Tag: comorbidities

The effect of comorbid medical diagnoses on disturbed sleep in chronic fatigue syndrome

Abstract:

Background: Chronic fatigue syndrome [CFS] may occur alone or with fibromyalgia. This has led some to believe the two occur along a common illness spectrum. Evaluating whether this is the case is important as differences in burden or severity of CFS with fibromyalgia (FM) would suggest different underlying pathophysiological processes.

Objective: To determine if Insomnia Severity Index [ISI] scores differ between patients with CFS and those with CFS plus FM. In addition, we aim to determine if insomnia severity is impacted by other comorbid medically unexplained diagnoses.

Methods: 247 patients with CFS completed the ISI and the Centers for Epidemiological Study – Depression. Patient groups were stratified on CFS severity and the presence of FM. A secondary analysis was conducted to evaluate insomnia severity related to the number of comorbid medically unexplained diagnoses including, FM, multiple chemical sensitivity and/or irritable bowel syndrome.

Results: When controlling for depressed mood, ISI did not differ significantly across patient groups defined by CFS severity and FM status. However, independent of mood, ISI was sensitive to multiple diagnoses showing a significant increasing trend from CFS alone to CFS plus one, two or three comorbid diagnoses.

Conclusion: Although CFS severity and FM status do not impact insomnia severity, increased illness burden as manifested by multiple medically unexplained diagnoses does appear to influence insomnia. In contrast to our earlier studies, this study did not find that a comorbid diagnosis of FM in patients with CFS is related to a worse outcome in the variable of interest.

Source: Aaron J. Stegner, Michelle Blate & Benjamin H. Natelson (2024) The effect of comorbid medical diagnoses on disturbed sleep in chronic fatigue syndrome, Fatigue: Biomedicine, Health & Behavior, DOI: 10.1080/21641846.2024.2322915 https://www.tandfonline.com/doi/full/10.1080/21641846.2024.2322915

Unraveling Links between Chronic Inflammation and Long COVID: Workshop Report

As COVID-19 continues, an increasing number of patients develop long COVID symptoms varying in severity that last for weeks, months, or longer. Symptoms commonly include lingering loss of smell and taste, hearing loss, extreme fatigue, and “brain fog.” Still, persistent cardiovascular and respiratory problems, muscle weakness, and neurologic issues have also been documented. A major problem is the lack of clear guidelines for diagnosing long COVID. Although some studies suggest that long COVID is due to prolonged inflammation after SARS-CoV-2 infection, the underlying mechanisms remain unclear.

The broad range of COVID-19’s bodily effects and responses after initial viral infection are also poorly understood. This workshop brought together multidisciplinary experts to showcase and discuss the latest research on long COVID and chronic inflammation that might be associated with the persistent sequelae following COVID-19 infection.

Source: Pushpa Tandon, Natalie D. Abrams, Leela Rani Avula, Danielle M. Carrick, Preethi Chander, Rao L. Divi, Johanna T. Dwyer, Gallya Gannot, Nataliya Gordiyenko, Qian Liu, Kyung Moon, Mercy PrabhuDas, Anju Singh, Mulualem E. Tilahun, Merriline M. Satyamitra, Chiayeng Wang, Ronald Warren, Christina H. Liu; Unraveling Links between Chronic Inflammation and Long COVID: Workshop Report. J Immunol 15 February 2024; 212 (4): 505–512. https://doi.org/10.4049/jimmunol.2300804 https://journals.aai.org/jimmunol/article/212/4/505/266648 (Full text)

Advancing Research and Treatment: An Overview of Clinical Trials in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and Future Perspectives

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic, debilitating, and multi-faceted illness. Heterogenous onset and clinical presentation with additional comorbidities make it difficult to diagnose, characterize, and successfully treat. Current treatment guidelines focus on symptom management, but with no clear target or causative mechanism, remission rates are low, and fewer than 5% of patients return to their pre-morbid activity levels. Therefore, there is an urgent need to undertake robust clinical trials to identify effective treatments.
This review synthesizes insights from clinical trials exploring pharmacological interventions and dietary supplements targeting immunological, metabolic, gastrointestinal, neurological, and neuroendocrine dysfunction in ME/CFS patients which require further exploration. Additionally, the trialling of alternative interventions in ME/CFS based on reported efficacy in the treatment of illnesses with overlapping symptomology is also discussed. Finally, we provide important considerations and make recommendations, focusing on outcome measures, to ensure the execution of future high-quality clinical trials to establish clinical efficacy of evidence-based interventions that are needed for adoption in clinical practice.
Source: Seton KA, Espejo-Oltra JA, Giménez-Orenga K, Haagmans R, Ramadan DJ, Mehlsen J on behalf of the European ME Research Group for Early Career Researchers (Young EMERG). Advancing Research and Treatment: An Overview of Clinical Trials in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and Future Perspectives. Journal of Clinical Medicine. 2024; 13(2):325. https://doi.org/10.3390/jcm13020325 https://www.mdpi.com/2077-0383/13/2/325 (Full text)

Severe mental illness, race/ethnicity, multimorbidity and mortality following COVID-19 infection: nationally representative cohort study

Abstract:

Background: The association of COVID-19 with death in people with severe mental illness (SMI), and associations with multimorbidity and ethnicity, are unclear.

Aims: To determine all-cause mortality in people with SMI following COVID-19 infection, and assess whether excess mortality is affected by multimorbidity or ethnicity.

Method: This was a retrospective cohort study using primary care data from the Clinical Practice Research Database, from February 2020 to April 2021. Cox proportional hazards regression was used to estimate the effect of SMI on all-cause mortality during the first two waves of the COVID-19 pandemic.

Results: Among 7146 people with SMI (56% female), there was a higher prevalence of multimorbidity compared with the non-SMI control group (n = 653 024, 55% female). Following COVID-19 infection, the SMI group experienced a greater risk of death compared with controls (adjusted hazard ratio (aHR) 1.53, 95% CI 1.39-1.68). Black Caribbean/Black African people were more likely to die from COVID-19 compared with White people (aHR = 1.22, 95% CI 1.12-1.34), with similar associations in the SMI group and non-SMI group (P for interaction = 0.73). Following infection with COVID-19, for every additional multimorbidity condition, the aHR for death was 1.06 (95% CI 1.01-1.10) in the SMI stratum and 1.16 (95% CI 1.15-1.17) in the non-SMI stratum (P for interaction = 0.001).

Conclusions: Following COVID-19 infection, patients with SMI were at an elevated risk of death, further magnified by multimorbidity. Black Caribbean/Black African people had a higher risk of death from COVID-19 than White people, and this inequity was similar for the SMI group and the control group.

Source: Das-Munshi J, Bakolis I, Bécares L, Dyer J, Hotopf M, Ocloo J, Stewart R, Stuart R, Dregan A. Severe mental illness, race/ethnicity, multimorbidity and mortality following COVID-19 infection: nationally representative cohort study. Br J Psychiatry. 2023 Nov;223(5):518-525. doi: 10.1192/bjp.2023.112. PMID: 37876350; PMCID: PMC7615273. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615273/ (Full text)

Predictive models of long COVID

Abstract:

Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future.

Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models – logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741).

Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75.

Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

Source: Antony B, Blau H, Casiraghi E, Loomba JJ, Callahan TJ, Laraway BJ, Wilkins KJ, Antonescu CC, Valentini G, Williams AE, Robinson PN, Reese JT, Murali TM; N3C consortium. Predictive models of long COVID. EBioMedicine. 2023 Oct;96:104777. doi: 10.1016/j.ebiom.2023.104777. Epub 2023 Sep 4. PMID: 37672869; PMCID: PMC10494314. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494314/ (Full text)

Prevalence and Predictive Factors of Small Intestinal Bacterial Overgrowth in Patients With Chronic Fatigue Syndrome

Introduction: Chronic fatigue syndrome (CFS) is a poorly understood illness, characterized by fatigue and related symptoms including cognitive dysfunction, headaches, joint pains, and gastrointestinal distress. Irritable bowel syndrome (IBS) is common and present in approximately 60% patients with CFS while the prevalence of small intestinal bacterial overgrowth (SIBO) in IBS is approximately 40%. Our study aimed to 1) Determine the prevalence of SIBO in patients with CFS with and without IBS symptoms 2) Identify factors associated with increased risk of SIBO.

Methods: A retrospective chart review of 479 patients with CFS referred for hydrogen/methane breath testing. Clinical documentation was reviewed to identify positive breath test result diagnosing SIBO. Statistical analysis was conducted with 2-proportions z test and logistic regression analysis to identify predictive variables of SIBO diagnosis.

Results: 479 patients with CFS referred for glucose or lactulose breath testing were identified. Three hundred sixty-seven of those patients completed a breath test with available result: 152(41%) SIBO+ (mean age (SD) 50 (17)), 164(45%) SIBO- (mean age SD 46 (15)), and 78(21%) equivocal results. In CFS patients with conclusive breath test result, 48% tested positive for SIBO, and the diagnosis of IBS was present in 186/316 (59%). There was no difference in the prevalence of IBS between the SIBO+ vs SIBO-group [98/152 (64%) vs 88/164 (53%), P < 0.05]. Using multiple logistic regression analysis, age, unknown race, and IBS diagnosis all significantly predicted increased odds of having a positive breath test (Table 1). Conversely, PPI use was associated with decreased odds of a positive breath test. Due to the high prevalence of IBS in our cohort and the association between IBS and SIBO, an analysis was performed excluding patients with IBS diagnosis. When excluding patients with IBS, unknown race and TCA use were associated with increased odds of positive breath test, while diarrhea, hypothyroidism, PPI, and naltrexone use were associated with decreased odds (P< 0.05).

Conclusion: SIBO is highly prevalent in patients with CFS referred for breath testing. Older age and comorbid IBS diagnosis predict increased odds of positive breath test. Surprisingly, PPI use predicted decreased odds despite its prior implication as a possible risk factor for SIBO. Further studies are needed to explore the underlying mechanism causing the overlap between CFS, IBS and SIBO which may provide insights into potential therapies for CFS.

Source: Karhu, Elisa MD, MS; Neshatian, Leila MD, MS; Fass, Ofer MD; Sonu, Irene MD; Nguyen, Linda Anh MD. S1821 Prevalence and Predictive Factors of Small Intestinal Bacterial Overgrowth in Patients With Chronic Fatigue Syndrome. The American Journal of Gastroenterology 118(10S):p S1351-S1352, October 2023. | DOI: 10.14309/01.ajg.0000956924.26236.c4 https://journals.lww.com/ajg/fulltext/2023/10001/s1821_prevalence_and_predictive_factors_of_small.2162.aspx

Fatigue, chronic fatigue syndrome and migraine: Intersecting the lines through a cross-sectional study in patients with episodic and chronic migraine

Abstract:

Objectives: Fatigue is a common symptom occurring in a variety of disorders. Chronic fatigue syndrome (CFS) is characterized by debilitating fatigue as the core symptom. The risk of CFS is nearly 1.5 times higher in migraine while headaches have been reported in 59% of cases with CFS. However, details of its occurrence and severity remain largely unexplored.

The primary objective of our study was to determine the occurrence and severity of fatigue and CFS in patients with episodic and chronic migraine. The secondary objectives were to define their relationship with other common comorbidities.

Materials and methods: 60 migraine patients (30 each, episodic [EM] and chronic migraine [CM]) were recruited from Neurology Outpatient Department, GIPMER a tertiary referral center in New Delhi, India. Patients’ headache severity was analyzed using the Headache impact test-6 (HIT-6) score while fatigue and other migraine accompaniments were assessed using Fatigue severity scale (FSS), Chalder fatigue scale, CDC diagnostic criteria for CFS, American College of Rheumatology Diagnostic Criteria for fibromyalgia, Hamilton Depression Scale, the Generalized Anxiety Disorder 7-Item Scale, and Epworth sleepiness Scale (ESS). Comparative analysis was further done among migraine patients with and without fatigue and CFS.

Results: The mean HIT-6 score was significantly higher in CM versus EM. The CM group had a higher mean FSS score (47.87 vs. 37.3 in EM; P = 0.004), a percentage of patients with severe fatigue (60% vs. 20% in EM; P = 0.004), and a higher percentage of patients with pathological fatigue (83.3% vs. 63.3% in EM; P = 0.04). Around 23.33% of CM patients fulfilled the criteria of CFS. Fatigue correlated positively with severity, frequency, attack duration and chronicity of the migraine episodes, along with depression, anxiety, and excessive daytime sleepiness.

Conclusion: Fatigue and related comorbid disorders are significantly more common in CM than in EM, expanding the morbidity of the condition and underscores the need to address these accompanying symptoms for devising a holistic treatment plan.

Source: Kumar H, Dhamija K, Duggal A, Khwaja GA, Roshan S. Fatigue, chronic fatigue syndrome and migraine: Intersecting the lines through a cross-sectional study in patients with episodic and chronic migraine. J Neurosci Rural Pract. 2023 Jul-Sep;14(3):424-431. doi: 10.25259/JNRP_63_2022. Epub 2023 Apr 20. PMID: 37692810; PMCID: PMC10483198. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483198/ (Full text)

Coronavirus (COVID-19) Pandemic – A Comprehensive Review of Demographics, Comorbidities, Vaccines, Therapeutic Development, Blood Type, and Long Covid

Abstract:

The study summarizes the pandemic COVID-19’s impact on symptoms, demographics, comorbidities, and vaccine and therapeutic development and demonstrates an association with cases and mortality for the past two years. There has been rapid scientific advancement over the past two years 2020-2022 in developing vaccines and therapeutics for combating the disease. We chose three highly affected countries US, India, and China, to address the impact of demographics and comorbidities on COVID-19 using US Center for Disease Control and Prevention (CDC) data.

Based on the analysis of this data, we see that the infection rate is higher in females, while the percentage of death is higher in males than females (p < 0.0001), and the number of female cases among females has increased by 1.7% while the number of deaths among females has decreased by ~1%, within the last two years. The trend of getting affected byCOVID-19 is similar during 2020-2022, i.e., Whites followed by Hispanics and Black people.

After a thorough review of many manuscripts, we concluded that diseases like cardiovascular disease (CVD), diabetes, hypertension, chronic pulmonary obstructive disease (COPD), and acute respiratory distress syndrome (ARDS) were the typical comorbidities leading to severe COVID-19 conditions. In addition, variants of COVID-19, current vaccine and therapeutic development efforts, and relation of COVID-19 with blood type are discussed.

Finally, to conclude that for designing vaccine trials, following FDA’s guidance emphasizing stratification factors based on demographics and comorbidities should be considered while allocating treatment to patients.

Source: Bhattacharyya, Arinjita & Seth, Anand & Rai, Shesh. (2023). Coronavirus (COVID-19) Pandemic -A Comprehensive Review of Demographics, Comorbidities, Vaccines, Therapeutic Development, Blood Type, and Long Covid. 10.36959/856/540.  https://www.researchgate.net/profile/Arinjita_Bhattacharyya/publication/369579104_Coronavirus_COVID-19_Pandemic_-A_Comprehensive_Review_of_Demographics_Comorbidities_Vaccines_Therapeutic_Development_Blood_Type_and_Long_Covid/links/6423001ba1b72772e4318d7d/Coronavirus-COVID-19-Pandemic-A-Comprehensive-Review-of-Demographics-Comorbidities-Vaccines-Therapeutic-Development-Blood-Type-and-Long-Covid.pdf (Full text PDF file)

Thrombophilia and Immune-Related Genetic Markers in Long COVID

Abstract:

Aiming to evaluate the role of ten functional polymorphisms in long COVID, involved in major inflammatory, immune response and thrombophilia pathways, a cross-sectional sample composed of 199 long COVID (LC) patients and a cohort composed of 79 COVID-19 patients whose follow-up by over six months did not reveal any evidence of long COVID (NLC) were investigated to detect genetic susceptibility to long COVID.
Ten functional polymorphisms located in thrombophilia-related and immune response genes were genotyped by real time PCR. In terms of clinical outcomes, LC patients presented higher prevalence of heart disease as preexistent comorbidity. In general, the proportions of symptoms in acute phase of the disease were higher among LC patients.
The genotype AA of the interferon gamma (IFNG) gene was observed in higher frequency among LC patients (60%; p = 0.033). Moreover, the genotype CC of the methylenetetrahydrofolate reductase (MTHFR) gene was also more frequent among LC patients (49%; p = 0.045). Additionally, the frequencies of LC symptoms were higher among carriers of IFNG genotypes AA than among non-AA genotypes (Z = 5.08; p < 0.0001).
Two polymorphisms were associated with LC in both inflammatory and thrombophilia pathways, thus reinforcing their role in LC. The higher frequencies of acute phase symptoms among LC and higher frequency of underlying comorbidities might suggest that acute disease severity and the triggering of preexisting condition may play a role in LC development.
Source: da Silva R, de Sarges KML, Cantanhede MHD, da Costa FP, dos Santos EF, Rodrigues FBB, de Nazaré do Socorro de Almeida Viana M, de Meira Leite M, da Silva ALS, de Brito MTM, da Silva Torres MK, Queiroz MAF, Vallinoto IMVC, Henriques DF, dos Santos CP, Viana GMR, Quaresma JAS, Falcão LFM, Vallinoto ACR, dos Santos EJM. Thrombophilia and Immune-Related Genetic Markers in Long COVID. Viruses. 2023; 15(4):885. https://doi.org/10.3390/v15040885 https://www.mdpi.com/1999-4915/15/4/885 (Full text)

What is the impact of post-COVID-19 syndrome on health-related quality of life and associated factors: a cross-sectional analysis

Abstract:

Background: After the acute phase, symptoms or sequelae related to post-COVID-19 syndrome may persist for months. In a population of patients, previously hospitalized and not, followed up to 12 months after the acute infection, we aim to assess whether and to what extent post-COVID-19 syndrome may have an impact on health-related quality of life (HRQoL) and to investigate influencing factors.

Methods: We present the cross-sectional analysis of a prospective study, including patients referred to the post-COVID-19 service. Questionnaires and scales administered at 3, 6, 12 months were: Short-Form 36-item questionnaire (SF-36); Visual Analogue Scale of the EQ5D (EQ-VAS); in a subgroup, Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI-II) and Pittsburgh Sleep Quality Index (PSQI). Linear regression models were fitted to identify factors associated with HRQoL.

Results: We considered the first assessment of each participant (n = 572). The mean scores in SF-36 and in EQ-VAS were significantly lower than the Italian normative values and remained stable over time, except the mental components score (MCS) of the SF-36 and EQ-VAS which resulted in lower ratings at the last observations. Female gender, presence of comorbidities, and corticosteroids treatment during acute COVID-19, were associated with lower scores in SF-36 and EQ-VAS; patients previously hospitalized (54%) reported higher MCS. Alterations in BAI, BDI-II, and PSQI (n = 265)were associated with lower ratings in SF-36 and EQ-VAS.

Conclusions: This study provides evidence of a significantly bad perception of health status among persons with post-COVID-19 syndrome, associated with female gender and, indirectly, with disease severity. In case of anxious-depressive symptoms and sleep disorders, a worse HRQoL was also reported. A systematic monitoring of these aspects is recommended to properly manage the post-COVID-19 period.

Source: Mastrorosa I, Del Duca G, Pinnetti C, Lorenzini P, Vergori A, Brita AC, Camici M, Mazzotta V, Baldini F, Chinello P, Mencarini P, Giancola ML, Abdeddaim A, Girardi E, Vaia F, Antinori A. What is the impact of post-COVID-19 syndrome on health-related quality of life and associated factors: a cross-sectional analysis. Health Qual Life Outcomes. 2023 Mar 22;21(1):28. doi: 10.1186/s12955-023-02107-z. PMID: 36949439; PMCID: PMC10031164. https://hqlo.biomedcentral.com/articles/10.1186/s12955-023-02107-z (Full text)