Background: This study investigated the impact of COVID-19 on patients with sickle cell crisis (SCC) using National Inpatient Sample (NIS) data for the year 2020. Methods: A retrospective cohort analysis was conducted utilizing International Classification of Diseases (ICD-10) codes to identify adults who were admitted with a principal diagnosis of sickle cell crisis. The primary outcomes examined were inpatient mortality, while the secondary outcomes assessed included morbidity, hospital length of stay, and resource utilization. Analyses were conducted with STATA. Multivariate logistic and linear regression analyses were used to adjust for confounding variables. Results: Of 66,415 adult patients with a primary SCC diagnosis, 875 were identified with a secondary diagnosis of COVID-19 infection. Unadjusted mortality rate was higher for SCC patients with COVID-19 (2.28%) compared to those without (0.33%), with an adjusted odds ratio (aOR) of 8.49 (p = 0.001). They also showed increased odds of developing acute respiratory failure (aOR = 2.37, p = 0.003) and acute kidney injury requiring dialysis (aOR = 8.66, p = 0.034). Additionally, these patients had longer hospital stays by an adjusted mean of 3.30 days (p < 0.001) and incurred higher hospitalization charges by an adjusted mean of USD 35,578 (p = 0.005). Conclusions: The SCC patients with COVID-19 presented higher mortality rates, increased morbidity indicators, longer hospital stays, and substantial economic burdens.

Independent predictors of mortality and 5-year trends in mortality and resource utilization in hospitalized patients with diffuse large B cell lymphoma.

Background: This retrospective study analyzed factors influencing all-cause inpatient mortality in 80,930 adult patients (2016-2020) with diffuse large B cell lymphoma using the National Inpatient Sample database. Methods: Utilizing ICD-10 codes, patients were identified, and statistical analysis was conducted using STATA. Fisher's exact and Student's t tests compared proportions and variables, multivariate logistic regression examined mortality predictors, and a 5-year longitudinal analysis identified mortality and resource utilization trends. Results: The inpatient mortality rate was found to be 6.56% with a mean age of 67.99 years. Several hospital- and patient-level factors including specific comorbidities such as congestive heart failure, atrial fibrillation, acute kidney injury, chronic obstructive pulmonary disease, liver failure, pancytopenia, tumor lysis syndrome, and severe protein-calorie malnutrition were independently associated with inpatient mortality. Hospitalization costs showed an increasing trend, impacting the overall population and survivors. Conclusion: These insights may refine risk assessment, treatment selection, and interventions.

Network Tomography for Understanding Phenotypic Presentations in Aortic Stenosis.

OBJECTIVES: This study sought to build a patient-patient similarity network using multiple features of left ventricular (LV) structure and function in patients with aortic stenosis (AS). The study further validated the observations in an experimental murine model of AS. BACKGROUND: The LV response in AS is variable and results in heterogeneous phenotypic presentations. METHODS: The patient similarity network was developed using topological data analysis (TDA) from cross-sectional echocardiographic data collected from 246 patients with AS. Multivariate features of AS were represented on the map, and the network topology was compared with that of a murine AS model by imaging 155 animals at 3, 6, 9, or 12 months of age. RESULTS: The topological map formed a loop in which patients with mild and severe AS were aggregated on the right and left sides, respectively (p < 0.001). These 2 regions were linked through moderate AS; with upper arm of the loop showing patients with predominantly reduced ejection fractions (EFs), and the lower arm showing patients with preserved EFs (p < 0.001). The region of severe AS showed >3 times the increased risk of balloon valvuloplasty, and transcatheter or surgical aortic valve replacement (hazard ratio: 3.88; p < 0.001) compared with the remaining patients in the map. Following aortic valve replacement, patients recovered and moved toward the zone of mild and moderate AS. Topological data analysis in mice showed a similar distribution, with 1 side of the loop corresponding to higher peak aortic velocities than the opposite side (p < 0.0001). The validity of the cross-sectional data that revealed a path of AS progression was confirmed by comparing the locations occupied by 2 groups of mice that were serially imaged. LV systolic and diastolic dysfunction were frequently identified even during moderate AS in both humans and mice. CONCLUSIONS: Multifeature assessments of patient similarity by machine-learning processes may allow precise phenotypic recognition of the pattern of LV responses during the progression of AS.