Apryl Susi

The long-term neuropsychiatric effects of COVID-19 are still unclear. Various mental health conditions are known to be influenced by biopsychosocial factors. We sought to investigate whether COVID-19 infection increases the risk for newly diagnosed anxiety, mood, or trauma and stressor-related disorders in individuals ages 12–64 years. We performed a retrospective cohort study using data from the Military Health System database (2018–2022). A propensity score match pairing each person with a COVID-19 diagnosis to two uninfected individuals was implemented, balancing matches across 1852 different variables representing medical records of procedures, diagnoses, and prescriptions in the year prior to COVID-19 infection. Exact matching was performed on sex, age in years, beneficiary type and month of entry into the cohort. We calculated the hazard ratios (HR) and Bonferroni-corrected confidence intervals (BoCI) for new mental health diagnoses using the Cox proportional hazards models. The initial matched cohort included 788,185 individuals. COVID-19 significantly increased the risk for newly diagnosed mental health conditions. The effect was strongest for trauma and stressor-related disorders (HR, 1.29; BoCI, 1.22–1.37), followed by mood disorders (HR, 1.22; BoCI, 1.15–1.30) and anxiety disorders (HR, 1.16; BoCI, 1.12–1.21). COVID-19 infection is associated with the subsequent diagnosis of a new mental health condition, including depressive, trauma and stressor-related, mood, and anxiety disorders. Our findings suggest that screening for mental health conditions should be a key part of post-COVID-19 care, and more work is needed to understand the biological reasons for this connection and consider the role of vaccines for prevention.

To identify whether a relationship exists between COVID-19 and appendicitis and compare the incidence of appendicitis during three pandemic years to the year prior to the pandemic, we conducted two observational retrospective studies: a propensity score-matched (PSM) cohort and a repeated monthly cross-sectional study. We used data from the Military Health System (MHS) Data Repository, which contains data about healthcare provided to active-duty service members, retirees, and their dependents. For the PSM cohort of 753,138 individuals, patients with COVID-19 between July 2020 and June 2021 from the MHS were matched to two similar people without COVID-19. Survival analysis using a conditional Cox proportional hazards model explored these relationships. For the cross-sectional study we used a separate, unmatched MHS cohort of 10,402,021 individuals. Poisson regression generated incident rate ratios (IRRs) of any appendicitis or complicated appendicitis by year, comparing three pandemic years to one pre-pandemic year. COVID-19 was associated with appendicitis or appendectomy within the first year of infection (hazard ratio: 1.13, 95% confidence interval: 1.02–1.26). The IRRs for both any appendicitis and complicated appendicitis were significantly less than one when comparing individual pandemic years to the pre-pandemic year. COVID-19 is associated with appendicitis. Rates of any appendicitis and complicated appendicitis were lower in each individual pandemic year.

Introduction: There are bidirectional associations between COVID-19 and thyroid disease; little is known about these risks among active-duty service members (ADSM). This study seeks to understand the associations between COVID-19 and thyroid disease in this population and in non–active-duty adults within the military health system. Methods: The researchers conducted a retrospective propensity score-matched cohort study using the Military Health System Database including individuals 18-64 years of age. International Classification of Diseases, 10th revision codes and laboratory results identified COVID-19 infections from July 2020 to June 2021. Patients with COVID-19 were matched 1:2 to controls based on age, sex, beneficiary type, month, and a propensity score. Thyroid disease was identified by ICD-10 codes and those with a thyroid diagnosis in the year prior were excluded. Hazard ratios (HR) and Bonferroni-adjusted 95% confidence intervals (95BoCI) were calculated. Results: There were 103,778 exposures and 207,556 controls among ADSM and 125,399 exposures and 250,798 controls among non-ADSM. Among ADSM there was a significant association with having any thyroid disease diagnoses (HR = 1.48, 95%CI [1.15-1.89]). However, no significant relationship was found between COVID-19 infection and hypothyroidism (HR = 1.11, 95BoCI [0.93-1.31]), Hashimoto’s thyroiditis (HR = 1.07, 95BoCI [0.77-1.48]), Grave’s disease (HR = 1.20, 95BoCI [0.85-1.70]), or other thyroiditis (HR = 1.11, 95BoCI [0.83-1.47]). Non-ADSM adults from ages 18-64 showed significantly increased rates of hypothyroidism (HR = 1.11, 95BoCI [1.03-1.19]), Hashimoto’s thyroiditis (HR = 1.15, 95BoCI [1.01-1.31]), Grave’s disease (HR = 1.26, 95BoCI [1.09-1.46]), and other thyroiditis (HR = 1.31, 95BoCI [1.18-1.45]). Conclusions: ADSMs with COVID-19 infection demonstrate an increased risk for combined thyroid disease, although non-ADSM adults had significantly increased rates of Grave’s disease, Hashimoto’s disease, hypothyroidism, and other thyroiditis. These results highlight that even in young, healthy populations like the ADSMs, COVID-19 can lead to long-term thyroid dysfunction.

Background: Post-COVID-19 conditions (PCCs) present a significant public health challenge due to a vast array of new or persistent health symptoms across subjects. The complex, multi-systemic nature of PCCs makes these conditions difficult to differentiate from other non-COVID-19 related medical conditions. While the Military Health System Data Repository (MDR) provides a robust supply of population-level encounter data, its high-dimensional structure poses challenges for knowledge discovery and outcome research. Objectives: The primary aim of this study was to identify novel manifestations of PCCs among active-duty service members, and model the probabilistic relationships between PCC-related diagnoses. We propose a machine learning workflow as an effective tool for knowledge discovery to statistically validate candidate PCCs from large datasets. Methods: We conducted a retrospective cohort study using MDR records from July 2018 to June 2023. From an initial pool of 311,367 eligible Active-Duty Tricare beneficiaries, we isolated 101,789 COVID-19 infections and matched them 1:1 with uninfected controls (N = 203,578 total) based on age, sex, and propensity for COVID-19. Encounter data was mapped to 392 clinical categories using the Healthcare Cost and Utilization Project (HCUP) Clinical Classification Software Refined (CCSR). Candidate PCC categories were isolated using a cross-validated lasso regression model optimized with a Tree of Parzen Estimators algorithm. A consensus Bayesian Network structure was fitted to model potential probabilistic dependency structures between identified PCCs and prior COVID-19 diagnosis. Finally, conditional Cox proportional hazards models were used to statistically validate selected novel conditions using larger cohorts drawn from the same initial eligible pool by matching cases 1:2 with controls. Results: Feature selection reduced the diagnosis set by 97.96%, isolating 8 clinical categories from the initial 392. The model confirmed known PCCs, such as respiratory symptoms and malaise, and identified two potentially novel candidate PCCs: tinnitus and personality disorders. Survival analysis validated the selection of tinnitus, showing a significant association with COVID-19 (HR: 1.17, 95% CI: 1.12–1.22). No significant association was found between COVID-19 infection and personality disorders (HR: 1.11, 95% CI: 0.97–1.26). Conclusions: This study demonstrates an effective analytical pathway for addressing the limitations of analyzing complex, high-dimensional healthcare billing data. The methodology successfully generated testable hypotheses, identifying tinnitus as a relevant sequela, and is generalizable to future research involving unknown health outcomes related to prior infection.

Background: The post-acute sequelae of SARS-CoV-2 infection represent a growing public health concern. While associations between COVID-19 and metabolic disorders have been reported, less is known about this risk in young, healthy populations. This study aimed to quantify the risk of developing new-onset metabolic disorders following SARS-CoV-2 infection among U.S. active-duty service members. Methods: We conducted a propensity score-matched cohort study using U.S. Military Health System data between July 2020 and June 2021 of active-duty service members (ADSM) aged 18 to 65 years old. COVID-19 infections were identified through ICD-10 codes or laboratory results. A 1:2 matched cohort compared 103,789 COVID-19 exposed individuals with 207,578 controls. Outcomes included incident diagnoses of type 2 diabetes mellitus (T2DM), hypertension (HTN), hyperlipidemia (HLD), metabolic dysfunction-associated steatotic liver disease (MASLD), and metabolic syndrome (MetS) within one year. Cox proportional hazards models calculated adjusted hazard ratios (aHR) while controlling for obesity and overweight status. Results: The median age for both those with and without COVID-19 infection was 26 years (interquartile range 22–33 years), with males comprising the majority of participants (81.1% male, 18.9% female). COVID-19 infection was associated with significantly increased hazards for incident HTN (aHR 1.09; 95% CI, 1.01–1.18), HLD (aHR 1.30; 95% CI, 1.10–1.54), and MASLD (aHR 1.36; 95% CI, 1.15–1.60). However, no significant increased risk was observed for T2DM or MetS. Conclusions: COVID-19 infection was associated with significantly increased risk of developing HTN, HLD, and MASLD, highlighting important long-term metabolic consequences in a young, healthy population.

Purpose To determine the effect the COVID-19 pandemic had on autism spectrum disorder (ASD) diagnosis in the Military Health System (MHS). Methods Repeated cross-sectional study utilized MHS Data Repository from JAN2018 to FEB2023. ASD encounters identified by ICD-10 diagnosis codes. Incident ASD encounters and overall visits were evaluated. Study included periods: Pre-COVID (PCo) (1/18 –2/20), COVID-19 Year (CoY) CoY1(3/20 –2/21), CoY2(3/21 –2/22) and CoY3(3/22 –2/23). Incident rates and overall visits were compared across time periods using Poisson regression, adjusting for sex, age group, region, and parent rank. Median age at first diagnosis across time periods were compared using generalized linear modeling. Results 2 million dependents ages 1–17 years were eligible for care over the study, with 44,508 incident ASD diagnoses (Table 1). ASD diagnosis incident rate decreased 10% in CoY1 vs. PCo (RR 0.90, 95% CI 0.87–0.93) and increased during CoY2 and CoY3 [RR2 1.21, 95% CI (1.18–1.24), RR3 1.50, 95% CI (1.46–1.54)]. CoY1-CoY3 vs. PCo all had statistically significant increased ASD visit rates (RR1 1.20, RR2 1.44, RR3 1.67). ASD diagnosis median age was 6 years (Table 1). Conclusion The incidence of ASD and related encounters decreased at the COVID-19 pandemic onset, highlighting the impact COVID-19 had on a delayed process within the MHS. The ASD incidence and encounters following the pandemic onset improved and continued to increase through CoY3. This uptrend suggests adaptation by providers during COVID-19 restrictions to use telehealth for developmental screening and ASD diagnosis.

Introduction: The COVID-19 pandemic challenged healthcare personnel worldwide. This study investigated the mental health of active duty military healthcare workers (HCWs) during the COVID-19 pandemic. Materials and Methods: We conducted a retrospective monthly cross-sectional analysis of active duty military enlisted and officer HCWs’ mental health encounter data from January 2018 to February 2023. Encounters for anxiety disorders, depressive disorders, reactive stress disorders, and suicidal attempt/ideation (SI) and self-harm were evaluated. Trends and trend changes in monthly rates of these 4 outcomes were evaluated using Joinpoint analysis. Poisson regression models evaluated the effect of time on the rates of these outcomes stratified by enlisted or officer status. Results: A total of 171,862 (122,413 enlisted, 49,449 officers) HCWs were included. Mental health utilization by both enlisted and officer HCWs had an upward trend for anxiety disorders, depressive disorders, reactive stress disorders, and suicidal attempt/SI and self-harm during the COVID-19 pandemic. Over the full study period, both enlisted and officer HCWs had significantly higher rates of all 4 outcomes in the second and third years of the pandemic. Female gender and older age were associated with higher rates across all outcomes, with the exception of SI and self-harm where the rates were higher among younger individuals. Discussion: Military healthcare providers experienced a significantly increased mental health burden during and following the COVID-19 pandemic. Females and older personnel were particularly vulnerable. These findings emphasize the need for targeted interventions to support these critical personnel during and after crises, such as resiliency training, peer support, and readily accessible mental healthcare services.

Introduction: Long COVID, also known as Post–COVID-19 Condition (PCC) is characterized by the persistence or development of symptoms following SARS-CoV-2 infection. Post–COVID-19 Condition has the potential to impact military readiness, and yet the incidence among active duty service members (ADSM) is unknown. The objective of this study is to assess the incidence of diagnosed PCC, explore demographic associations, and identify common co-occurring diagnoses among ADSM. Materials and Methods: We conducted a repeated cross-sectional study using the Military Health System Data Repository (MDR). The MDR was queried for care records containing the ICD-10 code for PCC, U09.9, from October 2021 to October 2022. Incidence was calculated using the monthly counts, although Incidence Rate Ratios were calculated using a Poisson regression model, adjusting for age, sex, rank, race/ethnicity, and region. The frequency of co-occurring diagnoses with PCC encounters was analyzed to identify the top co-occurring diagnoses. Results: A total of 7,171 ADSM were diagnosed with PCC. The average monthly incidence of PCC was 4.7 per 10,000 ADSM. Females had 3.70 times (95% CI, 3.50-3.90) the adjusted incident rate ratio (aIRR) of PCC compared to males. Active duty service members aged 55-64 had the greatest risk with an aIRR of 28.81 (95% CI, 20.81-38.75) compared to ADSM aged 17-24. The highest frequency co-occurring diagnoses were respiratory signs and symptoms, with 874 diagnosed with R06.02 (shortness of breath). Conclusion: Post–COVID-19 Condition represents a significant burden on the health of ADSM. Further research is warranted to study trends of PCC among the ADSM and to assess the effect of PCC on readiness and retention.

Background/Objectives: Rotavirus gastroenteritis is a vaccine-preventable disease that leads to hospitalization in children less than 5 years of age. Immunizations to prevent rotavirus have greatly altered the epidemiology of significant diarrheal illness. It has been reported that routine immunization rates in children were impacted during the COVID-19 pandemic. Contrary to this fact, rates of many childhood illnesses also decreased. Methods: The Military Health System Data Repository (MDR) contains the health records of all military beneficiaries. We queried the MDR before and during the COVID-19 pandemic to assess for alterations in immunization rates and hospitalization rates and to assess for risk factors for significant (hospitalizations) rotavirus disease. Results: Our study included a cohort of 1.27 million children under the age of 5 years old. There were 186 unique cases of rotavirus-related hospitalizations over the 5-year study period. During COVID-19 Years 1 and 2, there was a decrease in rotavirus-related hospitalizations compared to the pre-pandemic period. During Year 3, there was a return to the pre-pandemic level of rotavirus hospitalization rates. Patients in the northern United States were less likely to be hospitalized from rotavirus when compared to those in the south. The patients at greatest risk were the youngest beneficiaries. Rotavirus vaccination rates declined in this age group during all three years of the pandemic. Conclusions: As the pandemic resulted in less frequent rotavirus immunizations in the Military Health System (MHS), there was not an increase in rotavirus-related hospitalizations above the pre-pandemic baseline.

The COVID-19 pandemic had a significant impact on the physical and mental health of all age groups. While many studies have evaluated the serious cardiac manifestation associated with multisystem inflammatory syndrome of children, there are less studies evaluating how the COVID-19 pandemic impacted the presentation of less severe symptomatic cardiac manifestations. This large retrospective cross-sectional study examined the impact of the COVID-19 pandemic on the cardiovascular health of patients 1 to 24 years of age by assessing care presentation trends for chest pain, palpitations, and syncope for patients in the military health system. Overall, chest pain had the highest rate of presentation when compared to syncope and palpitations. There was a significant decrease in the rate of incidence for all three cardiac symptoms during the first year of the COVID-19 pandemic compared to the pre-COVID-19 period. When comparing the second year of the COVID-19 pandemic to the pre-COVID-19 period, there was a significant decrease in chest pain and syncope but a slight increase in palpitations. Overall, our results showed that these common cardiac presentations did not greatly increase during the COVID-19 pandemic.