Prognostic severity scores for patients with COPD exacerbations attending emergency departments

Quintana, José M.; Esteban, Cristóbal; Unzurrunzaga, Anette; García-Gutiérrez, Susana; González, Nerea; Lafuente, Iratxe; Baré, Marisa; Nf, de Larrea; Vidal, Silvia M.

doi:10.5588/ijtld.14.0312

Cited by 7 publications

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“…The selected two outcome variables were also previously described when the predictive models were developed [9][10]. However, due to the importance of the two outcomes for the purpose of this study, we present a brief definition of them.…”

Section: Methodsmentioning

confidence: 99%

“…The main screen incorporates a help button where specific definition of all the predictive variables is detailed exactly the same as in the manuscripts were prediction rules were developed [9][10]. The computer tool also incorporates a predefined range of acceptable values for each variable in order to control for typing mistakes or out of range values.…”

Section: The Computer Application: Prevecopdmentioning

confidence: 99%

“…More precisely, the Investigacion en Resultados y Servicios de Salud COPD (IRYSS-COPD) Appropriateness Study group has developed clinical prediction rules for short-term outcomes in eCOPD patients attending an ED. These outcomes include: 1) mortality during hospital admission or within a week after the ED visit [9]; and 2) admission to an intensive care unit (ICU) or an intermediate respiratory care unit (IRCU) during the eCOPD episode [10].…”

Section: Introductionmentioning

confidence: 99%

“…We present the PrEveCOPD (Prediction of Evolution of patients with eCOPD) tool for prediction of two outcomes: 1) mortality during hospital admission or within a week after the ED visit; and 2) admission to an ICU or IRCU during the eCOPD episode. The algorithms included in the computer tool are based on the clinical prediction rules previously published by Quintana et al [9][10] for the IRYSS-COPD Study.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Computer Application to Predict Adverse Events in the Short-Term Evolution of Patients With Exacerbation of Chronic Obstructive Pulmonary Disease (Preprint)

Aróstegui¹,

Legarreta²,

Barrio³

et al. 2018

Preprint

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Section: Methodsmentioning

confidence: 99%

Section: The Computer Application: Prevecopdmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Computer Application to Predict Adverse Events in the Short-Term Evolution of Patients With Exacerbation of Chronic Obstructive Pulmonary Disease (Preprint)

Aróstegui¹,

Legarreta²,

Barrio³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…More precisely, the Investigación en Resultados y Servicios de Salud COPD (IRYSS-COPD) Appropriateness Study group has developed clinical prediction rules for short-term outcomes in eCOPD patients attending an ED. These outcomes include (1) mortality during hospital admission or within a week after the ED visit [9] and (2) admission to an intensive care unit (ICU) or an intermediate respiratory care unit (IRCU) during the eCOPD episode [10].…”

Section: Introductionmentioning

confidence: 99%

A Computer Application to Predict Adverse Events in the Short-Term Evolution of Patients With Exacerbation of Chronic Obstructive Pulmonary Disease

et al. 2019

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Background Chronic obstructive pulmonary disease (COPD) is a common chronic disease. Exacerbations of COPD (eCOPD) contribute to the worsening of the disease and the patient’s evolution. There are some clinical prediction rules that may help to stratify patients with eCOPD by their risk of poor evolution or adverse events. The translation of these clinical prediction rules into computer applications would allow their implementation in clinical practice. Objective The goal of this study was to create a computer application to predict various outcomes related to adverse events of short-term evolution in eCOPD patients attending an emergency department (ED) based on valid and reliable clinical prediction rules. Methods A computer application, Prediction of Evolution of patients with eCOPD (PrEveCOPD), was created to predict 2 outcomes related to adverse events: (1) mortality during hospital admission or within a week after an ED visit and (2) admission to an intensive care unit (ICU) or an intermediate respiratory care unit (IRCU) during the eCOPD episode. The algorithms included in the computer tool were based on clinical prediction rules previously developed and validated within the Investigación en Resultados y Servicios de Salud COPD study. The app was developed for Windows and Android systems, using Visual Studio 2008 and Eclipse, respectively. Results The PrEveCOPD computer application implements the prediction models previously developed and validated for 2 relevant adverse events in the short-term evolution of patients with eCOPD. The application runs under Windows and Android systems and it can be used locally or remotely as a Web application. Full description of the clinical prediction rules as well as the original references is included on the screen. Input of the predictive variables is controlled for out-of-range and missing values. Language can be switched between English and Spanish. The application is available for downloading and installing on a computer, as a mobile app, or to be used remotely via internet. Conclusions The PrEveCOPD app shows how clinical prediction rules can be summarized into simple and easy to use tools, which allow for the estimation of the risk of short-term mortality and ICU or IRCU admission for patients with eCOPD. The app can be used on any computer device, including mobile phones or tablets, and it can guide the clinicians to a valid stratification of patients attending the ED with eCOPD. Trial Registration ClinicalTrials.gov NCT00102401; https://clinicaltrials.gov/ct2/show/results/NCT02434536 (Archived by WebCite at http://www.webcitation.org/76iwTxYuA) International Registered Report Identifier (IRRID) RR2-10.1186/1472-6963-11-322

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Effect of Intensivist Communication in a Simulated Setting on Interpretation of Prognosis Among Family Members of Patients at High Risk of Intensive Care Unit Admission

et al. 2020

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IMPORTANCE Discordance about prognosis between a patient's health care decision-making surrogate and the treating intensivist is common in the intensive care unit (ICU). Empowering families, friends, and caregivers of patients who are critically ill to make informed decisions about care is important, but it is unclear how best to communicate prognostic information to surrogates when a patient is expected to die. OBJECTIVETo determine whether family members, who are often health care decision-making surrogates, interpret intensivists as being more optimistic when questions about prognosis in the ICU are answered indirectly. DESIGN, SETTING, AND PARTICIPANTSThis web-based randomized trial was conducted between September 27, 2019, and October 17, 2019, among a national sample of adult children, spouses, partners, or siblings of people with chronic obstructive pulmonary disease who were receiving longterm oxygen therapy. Participants were shown video vignettes depicting an intensivist answering a standardized question about the prognosis of a patient at high risk of death on day 3 of ICU admission. Participants were excluded if they had worked as a physician, nurse, or advanced health care practitioner. Data were analyzed from INTERVENTIONS Participants were randomized to view 1 of 4 intensivist communication styles in response to the question "What do you think is most likely to happen?": (1) a direct response (control), (2) an indirect response comparing the patient's condition with that of other patients, (3) an indirect response describing the patient's deteriorating physiological condition, or (4) redirection to a discussion of the patient's values and goals. MAIN OUTCOMES AND MEASURES Participant responses to 2 questions: (1) "If you had to guess,what do you think the doctor thinks is the chance that your loved one will survive this hospitalization?" and (2) "What do you think are the chances that your loved one will survive this hospitalization?" answered using a 0% to 100% probability scale. RESULTSAmong 302 participants (median [interquartile range] age, 49 [38-59] years; 204 [68%]women) included in the trial, 165 (55%) were adult children of the individual with chronic obstructive pulmonary disease; 77 participants were randomized to view a direct response, 77 participants were randomized to view an indirect response referencing other patients, 68 participants were randomized to view an indirect response referencing physiological condition, and 80 participants were randomized to view a redirection response. Compared with participants who viewed a direct response, participants who viewed an indirect response referencing other patients (β = 10 [95% CI, (continued) Key Points Question Do intensivist communication patterns affect the way family members understand their loved one's prognosis in the intensive care unit?Abstract (continued) 1-19]; P = .03), physiological condition (β = 10 [95% CI, 0-19]; P = .04), or redirection to a discussion of the patient's values and goals (β = 19 [95% CI, 10-28]; P < .001) p...

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Prognostic severity scores for patients with COPD exacerbations attending emergency departments

Abstract: Three clinical predictors available in the ED can be used to create a simple score to predict the need for intensive treatment among eCOPD patients. Such a score can be a tool for clinical practice.

Cited by 7 publications

References 0 publications

A Computer Application to Predict Adverse Events in the Short-Term Evolution of Patients With Exacerbation of Chronic Obstructive Pulmonary Disease (Preprint)

A Computer Application to Predict Adverse Events in the Short-Term Evolution of Patients With Exacerbation of Chronic Obstructive Pulmonary Disease (Preprint)

A Computer Application to Predict Adverse Events in the Short-Term Evolution of Patients With Exacerbation of Chronic Obstructive Pulmonary Disease

Effect of Intensivist Communication in a Simulated Setting on Interpretation of Prognosis Among Family Members of Patients at High Risk of Intensive Care Unit Admission

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