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Immune checkpoint inhibitors (ICI) are now routinely used in multiple cancers but may induce autoimmune-like side effects known as immune-related adverse events (irAE). Although classical autoimmune diseases have well-known risk factors, including age, gender, and seasonality, the clinical factors that lead to irAEs are not well-defined. To explore these questions, we assessed 455 patients with advanced melanoma treated with ICI at our center and a large pharmacovigilance database (VigiBase). We found that younger age was associated with a similar rate of any irAEs but more frequent severe irAEs and more hospitalizations (OR, 0.97 per year). Paradoxically, however, older patients had more deaths and increased length of stay (LOS) when hospitalized. This was partially due to a distinct toxicity profile: Colitis and hepatitis were more common in younger patients, whereas myocarditis and pneumonitis had an older age distribution both in our center and in VigiBase. This pattern was particularly apparent with combination checkpoint blockade with ipilimumab and nivolumab. We did not find a link between gender or seasonality on development of irAEs in univariate or multivariate analyses, although winter hospitalizations were associated with marginally increased LOS. This study identifies age-specific associations of irAEs.
©2020 American Association for Cancer Research.
Importance - Whether low levels of low-density lipoprotein cholesterol (LDL-C) are associated with increased risk of sepsis and poorer outcomes is unknown.
Objective - To examine the association between LDL-C levels and risk of sepsis among patients admitted to the hospital with infection.
Design, Setting, and Participants - Cohort study in which deidentified electronic health records were used to define a cohort of patients admitted to Vanderbilt University Medical Center, Nashville, Tennessee, with infection. Patients were white adults, had a code indicating infection from the International Classification of Diseases, Ninth Revision, Clinical Modification, and received an antibiotic within 1 day of hospital admission (N = 61 502). Data were collected from January 1, 1993, through December 31, 2017, and analyzed from January 24 through October 31, 2018.
Interventions - Clinically measured LDL-C levels (excluding measurements <1 year before hospital admission and those associated with acute illness) and a genetic risk score (GRS).
Main Outcomes and Measures - The primary outcome was sepsis; secondary outcomes included admission to an intensive care unit (ICU) and in-hospital death.
Results - Among the 3961 patients with clinically measured LDL-C levels (57.8% women; mean [SD] age, 64.1 [15.9] years) and the 7804 with a GRS for LDL-C (54.0% men; mean [SD] age, 59.8 [15.2] years), lower measured LDL-C levels were significantly associated with increased risk of sepsis (odds ratio [OR], 0.86; 95% CI, 0.79-0.94; P = .001) and ICU admission (OR, 0.85; 95% CI, 0.76-0.96; P = .008), but not in-hospital mortality (OR, 0.80; 95% CI, 0.63-1.00; P = .06); however, none of these associations were statistically significant after adjustment for age, sex, and comorbidity variables (OR for risk of sepsis, 0.96 [95% CI, 0.88-1.06]; OR for ICU admission, 0.94 [95% CI, 0.83-1.06]; OR for in-hospital death, 0.97 [95% CI, 0.76-1.22]; P > .05 for all). The LDL-C GRS correlated with measured LDL-C levels (r = 0.24; P < 2.2 × 10-16) but was not significantly associated with any of the outcomes.
Conclusions and Relevance - Results of this study suggest that lower measured LDL-C levels were significantly associated with increased risk of sepsis and admission to ICU in patients admitted to the hospital with infection; however, this association was due to comorbidities because both clinical models adjusted for confounders, and the genetic model showed no increased risk. Levels of LDL-C do not appear to directly alter the risk of sepsis or poor outcomes in patients hospitalized with infection.
OBJECTIVES - We aimed to validate an algorithm using both primary discharge diagnosis (International Classification of Diseases Ninth Revision (ICD-9)) and diagnosis-related group (DRG) codes to identify hospitalisations due to decompensated heart failure (HF) in a population of patients with diabetes within the Veterans Health Administration (VHA) system.
DESIGN - Validation study.
SETTING - Veterans Health Administration-Tennessee Valley Healthcare System PARTICIPANTS: We identified and reviewed a stratified, random sample of hospitalisations between 2001 and 2012 within a single VHA healthcare system of adults who received regular VHA care and were initiated on an antidiabetic medication between 2001 and 2008. We sampled 500 hospitalisations; 400 hospitalisations that fulfilled algorithm criteria, 100 that did not. Of these, 497 had adequate information for inclusion. The mean patient age was 66.1 years (SD 11.4). Majority of patients were male (98.8%); 75% were white and 20% were black.
PRIMARY AND SECONDARY OUTCOME MEASURES - To determine if a hospitalisation was due to HF, we performed chart abstraction using Framingham criteria as the referent standard. We calculated the positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity for the overall algorithm and each component (primary diagnosis code (ICD-9), DRG code or both).
RESULTS - The algorithm had a PPV of 89.7% (95% CI 86.8 to 92.7), NPV of 93.9% (89.1 to 98.6), sensitivity of 45.1% (25.1 to 65.1) and specificity of 99.4% (99.2 to 99.6). The PPV was highest for hospitalisations that fulfilled both the ICD-9 and DRG algorithm criteria (92.1% (89.1 to 95.1)) and lowest for hospitalisations that fulfilled only DRG algorithm criteria (62.5% (28.4 to 96.6)).
CONCLUSIONS - Our algorithm, which included primary discharge diagnosis and DRG codes, demonstrated excellent PPV for identification of hospitalisations due to decompensated HF among patients with diabetes in the VHA system.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Background - Trauma-related hospitalizations drive a high percentage of health care expenditure and inpatient resource consumption, which is directly related to length of stay (LOS). Robust and reliable interactions among health care employees can reduce LOS. However, there is little known about whether certain patterns of interactions exist and how they relate to LOS and its variability. The objective of this study is to learn interaction patterns and quantify the relationship to LOS within a mature trauma system and long-standing electronic medical record (EMR).
Methods - We adapted a spectral co-clustering methodology to infer the interaction patterns of health care employees based on the EMR of 5588 hospitalized adult trauma survivors. The relationship between interaction patterns and LOS was assessed via a negative binomial regression model. We further assessed the influence of potential confounders by age, number of health care encounters to date, number of access action types care providers committed to patient EMRs, month of admission, phenome-wide association study codes, procedure codes, and insurance status.
Results - Three types of interaction patterns were discovered. The first pattern exhibited the most collaboration between employees and was associated with the shortest LOS. Compared to this pattern, LOS for the second and third patterns was 0.61 days (P = 0.014) and 0.43 days (P = 0.037) longer, respectively. Although the 3 interaction patterns dealt with different numbers of patients in each admission month, our results suggest that care was provided for similar patients.
Discussion - The results of this study indicate there is an association between LOS and the extent to which health care employees interact in the care of an injured patient. The findings further suggest that there is merit in ascertaining the content of these interactions and the factors that induce these differences in interaction patterns within a trauma system.
INTRODUCTION - Hospital readmissions within 30 days are a healthcare quality problem associated with increased costs and poor health outcomes. Identifying interventions to improve patients' successful transition from inpatient to outpatient care is a continued challenge.
METHODS AND ANALYSIS - This is a single-centre pragmatic randomised and controlled clinical trial examining the effectiveness of a discharge follow-up phone call to reduce 30-day inpatient readmissions. Our primary endpoint is inpatient readmission within 30 days of hospital discharge censored for death analysed with an intention-to-treat approach. Secondary endpoints included observation status readmission within 30 days, time to readmission, all-cause emergency department revisits within 30 days, patient satisfaction (measured as mean Hospital Consumer Assessment of Healthcare Providers and Systems scores) and 30-day mortality. Exploratory endpoints include the need for assistance with discharge plan implementation among those randomised to the intervention arm and reached by the study nurse, and the number of call attempts to achieve successful intervention delivery. Consistent with the Learning Healthcare System model for clinical research, timeliness is a critical quality for studies to most effectively inform hospital clinical practice. We are challenged to apply pragmatic design elements in order to maintain a high-quality practicable study providing timely results. This type of prospective pragmatic trial empowers the advancement of hospital-wide evidence-based practice directly affecting patients.
ETHICS AND DISSEMINATION - Study results will inform the structure, objective and function of future iterations of the hospital's discharge follow-up phone call programme and be submitted for publication in the literature.
TRIAL REGISTRATION NUMBER - NCT03050918; Pre-results.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
BACKGROUND - Recent studies suggest older patients hospitalized for community-acquired pneumonia are at risk for new-onset cognitive impairment. The characteristics of long-term cognitive impairment after pneumonia, however, have not been elucidated.
OBJECTIVE - To characterize long-term cognitive impairment among adults of all ages hospitalized for community-acquired pneumonia.
DESIGN - Prospective cohort study.
PARTICIPANTS - Adults without severe preexisting cognitive impairment who were hospitalized with community-acquired pneumonia.
MAIN MEASURES - At enrollment, we estimated baseline cognitive function with the Short Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). At 2- and 12-month follow-up, we assessed cognition using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and tests of executive function, diagnosing cognitive impairment when results were ≥ 1.5 standard deviations below published age-adjusted means for the general population. We also identified subtypes of mild cognitive impairment using standard definitions.
KEY RESULTS - We assessed 58 (73%) of 80 patients who survived to 2-month follow-up and 57 (77%) of 74 who survived to 12-month follow-up. The median [range] age of survivors tested was 57 [19-97] years. Only 8 (12%) had evidence of mild cognitive impairment at baseline according to the Short IQCODE, but 21 (38%) at 2 months and 17 (30%) at 12 months had mild cognitive impairment per the RBANS. Moderate-to-severe cognitive impairment was common among adults ≥ 65 years [4/13 (31%) and 5/13 (38%) at 2 and 12 months, respectively] but also affected many of those < 65 years [10/43 (23%) and 8/43 (19%) at 2 and 12 months, respectively]. Deficits were most often noted in visuospatial function, attention, and memory.
CONCLUSIONS - A year after hospitalization for community-acquired pneumonia, moderate-to-severe impairment in multiple cognitive domains affected one-third of patients ≥ 65 years old and 20% of younger patients, and another third of survivors had mild cognitive impairment.
Obstetric care refers to the care provided to patients during ante-, intra-, and postpartum periods. Predicting length of stay (LOS) for these patients during their hospitalizations can assist healthcare organizations in allocating hospital resources more effectively and efficiently, ultimately improving maternal care quality and reducing costs to patients. In this paper, we investigate the extent to which LOS can be forecast from a patient's medical history. We introduce a machine learning framework to incorporate a patient's prior conditions (e.g., diagnostic codes) as features in a predictive model for LOS. We evaluate the framework with three years of historical billing data from the electronic medical records of 9188 obstetric patients in a large academic medical center. The results indicate that our framework achieved an average accuracy of 49.3%, which is higher than the baseline accuracy 37.7% (that relies solely on a patient's age). The most predictive features were found to have statistically significant discriminative ability. These features included billing codes for normal delivery (indicative of shorter stay) and antepartum hypertension (indicative of longer stay).
Background - Recognition that coinfections are common in children with community-acquired pneumonia (CAP) is increasing, but gaps remain in our understanding of their frequency and importance.
Methods - We analyzed data from 2219 children hospitalized with CAP and compared demographic and clinical characteristics and outcomes between groups with viruses alone, bacteria alone, or coinfections. We also assessed the frequency of selected pairings of codetected pathogens and their clinical characteristics.
Results - A total of 576 children (26%) had a coinfection. Children with only virus detected were younger, more likely to be black, and more likely to have comorbidities such as asthma, compared with children infected with typical bacteria alone. Children with virus-bacterium coinfections had a higher frequency of leukocytosis, consolidation on chest radiography, parapneumonic effusions, intensive care unit admission, and need for mechanical ventilation and an increased length of stay, compared with children infected with viruses alone. Virus-virus coinfections were generally comparable to single-virus infections, with the exception of the need for oxygen supplementation, which was higher during the first 24 hours of hospitalization in some virus-virus pairings.
Conclusions - Coinfections occurred in 26% of children hospitalized for CAP. Children with typical bacterial infections, alone or complicated by a viral infection, have worse outcomes than children infected with a virus alone.
BACKGROUND - Acute kidney injury (AKI) is common and associated with poor outcomes. Heart failure is a leading cause of cardiovascular disease among patients with chronic kidney disease. The relationship between AKI and heart failure remains unknown and may identify a novel mechanistic link between kidney and cardiovascular disease.
STUDY DESIGN - Observational study.
SETTING & PARTICIPANTS - We studied a national cohort of 300,868 hospitalized US veterans (2004-2011) without a history of heart failure.
PREDICTOR - AKI was the predictor and was defined as a 0.3-mg/dL or 50% increase in serum creatinine concentration from baseline to the peak hospital value. Patients with and without AKI were matched (1:1) on 28 in- and outpatient covariates using optimal Mahalanobis distance matching.
OUTCOMES - Incident heart failure was defined as 1 or more hospitalization or 2 or more outpatient visits with a diagnosis of heart failure within 2 years through 2013.
RESULTS - There were 150,434 matched pairs in the study. Patients with and without AKI during the index hospitalization were well matched, with a median preadmission estimated glomerular filtration rate of 69mL/min/1.73m. The overall incidence rate of heart failure was 27.8 (95% CI, 19.3-39.9) per 1,000 person-years. The incidence rate was higher in those with compared with those without AKI: 30.8 (95% CI, 21.8-43.5) and 24.9 (95% CI, 16.9-36.5) per 1,000 person-years, respectively. In multivariable models, AKI was associated with 23% increased risk for incident heart failure (HR, 1.23; 95% CI, 1.19-1.27).
LIMITATIONS - Study population was primarily men, reflecting patients seen at Veterans Affairs hospitals.
CONCLUSIONS - AKI is an independent risk factor for incident heart failure. Future studies to identify underlying mechanisms and modifiable risk factors are needed.
Copyright © 2017 National Kidney Foundation, Inc. All rights reserved.
Importance - β-Lactam monotherapy and β-lactam plus macrolide combination therapy are both common empirical treatment strategies for children hospitalized with pneumonia, but few studies have evaluated the effectiveness of these 2 treatment approaches.
Objective - To compare the effectiveness of β-lactam monotherapy vs β-lactam plus macrolide combination therapy among a cohort of children hospitalized with pneumonia.
Design, Setting, and Participants - We analyzed data from the Etiology of Pneumonia in the Community Study, a multicenter, prospective, population-based study of community-acquired pneumonia hospitalizations conducted from January 1, 2010, to June 30, 2012, in 3 children's hospitals in Nashville, Tennessee; Memphis, Tennessee; and Salt Lake City, Utah. The study included all children (up to 18 years of age) who were hospitalized with radiographically confirmed pneumonia and who received β-lactam monotherapy or β-lactam plus macrolide combination therapy. Data analysis was completed in April 2017.
Main Outcomes and Measures - We defined the referent as β-lactam monotherapy, including exclusive use of an oral or parenteral second- or third-generation cephalosporin, penicillin, ampicillin, ampicillin-sulbactam, amoxicillin, or amoxicillin-clavulanate. Use of a β-lactam plus an oral or parenteral macrolide (azithromycin or clarithromycin) served as the comparison group. We modeled the association between these groups and patients' length of stay using multivariable Cox proportional hazards regression. Covariates included demographic, clinical, and radiographic variables. We further evaluated length of stay in a cohort matched by propensity to receive combination therapy. Logistic regression was used to evaluate secondary outcomes in the unmatched cohort, including intensive care admission, rehospitalizations, and self-reported recovery at follow-up.
Results - Our study included 1418 children (693 girls and 725 boys) with a median age of 27 months (interquartile range, 12-69 months). This cohort was 60.1% of the 2358 children enrolled in the Etiology of Pneumonia in the Community Study with radiographically confirmed pneumonia in the study period; 1019 (71.9%) received β-lactam monotherapy and 399 (28.1%) received β-lactam plus macrolide combination therapy. In the unmatched cohort, there was no statistically significant difference in length of hospital stay between children receiving β-lactam monotherapy and combination therapy (median, 55 vs 59 hours; adjusted hazard ratio, 0.87; 95% CI, 0.74-1.01). The propensity-matched cohort (n = 560, 39.5%) showed similar results. There were also no significant differences between treatment groups for the secondary outcomes.
Conclusions and Relevance - Empirical macrolide combination therapy conferred no benefit over β-lactam monotherapy for children hospitalized with community-acquired pneumonia. The results of this study elicit questions about the routine empirical use of macrolide combination therapy in this population.