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The Relative Ability of Comorbidity Ascertainment Methodologies to Predict In-Hospital Mortality Among Hospitalized Community-acquired Pneumonia Patients.

ABSTRACT: BACKGROUND:Despite widespread use of comorbidities for population health descriptions and risk adjustment, the ideal method for ascertaining comorbidities is not known. We sought to compare the relative value of several methodologies by which comorbidities may be ascertained. METHODS:This is an observational study of 1596 patients admitted to the University of Chicago for community-acquired pneumonia from 1998 to 2012. We collected data via chart abstraction, administrative data, and patient report, then performed logistic regression analyses, specifying comorbidities as independent variables and in-hospital mortality as the dependent variable. Finally, we compared area under the curve (AUC) statistics to determine the relative ability of each method of comorbidity ascertainment to predict in-hospital mortality. RESULTS:Chart review (AUC, 0.72) and administrative data (Charlson AUC, 0.83; Elixhauser AUC, 0.84) predicted in-hospital mortality with greater fidelity than patient report (AUC, 0.61). However, multivariate logistic regression analyses demonstrated that individual comorbidity derivation via chart review had the strongest relationship with in-hospital mortality. This is consistent with prior literature suggesting that administrative data have inherent, paradoxical biases with important implications for risk adjustment based solely on administrative data. CONCLUSIONS:Although comorbidities derived through administrative data did produce an AUC greater than chart review, our analyses suggest a coding bias in several comorbidities with a paradoxically protective effect. Therefore, chart review, while labor and resource intensive, may be the ideal method for ascertainment of clinically relevant comorbidities.

SUBMITTER: Weir RE

PROVIDER: S-EPMC6185751 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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The Relative Ability of Comorbidity Ascertainment Methodologies to Predict In-Hospital Mortality Among Hospitalized Community-acquired Pneumonia Patients.

Weir Ronald E RE Lyttle Christopher S CS Meltzer David O DO Dong Tien S TS Ruhnke Gregory W GW

Medical care 20181101 11

<h4>Background</h4>Despite widespread use of comorbidities for population health descriptions and risk adjustment, the ideal method for ascertaining comorbidities is not known. We sought to compare the relative value of several methodologies by which comorbidities may be ascertained.<h4>Methods</h4>This is an observational study of 1596 patients admitted to the University of Chicago for community-acquired pneumonia from 1998 to 2012. We collected data via chart abstraction, administrative data, ...[more]

PMID: 30234766

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Project description:ObjectivesSARS-CoV-2 may cause acute lung injury, and secondary infections are thus relevant complications in patients with COVID-19 pneumonia. However, detailed information on community- and hospital-acquired infections among patients with COVID-19 pneumonia is scarce.MethodsWe identified 220 SARS-CoV-2-positive patients hospitalized at the University Hospital Basel, Switzerland (between 25 February and 31 May 2020). We excluded patients who declined the general consent (n = 12), patients without clinical evidence of pneumonia (n = 29), and patients hospitalized for < 24 h (n = 17). We evaluated the frequency of community- and hospital-acquired infections using respiratory and blood culture materials with antigen, culture-based, and molecular diagnostics. For ICU patients, all clinical and microbial findings were re-evaluated interdisciplinary (intensive care, infectious disease, and clinical microbiology), and agreement reached to classify patients with infections.ResultsIn the final cohort of 162 hospitalized patients (median age 64.4 years (IQR, 50.4-74.2); 61.1% male), 41 (25.3%) patients were admitted to the intensive care unit, 34/41 (82.9%) required mechanical ventilation, and 17 (10.5%) of all hospitalized patients died. In total, 31 infections were diagnosed including five viral co-infections, 24 bacterial infections, and three fungal infections (ventilator-associated pneumonia, n = 5; tracheobronchitis, n = 13; pneumonia, n = 1; and bloodstream infection, n = 6). Median time to respiratory tract infection was 12.5 days (IQR, 8-18) and time to bloodstream infection 14 days (IQR, 6-30). Hospital-acquired bacterial and fungal infections were more frequent among ICU patients than other patients (36.6% vs. 1.7%). Antibiotic or antifungal treatment was administered in 71 (43.8%) patients.ConclusionsCommunity-acquired viral and bacterial infections were rare among COVID-19 pneumonia patients. By contrast, hospital-acquired bacterial or fungal infections were frequently complicating the course among ICU patients.

Project description:BackgroundLimited information exists on the clinical characteristics predictive of mortality in patients aged ≥65 years in many countries. The impact of adherence to current antimicrobial guidelines on the mortality of hospitalized elderly patients with community-acquired pneumonia (CAP) has never been assessed.MethodsA total of 3131 patients aged ≥65 years were enrolled from a multi-center, retrospective, observational study initiated by the CAP-China network. Risk factors for death were screened with multivariable logistic regression analysis, with emphasis on the evaluation of age, comorbidities and antimicrobial treatment regimen with regard to the current Chinese CAP guidelines.ResultsThe mean age of the study population was 77.4 ± 7.4 years. Overall in-hospital and 60-day mortality were 5.7% and 7.6%, respectively; these rates were three-fold higher in those aged ≥85 years than in the 65-74 group (11.9% versus 3.2% for in-hospital mortality and 14.1% versus 4.7% for 60-day mortality, respectively). The mortality was significantly higher among patients with comorbidities compared with those who were otherwise healthy. According to the 2016 Chinese CAP guidelines, 62.1% of patients (1907/3073) received non-adherent treatment. For general-ward patients without risk factors for Pseudomonas aeruginosa (PA) infection (n = 2258), 52.3% (1094/2090) were over-treated, characterized by monotherapy with an anti-pseudomonal β-lactam or combination with fluoroquinolone + β-lactam; while 71.4% of intensive care unit (ICU) patients (120/168) were undertreated, without coverage of atypical bacteria. Among patients with risk factors for PA infection (n = 815), 22.9% (165/722) of those in the general ward and 74.2% of those in the ICU (69/93) were undertreated, using regimens without anti-pseudomonal activity. The independent predictors of 60-day mortality were age, long-term bedridden status, congestive heart failure, CURB-65, glucose, heart rate, arterial oxygen saturation (SaO2) and albumin levels.ConclusionsOvertreatment in general-ward patients and undertreatment in ICU patients were critical problems. Compliance with Chinese guidelines will require fundamental changes in standard-of-care treatment patterns. The data included herein may facilitate early identification of patients at increased risk of mortality.Trial registrationThe study was registered at ClinicalTrials.gov ( NCT02489578 ).

Project description:BackgroundCurrently, there is no effective tool for predicting the risk of nonventilator hospital-acquired pneumonia (NV-HAP) in older hospitalized patients. The current study aimed to develop and validate a simple nomogram and a dynamic web-based calculator for predicting the risk of NV-HAP among older hospitalized patients.MethodsA retrospective evaluation was conducted on 15,420 consecutive older hospitalized patients admitted to a tertiary hospital in China between September 2017 and June 2020. The patients were randomly divided into training (n = 10,796) and validation (n = 4624) cohorts at a ratio of 7:3. Predictors of NV-HAP were screened using the least absolute shrinkage and selection operator method and multivariate logistic regression. The identified predictors were integrated to construct a nomogram using R software. Furthermore, the optimum cut-off value for the clinical application of the model was calculated using the Youden index. The concordance index (C-index), GiViTI calibration belts, and decision curve were analysed to validate the discrimination, calibration, and clinical utility of the model, respectively. Finally, a dynamic web-based calculator was developed to facilitate utilization of the nomogram.ResultsPredictors included in the nomogram were the Charlson comorbidity index, NRS-2002, enteral tube feeding, Barthel Index, use of sedatives, use of NSAIDs, use of inhaled steroids, and "time at risk". The C-index of the nomogram for the training and validation cohorts was 0.813 and 0.821, respectively. The 95% CI region of the GiViTI calibration belt in the training (P = 0.694) and validation (P = 0.614) cohorts did not cross the diagonal bisector line, suggesting that the prediction model had good discrimination and calibration. Furthermore, the optimal cut-off values for the training and validation cohorts were 1.58 and 1.74%, respectively. Analysis of the decision curve showed that the nomogram had good clinical value when the threshold likelihood was between 0 and 49%.ConclusionThe developed nomogram can be used to predict the risk of NV-HAP among older hospitalized patients. It can, therefore, help healthcare providers initiate targeted medical interventions in a timely manner for high-risk groups.

Project description:BackgroundSocial and hospital environmental factors that may be associated with hospital-acquired pneumonia (HAP) have not been evaluated. Comprehensive risk assessment for the incidence of HAP including sociodemographic, clinical, and hospital environmental factors was conducted using national health insurance claims data.MethodsThis is a population-based retrospective cohort study of adult patients who were hospitalized for more than 3 days from the Health Insurance Review and Assessment Service-National Inpatient Sample data between January 1, 2016 and December 31, 2018 in South Korea. Multivariable logistic regression analyses were conducted to identify the factors associated with the incidence of HAP.ResultsAmong the 512,278 hospitalizations, we identified 25,369 (5.0%) HAP cases. In multivariable analysis, well-known risk factors associated with HAP such as older age (over 70 vs. 20-29; adjusted odds ratio [aOR], 3.66; 95% confidence interval [CI] 3.36-3.99), male sex (aOR, 1.35; 95% CI 1.32-1.39), pre-existing lung diseases (asthma [aOR, 1.73; 95% CI 1.66-1.80]; chronic obstructive pulmonary disease [aOR, 1.62; 95% CI 1.53-1.71]; chronic lower airway disease [aOR, 1.79; 95% CI 1.73-1.85]), tube feeding (aOR, 3.32; 95% CI 3.16-3.50), suctioning (aOR, 2.34; 95% CI 2.23-2.47), positioning (aOR, 1.63; 95% CI 1.55-1.72), use of mechanical ventilation (aOR, 2.31; 95% CI 2.15-2.47), and intensive care unit admission (aOR, 1.29; 95% CI 1.22-1.36) were associated with the incidence of HAP. In addition, poverty (aOR, 1.08; 95% CI 1.04-1.13), general hospitals (aOR, 1.54; 95% CI 1.39-1.70), higher bed-to-nurse ratio (Grade ≥ 5; aOR, 1.45; 95% CI 1.32-1.59), higher number of beds per hospital room (6 beds; aOR, 3.08; 95% CI 2.77-3.42), and ward with caregiver (aOR, 1.19; 95% CI 1.12-1.26) were related to the incidence of HAP.ConclusionsThe incidence of HAP was associated with various sociodemographic, clinical, and hospital environmental factors. Thus, taking a comprehensive approach to prevent and treat HAP is important.

Project description:BackgroundCommunity acquired pneumonia (CAP) is a high incidence disease resulting in about 260,000 hospital admissions per year in Germany, more than myocardial infarction or stroke. Worldwide, CAP is the most frequent infectious disease with high lethality ranging from 1.2 % in those 20-29 years old to over 10 % in patients older than 70 years, even in industrial nations. CAP poses numerous medical challenges, which the PROGRESS (Pneumonia Research Network on Genetic Resistance and Susceptibility for the Evolution of Severe Sepsis) network aims to tackle: Operationalization of disease severity throughout the course of disease, outcome prediction for hospitalized patients and prediction of transitions from uncomplicated CAP to severe CAP, and finally, to CAP with sepsis and organ failure as a life-threatening condition. It is a major aim of PROGRESS to understand and predict patient heterogeneity regarding outcome in the hospital and to develop novel treatment concepts.MethodsPROGRESS was designed as a clinical, observational, multi-center study of patients with CAP requiring hospitalization. More than 1600 patients selected for low burden of co-morbidities have been enrolled, aiming at a total of 3000. Course of disease, along with therapy, was closely monitored by daily assessments and long-term follow-up. Daily blood samples allow in depth molecular-genetic characterization of patients. We established a well-organized workflow for sample logistics and a comprehensive data management system to collect and manage data from more than 50 study centers in Germany and Austria. Samples are stored in a central biobank and clinical data are stored in a central data base which also integrates all data from molecular assessments.DiscussionWith the PROGRESS study, we established a comprehensive data base of high quality clinical and molecular data allowing investigation of pressing research questions regarding CAP. In-depth molecular characterization will contribute to the discovery of disease mechanisms and establishment of diagnostic and predictive biomarkers. A strength of PROGRESS is the focus on younger patients with low burden of co-morbidities, allowing a more direct look at host biology with less confounding. As a resulting limitation, insights from PROGRESS will require validation in representative patient cohorts to assess clinical utility.Trial registrationThe PROGRESS study was retrospectively registered on May 24(th), 2016 with ClinicalTrials.gov: NCT02782013.

Dataset Information

The Relative Ability of Comorbidity Ascertainment Methodologies to Predict In-Hospital Mortality Among Hospitalized Community-acquired Pneumonia Patients.

Publications

The Relative Ability of Comorbidity Ascertainment Methodologies to Predict In-Hospital Mortality Among Hospitalized Community-acquired Pneumonia Patients.

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