ABSTRACT
BACKGROUND: Machine learning (ML) may improve clinical decision-making in critical care settings, but intrinsic biases in datasets can introduce bias into predictive models. This study aims to determine if publicly available critical care datasets provide relevant information to identify historically marginalized populations. METHOD: We conducted a review to identify the manuscripts that report the training/validation of ML algorithms using publicly accessible critical care electronic medical record (EMR) datasets. The datasets were reviewed to determine if the following 12 variables were available: age, sex, gender identity, race and/or ethnicity, self-identification as an indigenous person, payor, primary language, religion, place of residence, education, occupation, and income. RESULTS: 7 publicly available databases were identified. Medical Information Mart for Intensive Care (MIMIC) reports information on 7 of the 12 variables of interest, Sistema de Informação de Vigilância Epidemiológica da Gripe (SIVEP-Gripe) on 7, COVID-19 Mexican Open Repository on 4, and eICU on 4. Other datasets report information on 2 or fewer variables. All 7 databases included information about sex and age. Four databases (57%) included information about whether a patient identified as native or indigenous. Only 3 (43%) included data about race and/or ethnicity. Two databases (29%) included information about residence, and one (14%) included information about payor, language, and religion. One database (14%) included information about education and patient occupation. No databases included information on gender identity and income. CONCLUSION: This review demonstrates that critical care publicly available data used to train AI algorithms do not include enough information to properly look for intrinsic bias and fairness issues towards historically marginalized populations.
ABSTRACT
Objective To investigate risk factors and subphenotypes associated with long term symptoms and outcomes after hospital admission for covid-19. Design Prospective, multicentre observational study. Setting 93 hospitals in France. Participants Data from 2187 adults admitted to hospital with covid-19 in France between 1 February 2020 and 30 June 2021. Main outcome measures Primary endpoint was the total number of persistent symptoms at six months after hospital admission that were not present before admission. Outcomes examined at six months were persistent symptoms, Hospital Anxiety and Depression Scale, six minute walk test distances, 36-Item Short Form Health Survey scores, and ability to resume previous professional activities and self-care. Secondary endpoints included vital status at six months, and results of standardised quality-of-life scores. Additionally, an unsupervised consensus clustering algorithm was used to identify subphenotypes based on the severity of hospital course received by patients. Results 1109 (50.7%) of 2187 participants had at least one persistent symptom. Factors associated with an increased number of persistent symptoms were in-hospital supplemental oxygen (odds ratio 1.12, 95% confidence interval 1 to 1.24), no intensive care unit admission (1.15, 1.01 to 1.32), female sex (1.33, 1.22 to 1.45), gastrointestinal haemorrhage (1.51, 1.02 to 2.23), a thromboembolic event (1.66, 1.17 to 2.34), and congestive heart failure (1.76, 1.27 to 2.43). Three subphenotypes were identified: including patients with the least severe hospital course (based on ventilatory support requirements). Although Hospital Anxiety and Depression Scale scores were within normal values for all groups, patients of intermediate severity and more comorbidities had a higher median Hospital Anxiety and Depression Scale score than did the other subphenotypes. Patients in the subphenotype with most severe hospital course had worse short form-36 scores and were less able to resume their professional activity or care for themselves as before compared with other subphenotypes. Conclusions Persistent symptoms after hospital admission were frequent, regardless of acute covid-19 severity. However, patients in more severe subphenotypes had a significantly worse functional status and were less likely to resume their professional activity or able to take care of themselves as before. Trial registration NCT04262921.