What outcomes should be evaluated in critically ill patients?

Teixeira, Cassiano; Kern, M J; Rosa, Régis Goulart

doi:10.5935/0103-507x.20210040

Cited by 4 publications

(4 citation statements)

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Section: Introductionmentioning

confidence: 99%

“…The key outcomes of significant randomized controlled trials in intensive care medicine are disease-focused [ 1 ]. In fact, significant clinical advances over the past few decades have enabled the lowering of mortality in critically ill patients, which is highly important for intensivists [ 1 ]. However, patient-centered outcomes have grown in importance over the years, and the quality of life and functional, cognitive, and neurological performance stand out in the scope of action of critical care physicians [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

“…In fact, significant clinical advances over the past few decades have enabled the lowering of mortality in critically ill patients, which is highly important for intensivists [ 1 ]. However, patient-centered outcomes have grown in importance over the years, and the quality of life and functional, cognitive, and neurological performance stand out in the scope of action of critical care physicians [ 1 ]. Family members and caregivers are crucial components for enhancing these patient-centered outcomes.…”

Section: Introductionmentioning

confidence: 99%

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Family Satisfaction With Critical Care: Before and After the COVID-19 Outbreak

Jorge¹,

Hipólito-Reis²,

Esteves³

et al. 2023

Cureus

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IntroductionFamily satisfaction with intensive care units (ICU) is recognized as a key component of the quality of care. As a result, family members are now more involved in the care process, and their needs are recognized throughout the ICU stay. The coronavirus disease 2019 (COVID-19) changed healthcare worldwide, due to the several restrictions imposed; the communication patterns changed drastically, and institutions were forced to adapt to create a balance between security and the needs of relatives. The aim of this study was to assess family members' satisfaction with the ICU and determine if the COVID-19 restructuring affected family satisfaction. MethodsA prospective observational study was performed among the designated family members (DFM) of ICU patients over two time periods, a pre-pandemic period from December 2019 to February 2020 and a pandemic period from May 2020 to February 2021. The Family Satisfaction in the Intensive Care Unit 24 (FS-ICU 24) questionnaire, which was given to the DFM, was the instrument used to determine family satisfaction. ResultsThe study involved 290 DFM, 175 during the pre-pandemic phase and 115 during the pandemic period. The overall and domain-specific family satisfaction scores were high (score > 80) in both the pre-pandemic and pandemic periods. The greatest satisfaction levels were related with symptom management and how nurses and doctors cared for the patient. No statistical differences were found between the two time periods. Lastly, a positive association between the two domains explored by FS-ICU 24, satisfaction with care and satisfaction with decision-making process, was verified in both time frames. ConclusionThe data obtained revealed very good outcomes on the different FS-ICU 24 domains, in line with other studies in literature. No significant differences were found between the pre-pandemic and pandemic periods, suggesting that the measures implemented during the COVID-19 were successful. The importance of involving families in the decision-making process, providing them with accurate information, and active listening, as well as using better communication skills, is emphasized throughout all these results. The relevance of measuring family satisfaction should be brought to the attention of family members and healthcare professionals so that additional research may be conducted.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Family Satisfaction With Critical Care: Before and After the COVID-19 Outbreak

Jorge¹,

Hipólito-Reis²,

Esteves³

et al. 2023

Cureus

View full text Add to dashboard Cite

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“…Mortality prediction in ICU patients has been a major challenge in the area of medical informatics [6] and has long been used as a quality indicator. Mortality is a major end point in epidemiological and interventional studies in the ICUs [7]. Published studies so far mainly focus on the prediction of in-hospital or early mortality, irrespective of the primary diagnosis and related comorbidities [8][9][10][11][12], whereas studies focusing on late mortality prediction are quite rare [13,14].…”

Section: Introductionmentioning

confidence: 99%

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

Danilatou

Nikolakakis

Antonakaki

et al. 2022

IJMS

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Intensive care unit (ICU) patients with venous thromboembolism (VTE) and/or cancer suffer from high mortality rates. Mortality prediction in the ICU has been a major medical challenge for which several scoring systems exist but lack in specificity. This study focuses on two target groups, namely patients with thrombosis or cancer. The main goal is to develop and validate interpretable machine learning (ML) models to predict early and late mortality, while exploiting all available data stored in the medical record. To this end, retrospective data from two freely accessible databases, MIMIC-III and eICU, were used. Well-established ML algorithms were implemented utilizing automated and purposely built ML frameworks for addressing class imbalance. Prediction of early mortality showed excellent performance in both disease categories, in terms of the area under the receiver operating characteristic curve (AUC−ROC): VTE-MIMIC-III 0.93, eICU 0.87, cancer-MIMIC-III 0.94. On the other hand, late mortality prediction showed lower performance, i.e., AUC−ROC: VTE 0.82, cancer 0.74–0.88. The predictive model of early mortality developed from 1651 VTE patients (MIMIC-III) ended up with a signature of 35 features and was externally validated in 2659 patients from the eICU dataset. Our model outperformed traditional scoring systems in predicting early as well as late mortality. Novel biomarkers, such as red cell distribution width, were identified.

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Reimagining Patient-Centered Outcome Measurement

Teixeira

2024

CHEST Critical Care

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What outcomes should be evaluated in critically ill patients?

Cited by 4 publications

References 0 publications

Family Satisfaction With Critical Care: Before and After the COVID-19 Outbreak

Family Satisfaction With Critical Care: Before and After the COVID-19 Outbreak

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

Reimagining Patient-Centered Outcome Measurement

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