Comorbidity Index as a Predictor of Mortality in Pediatric Patients With Solid Tumors

Torres‐Espíndola, Luz María; Demetrio-Ríos, Joel; Carmona-Aparicio, Liliana; Galván-Díaz, César; Pérez-García, Martin; Chávez‐Pacheco, Juan Luis; Granados-Montiel, Julio; Arellano, Israel Torres-Ramirez de; Aquino‐Gálvez, Arnoldo; Castillejos-López, Manuel

doi:10.3389/fped.2019.00048

Cited by 18 publications

(13 citation statements)

References 30 publications

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“…For patients recruited from adult centers, the iHCP determined if patients had high unmet health or social needs as defined by Schaink et al [ 36 ]. Although a Pediatric Comorbidity Index is being developed, there is currently no validated measure of comorbidity or complexity for pediatric patients [ 37 ].…”

Section: Methodsmentioning

confidence: 99%

A Clinical Communication Tool (Loop) for Team-Based Care in Pediatric and Adult Care Settings: Hybrid Mixed Methods Implementation Study

Husain¹,

Cohen²,

Dubrowski³

et al. 2021

J Med Internet Res

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Background Communication within the circle of care is central to coordinated, safe, and effective care; yet patients, caregivers, and health care providers often experience poor communication and fragmented care. Through a sequential program of research, the Loop Research Collaborative developed a web-based, asynchronous clinical communication system for team-based care. Loop assembles the circle of care centered on a patient, in private networking spaces called Patient Loops. The patient, their caregiver, or both are part of the Patient Loop. The communication is threaded, it can be filtered and sorted in multiple ways, it is securely stored, and can be exported for upload to a medical record. Objective The objective of this study was to implement and evaluate Loop. The study reporting adheres to the Standards for Reporting Implementation Research. Methods The study was a hybrid type II mixed methods design to simultaneously evaluate Loop’s clinical and implementation effectiveness, and implementation barriers and facilitators in 6 health care sites. Data included monthly user check-in interviews and bimonthly surveys to capture patient or caregiver experience of continuity of care, in-depth interviews to explore barriers and facilitators based on the Consolidated Framework for Implementation Research (CFIR), and Loop usage extracted directly from the Loop system. Results We recruited 25 initiating health care providers across 6 sites who then identified patients or caregivers for recruitment. Of 147 patient or caregiver participants who were assessed and met screening criteria, 57 consented and 52 were enrolled on Loop, creating 52 Patient Loops. Across all Patient Loops, 96 additional health care providers consented to join the Loop teams. Loop usage was followed for up to 8 months. The median number of messages exchanged per team was 1 (range 0-28). The monthly check-in and CFIR interviews showed that although participants acknowledged that Loop could potentially fill a gap, existing modes of communication, workflows, incentives, and the lack of integration with the hospital electronic medical records and patient portals were barriers to its adoption. While participants acknowledged Loop’s potential value for engaging the patient and caregiver, and for improving communication within the patient’s circle of care, Loop’s relative advantage was not realized during the study and there was insufficient tension for change. Missing data limited the analysis of continuity of care. Conclusions Fundamental structural and implementation challenges persist toward realizing Loop’s potential as a shared system of asynchronous communication. Barriers include health information system integration; system, organizational, and individual tension for change; and a fee structure for health care provider compensation for asynchronous communication.

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Section: Methodsmentioning

confidence: 99%

A Clinical Communication Tool (Loop) for Team-Based Care in Pediatric and Adult Care Settings: Hybrid Mixed Methods Implementation Study

Husain¹,

Cohen²,

Dubrowski³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…The ECI was applied for measuring patient comorbidities which, like Charlson Comorbidity Index (CCI) [ 47 ] is validated for adult populations. Although studies of T1D generally involve a higher prevalence of pediatric patients, and other studies [ 48 ] have shown that pediatric-specific comorbidity indices perform most optimally among these groups, this study population largely comprised adults. Lastly, because of the pandemic, many patients avoided hospital visits [ 49 , 50 ].…”

Section: Discussionmentioning

confidence: 99%

The associations between COVID-19 diagnosis, type 1 diabetes, and the risk of diabetic ketoacidosis: A nationwide cohort from the US using the Cerner Real-World Data

et al. 2022

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Objective To assess the risk of new-onset type 1 diabetes mellitus (T1D) diagnosis following COVID-19 diagnosis and the impact of COVID-19 diagnosis on the risk of diabetic ketoacidosis (DKA) in patients with prior T1D diagnosis. Research design and methods Retrospective data consisting of 27,292,879 patients from the Cerner Real-World Data were used. Odds ratios, overall and stratified by demographic predictors, were calculated to assess associations between COVID-19 and T1D. Odds ratios from multivariable logistic regression models, adjusted for demographic and clinical predictors, were calculated to assess adjusted associations between COVID-19 and DKA. Multiple imputation with multivariate imputation by chained equations (MICE) was used to account for missing data. Results The odds of developing new-onset T1D significantly increased in patients with COVID-19 diagnosis (OR: 1.42, 95% CI: 1.38, 1.46) compared to those without COVID-19. Risk varied by demographic groups, with the largest risk among pediatric patients ages 0–1 years (OR: 6.84, 95% CI: 2.75, 17.02) American Indian/Alaskan Natives (OR: 2.30, 95% CI: 1.86, 2.82), Asian or Pacific Islanders (OR: 2.01, 95% CI: 1.61, 2.53), older adult patients ages 51–65 years (OR: 1.77, 95% CI: 1.66, 1.88), those living in the Northeast (OR: 1.71, 95% CI: 1.61, 1.81), those living in the West (OR: 1.65, 95% CI: 1.56, 1.74), and Black patients (OR: 1.59, 95% CI: 1.47, 1.71). Among patients with diagnosed T1D at baseline (n = 55,359), 26.7% (n = 14,759) were diagnosed with COVID-19 over the study period. The odds of developing DKA for those with COVID-19 were significantly higher (OR 2.26, 95% CI: 2.04, 2.50) than those without COVID-19, and the largest risk was among patients with higher Elixhauser Comorbidity Index. Conclusions COVID-19 diagnosis is associated with significantly increased risk of new-onset T1D, and American Indian/Alaskan Native, Asian/Pacific Islander, and Black populations are disproportionately at risk. In patients with pre-existing T1D, the risk of developing DKA is significantly increased following COVID-19 diagnosis.

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“…The study used the most recent available recordings of SEIFA, IRSEO, ARIA, age and jurisdiction of residence for each individual. As comorbidity indices such as the Charlson Comorbidity Index [ 24 ] are not suitable for childhood conditions [ 25 ], individual comorbidities based on ICD-10-AM coded hospital admissions were investigated. The comorbidities included chronic obstructive pulmonary diseases, chronic kidney disease, other cardiovascular diseases, coronary heart disease, anticoagulant treatment, diabetes and mental health conditions.…”

Section: Methodsmentioning

confidence: 99%

Case Ascertainment on Australian Registers for Acute Rheumatic Fever and Rheumatic Heart Disease

Agenson

Katzenellenbogen

Seth

et al. 2020

IJERPH

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In Australia, disease registers for acute rheumatic fever (ARF) and rheumatic heart disease (RHD) were previously established to facilitate disease surveillance and control, yet little is known about the extent of case-ascertainment. We compared ARF/RHD case ascertainment based on Australian ARF/RHD register records with administrative hospital data from the Northern Territory (NT), South Australia (SA), Queensland (QLD) and Western Australia (WA) for cases 3–59 years of age. Agreement across data sources was compared for persons with an ARF episode or first-ever RHD diagnosis. ARF/RHD registers from the different jurisdictions were missing 26% of Indigenous hospitalised ARF/RHD cases overall (ranging 17–40% by jurisdiction) and 10% of non-Indigenous hospitalised ARF/RHD cases (3–28%). The proportion of hospitalised RHD cases (36%) was half the proportion of hospitalised ARF cases (70%) notified to the ARF/RHD registers. The registers were found to capture few RHD cases in metropolitan areas (SA Metro: 13%, QLD Metro: 35%, WA Metro: 14%). Indigenous status, older age, comorbidities, drug/alcohol abuse and disease severity were predictors of cases appearing in the hospital data only (p < 0.05); sex was not a determinant. This analysis confirms that there are biases associated with the epidemiological analysis of single sources of case ascertainment for ARF/RHD using Australian data.

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Comorbidity Index as a Predictor of Mortality in Pediatric Patients With Solid Tumors

Cited by 18 publications

References 30 publications

A Clinical Communication Tool (Loop) for Team-Based Care in Pediatric and Adult Care Settings: Hybrid Mixed Methods Implementation Study

A Clinical Communication Tool (Loop) for Team-Based Care in Pediatric and Adult Care Settings: Hybrid Mixed Methods Implementation Study

The associations between COVID-19 diagnosis, type 1 diabetes, and the risk of diabetic ketoacidosis: A nationwide cohort from the US using the Cerner Real-World Data

Case Ascertainment on Australian Registers for Acute Rheumatic Fever and Rheumatic Heart Disease

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