Post-acute sequelae of COVID-19 in solid organ transplant recipients.

BACKGROUND: Post-acute sequelae of coronavirus disease 2019 (COVID-19) (PASC), defined as prolonged symptoms following an episode of COVID-19, is not well-characterized in solid organ transplant recipients (SOTR). In this study, we aimed to assess the prevalence of PASC in SOTR, its descriptive characteristics, and associated risk factors. METHODS: We retrospectively identified SOTRs with acute COVID-19 between June 1, 2020 and April 15, 2022, and abstracted demographic and medical history, characteristics of acute COVID-19 illness, and COVID-19 vaccination status. We defined PASC as ongoing/new symptoms present at 6 weeks or longer following acute COVID-19 diagnosis. RESULTS: Among 208 SOTRs with acute COVID-19, 72 (35%) developed PASC. Common symptoms were respiratory symptoms (67%), headache (40%), and difficulty concentrating (10%). Severe acute COVID-19 disease and presence of respiratory symptoms were associated with higher odds of PASC in multivariable analyses, while receipt of at least one COVID-19 vaccination prior to transplantation was protective. CONCLUSION: We found that PASC occurs in about a third of SOTRs with acute COVID-19 and has similar symptoms as described previously in immunocompetent hosts. Pre-transplant vaccination may be protective. Further prospective multicenter studies are needed.

Nocturnal Respiratory Rate Dynamics Enable Early Recognition of Impending Hospitalizations.

The days and weeks preceding hospitalization are poorly understood because they transpire before patients are seen in conventional clinical care settings. Home health sensors offer opportunities to learn signatures of impending hospitalizations and facilitate early interventions, however the relevant biomarkers are unknown. Nocturnal respiratory rate (NRR) is an activity-independent biomarker that can be measured by adherence-independent sensors in the home bed. Here, we report automated longitudinal monitoring of NRR dynamics in a cohort of high-risk recently hospitalized patients using non-contact mechanical sensors under patients' home beds. Since the distribution of nocturnal respiratory rates in populations is not well defined, we first quantified it in 2,000 overnight sleep studies from the NHLBI Sleep Heart Health Study. This revealed that interpatient variability was significantly greater than intrapatient variability (NRR variances of 11.7 brpm2 and 5.2 brpm2 respectively, n=1,844,110 epochs), which motivated the use of patient-specific references when monitoring longitudinally. We then performed adherence-independent longitudinal monitoring in the home beds of 34 high-risk patients and collected raw waveforms (sampled at 80 Hz) and derived quantitative NRR statistics and dynamics across 3,403 patient-nights (n= 4,326,167 epochs). We observed 23 hospitalizations for diverse causes (a 30-day hospitalization rate of 20%). Hospitalized patients had significantly greater NRR deviations from baseline compared to those who were not hospitalized (NRR variances of 3.78 brpm2 and 0.84 brpm2 respectively, n= 2,920 nights). These deviations were concentrated prior to the clinical event, suggesting that NRR can identify impending hospitalizations. We analyzed alarm threshold tradeoffs and demonstrated that nominal values would detect 11 of the 23 clinical events while only alarming 2 times in non-hospitalized patients. Taken together, our data demonstrate that NRR dynamics change days to weeks in advance of hospitalizations, with longer prodromes associating with volume overload and heart failure, and shorter prodromes associating with acute infections (pneumonia, septic shock, and covid-19), inflammation (diverticulitis), and GI bleeding. In summary, adherence-independent longitudinal NRR monitoring has potential to facilitate early recognition and management of pre-symptomatic disease.

Natural History of Adapted Leaman Score Assessing Coronary Artery Disease Progression by Computed Tomography Angiography: A 7-Year Follow-Up Report.

BACKGROUND: Coronary computed tomographic angiography (CCTA) provides a non-invasive assessment of the coronary artery tree. Computed Tomography - adapted Leaman Score (CT-LeSc) has been shown to be an independent predictor of cardiac events in coronary artery disease (CAD) patients with a score greater than 5 (high). PURPOSE: To investigate the relationship between CT-LeSc and the progression of CAD and to provide vessel- and segment-level CAD qualification and quantification at baseline and 7-year follow-up. METHODS: Patients with multivessel CAD and CCTA assessments at baseline and follow-up were included. The CT-LeSc analysis was performed in a paired fashion. The patient-level scores and the differences between each phase were assessed by 2 analysts in an independent core laboratory. RESULTS: This study analyzed 248 coronary segments from 17 patients with a mean follow-up interval of 7.5 ± 0.6 years. The mean CT-LeSc at baseline and follow-up were 14.6 ± 4.2 and 16.9 ± 1.5, respectively, with an absolute increase of 2.3 ± 1.8. The mean cumulative increase of new lesions was 0.2 ± 0.2 per year. Over time, 14.6% of the non-obstructive lesions became obstructive, and 15.0% of the non-calcified plaques became calcified. There were 29 new lesions found at follow-up, and out of these, 16 were obstructive and 19 were non-calcified. CONCLUSION: In patients at high risk for cardiac events, as determined by CT-LeSc, there was an increase in CT-LeSc, obstructive lesions, and calcified plaques over the 7-year follow-up period. Most of the new lesions were obstructive and non-calcified. This is the first report showing long-term serial imaging CCTA changes in a high-risk population.