Coding Long COVID: Characterizing a new disease through an ICD-10 lens

Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs

Post-Acute Sequelae of SARS-CoV-2 infection (PASC), also known as Long-COVID, encompasses a variety of complex and varied outcomes following COVID-19 infection that are still poorly understood. We clustered over 600 million condition diagnoses from 14 million patients available through the National COVID Cohort Collaborative (N3C), generating hundreds of highly detailed clinical phenotypes. Assessing patient clinical trajectories using these clusters allowed us to identify individual conditions and phenotypes strongly increased after acute infection. We found many conditions increased in COVID-19 patients compared to controls, and using a novel method to associate patients with clusters over time, we additionally found phenotypes specific to patient sex, age, wave of infection, and PASC diagnosis status. While many of these results reflect known PASC symptoms, the resolution provided by this unprecedented data scale suggests avenues for improved diagnostics and mechanistic understanding of this multifaceted disease.

The long tail of COVID and the tale of long COVID: Diagnostic construction and the management of ignorance

We bring together insights from the sociology of diagnosis and the sociology of ignorance to examine the early diagnostic unfolding of 'Long COVID' (LC). Originally described by patient activists, researchers set out to ponder its unwieldy clinical boundaries. Using a scoping review method in tandem with qualitative content analytic techniques, we analyse medicine's initial struggles to construct a LC diagnosis. Paying attention to the dynamics of ignorance, we highlight three consequential conceptual manoeuvres in the early classifications of LC: causal agnosticism concerning the relationship between COVID-19 and LC, evasion of lumping LC with similar conditions; and the predictable splitting off of medically explainable cases from the LC designation. These manoeuvres are not maleficent, inept or unreasonable. They are practical but impactful responses to the classificatory dilemmas present in the construction of diagnoses amidst ignorance. Although there are unique aspects to LC, we suggest that its early fate is nevertheless emblematic of medicine's diagnostic standardisation processes more generally. To varying degrees, diagnoses are ignorance management strategies; they create a pathway through the uncertainty at the core of disease realities. However, while diagnoses circumscribe some types of ignorance, they produce others through the creation of blind spots and paths not taken.

Characteristics of brain lesions found using MRI imaging in patients with post-COVID with signs of cognitive decline

OBJECTIVE

Aim: To describe and evaluate abnormalities of the brain in post-COVID patients with neurologic symptoms and cognitive deficits using MRI imaging of the brain.

PATIENTS AND METHODS

Materials and Methods: We included 21 patients with a previous positive PCR testing for SARS-CoV-2 and one or more of the following symptoms: memory and cognitive decline, dizziness, anxiety, depression, chronic headaches. All patients had MRI imaging done at onset of symptoms, but after at least 1 year after positive testing for COVID-19 based on the patient's previous medical history.

RESULTS

Results: All of the patients complained of lack of concentration, forgetfulness, hard to process information. 15 patients suffered from confusion, 10 from anxiety. Of the 21 patients 14 had isolated chronic headaches, 3 had isolated dizziness, 4 patients had both symptoms upon inclusion. All patients underwent MRI imaging as a part of the diagnostic workup and had varying degrees of neurodegeneration.

CONCLUSION

Conclusions: Our data correlates with existing research and shows tendency for cognitive decline in post-COVID patients. This provides groundwork for further research to determine correlation between acceleration of neurodegeneration and post-COVID.

Risk factors associated with post-acute sequelae of SARS-CoV-2: an N3C and NIH RECOVER study

BACKGROUND

More than one-third of individuals experience post-acute sequelae of SARS-CoV-2 infection (PASC, which includes long-COVID). The objective is to identify risk factors associated with PASC/long-COVID diagnosis.

METHODS

This was a retrospective case-control study including 31 health systems in the United States from the National COVID Cohort Collaborative (N3C). 8,325 individuals with PASC (defined by the presence of the International Classification of Diseases, version 10 code U09.9 or a long-COVID clinic visit) matched to 41,625 controls within the same health system and COVID index date within ± 45 days of the corresponding case's earliest COVID index date. Measurements of risk factors included demographics, comorbidities, treatment and acute characteristics related to COVID-19. Multivariable logistic regression, random forest, and XGBoost were used to determine the associations between risk factors and PASC.

RESULTS

Among 8,325 individuals with PASC, the majority were > 50 years of age (56.6%), female (62.8%), and non-Hispanic White (68.6%). In logistic regression, middle-age categories (40 to 69 years; OR ranging from 2.32 to 2.58), female sex (OR 1.4, 95% CI 1.33-1.48), hospitalization associated with COVID-19 (OR 3.8, 95% CI 3.05-4.73), long (8-30 days, OR 1.69, 95% CI 1.31-2.17) or extended hospital stay (30 + days, OR 3.38, 95% CI 2.45-4.67), receipt of mechanical ventilation (OR 1.44, 95% CI 1.18-1.74), and several comorbidities including depression (OR 1.50, 95% CI 1.40-1.60), chronic lung disease (OR 1.63, 95% CI 1.53-1.74), and obesity (OR 1.23, 95% CI 1.16-1.3) were associated with increased likelihood of PASC diagnosis or care at a long-COVID clinic. Characteristics associated with a lower likelihood of PASC diagnosis or care at a long-COVID clinic included younger age (18 to 29 years), male sex, non-Hispanic Black race, and comorbidities such as substance abuse, cardiomyopathy, psychosis, and dementia. More doctors per capita in the county of residence was associated with an increased likelihood of PASC diagnosis or care at a long-COVID clinic. Our findings were consistent in sensitivity analyses using a variety of analytic techniques and approaches to select controls.

CONCLUSIONS

This national study identified important risk factors for PASC diagnosis such as middle age, severe COVID-19 disease, and specific comorbidities. Further clinical and epidemiological research is needed to better understand underlying mechanisms and the potential role of vaccines and therapeutics in altering PASC course.

SARS-CoV-2 Reinfection is Preceded by Unique Biomarkers and Related to Initial Infection Timing and Severity: an N3C RECOVER EHR-Based Cohort Study

Although the COVID-19 pandemic has persisted for over 2 years, reinfections with SARS-CoV-2 are not well understood. We use the electronic health record (EHR)-based study cohort from the National COVID Cohort Collaborative (N3C) as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We validate previous findings of reinfection incidence (5.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present novel findings that Long COVID diagnoses occur closer to the index date for infection or reinfection in the Omicron BA epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between first infection and reinfection (chi-squared value: 9446.2, p-value: 0) with a medium effect size (Cramer's V: 0.18, DoF = 4).

Risk Factors Associated with Post-Acute Sequelae of SARS-CoV-2 in an EHR Cohort: A National COVID Cohort Collaborative (N3C) Analysis as part of the NIH RECOVER program

Background

More than one-third of individuals experience post-acute sequelae of SARS-CoV-2 infection (PASC, which includes long-COVID).

Objective

To identify risk factors associated with PASC/long-COVID.

Design

Retrospective case-control study.

Setting

31 health systems in the United States from the National COVID Cohort Collaborative (N3C).

Patients

8,325 individuals with PASC (defined by the presence of the International Classification of Diseases, version 10 code U09.9 or a long-COVID clinic visit) matched to 41,625 controls within the same health system.

Measurements

Risk factors included demographics, comorbidities, and treatment and acute characteristics related to COVID-19. Multivariable logistic regression, random forest, and XGBoost were used to determine the associations between risk factors and PASC.

Results

Among 8,325 individuals with PASC, the majority were >50 years of age (56.6%), female (62.8%), and non-Hispanic White (68.6%). In logistic regression, middle-age categories (40 to 69 years; OR ranging from 2.32 to 2.58), female sex (OR 1.4, 95% CI 1.33-1.48), hospitalization associated with COVID-19 (OR 3.8, 95% CI 3.05-4.73), long (8-30 days, OR 1.69, 95% CI 1.31-2.17) or extended hospital stay (30+ days, OR 3.38, 95% CI 2.45-4.67), receipt of mechanical ventilation (OR 1.44, 95% CI 1.18-1.74), and several comorbidities including depression (OR 1.50, 95% CI 1.40-1.60), chronic lung disease (OR 1.63, 95% CI 1.53-1.74), and obesity (OR 1.23, 95% CI 1.16-1.3) were associated with increased likelihood of PASC diagnosis or care at a long-COVID clinic. Characteristics associated with a lower likelihood of PASC diagnosis or care at a long-COVID clinic included younger age (18 to 29 years), male sex, non-Hispanic Black race, and comorbidities such as substance abuse, cardiomyopathy, psychosis, and dementia. More doctors per capita in the county of residence was associated with an increased likelihood of PASC diagnosis or care at a long-COVID clinic. Our findings were consistent in sensitivity analyses using a variety of analytic techniques and approaches to select controls.

Conclusions

This national study identified important risk factors for PASC such as middle age, severe COVID-19 disease, and specific comorbidities. Further clinical and epidemiological research is needed to better understand underlying mechanisms and the potential role of vaccines and therapeutics in altering PASC course.