Skip to main content
OpenTrials
Recruiting

NCT Number: NCT07292857

Comparing and Predicting the Risk of Respiratory Tract Infection (RTI) Among Post-menopausal Women on or Without Hormone Replacement Therapy (HRT): an Observational Cohort Study

Background: Respiratory tract infections (RTIs) are a major public health concern. Global studies published in Lancet Infect. Dis. highlight the persistent morbidity and mortality from RTIs, with upper- and lower-RTIs collectively accounting for more than 100 million disability-adjusted-life-years per year.

During menopause, hormonal changes alongside other factors increase the risk for illnesses, such as RTIs, COPD, cardiovascular disease, and diabetes. However, it remains unknown how hormone-replacement therapy during menopause might impact the frequency or severity of RTIs. While hormone replacement therapy (HRT) is often prescribed for menopausal symptom relief, its potential impact on RTI risk and severity has not been examined.

Objective: This observational cohort study aims to compare and predict the risk of RTI among postmenopausal women, with a particular focus on the influence of HRT. The principal aim is to compare the rates and severity of respiratory tract infections in postmenopausal women taking or not taking HRT. The secondary aims are to characterize risk factors for RTI in postmenopausal women and identify signals in wearable data that predict the onset of an RTI before symptoms become apparent.

Methods: 400 women aged 40-60 will be studied, stratified into two groups: postmenopausal women taking HRT, and postmenopausal women not taking HRT. Participants will each be followed for six months, with RTI episodes recorded through self-reporting and confirmed by laboratory tests. Wearable devices will continuously monitor physiological parameters (e.g., heart rate, sleep patterns), and questionnaires will assess lifestyle factors, medical history, and environmental exposure. Statistical modeling and machine learning approaches will be used to analyze infection predictors and develop a model that predicts the risk of onset of an RTI.

Impact: Half of the world's population inevitably undergoes menopause, and this important life transition has wide-ranging impacts on women's health and quality of life for decades. Studies show that women spend more of their lives in poor health than men, with far-reaching impacts on a woman's participation in society, career performance, and ability to care for other family members. A better understanding of risk factors for respiratory infections in menopausal women and whether hormone-replacement therapy influences RTIs will contribute much-needed knowledge to enable better health management strategies for women. Furthermore, an "early-warning" system based on wearable signals will provide a valuable tool for quick intervention and to reduce the spread of infectious illnesses. Such an "early-warning" system will subsequently be tested for applicability across a broader representation of society as a preventive health measure and tool for pandemic preparedness.

Conclusion: Findings will enhance understanding of RTI risk and management in menopausal women and contribute to the development of personalized prevention strategies. Future applications include a wearable-based medical device for real-time RTI risk assessment, potentially reducing antibiotic overuse and improving healthcare efficiency. By enabling early detection and risk stratification, this study paves the way for a proactive and personalized approach to respiratory health in postmenopausal women, ultimately shifting the focus to prevention.

Recruiting

Interested in participating?

Request Info

Key information

Conditions

Menopausal Women Infections Respiratory Tract Diseases Respiratory Tract Infections Respiratory Tract Infections (RTI)

Age range

40 year–60 year

Sex eligibility

Female

Study type

Observational

Primary location

University Hospital of Bern, Department of Gynecological Endocrinology & Reproductive Medicine

Bern, 3010, Switzerland

Location status: Recruiting

Location contact

Petra Stute, Prof. Dr. med.

CONTACT

[email protected]

+41 31 632 1010

Petra Stute, Prof. Dr. med.

PRINCIPAL_INVESTIGATOR

Who can participate

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Biological sex: female
  • Age: 40-60 years
  • Self-determined decision to participate, confirmed by signing the informed consent form (ICF)
  • Fluent in German
  • Agreement to wear a smartwatch (Garmin Vivosmart 5) for most of the time over six months
  • Ownership of a smartphone compatible with the Fitrockr application
  • Confirmed post-menopausal status: Spontaneous amenorrhea for ≥12 consecutive months without other causes OR ≥6 months of spontaneous amenorrhea with biochemical confirmation (FSH > 40 IU/L OR FSH > 30 IU/L for women aged ≥50 using hormonal contraception) OR bilateral oophorectomy ≥6 weeks before enrollment

Exclusion criteria

  • Inability to provide informed consent
  • Known allergic reaction to polycarbonate (smartwatch wristband material)
  • Asthma not well-controlled (ACT score <20 despite medication)
  • Use of injectable asthma drugs with broad immunomodulatory activity
  • Coronary artery disease
  • Diagnosis of diabetes mellitus
  • Cancer diagnosis
  • Diagnosis of chronic kidney disease
  • Confirmed diagnosis of familial hypercholesterolemia (genetic)
  • Sleep apnea managed with bi-level positive airway pressure (PAP)
  • Chronic rhinosinusitis
  • Severe (stage 3 or 4) chronic obstructive pulmonary disease (COPD) or interstitial lung disease with hospitalization within the prior 12 months for respiratory symptoms
  • Any other condition/treatment deemed incompatible with the study objectives by the PI or delegated co-investigators
  • Current employment in the Section of Gynecological Endocrinology and Reproductive Medicine (Inselspital Bern) or any other relation to the principal investigator
  • Concurrent participation in a clinical interventional study
  • Technical inability to pair the participant's smartphone with the smartwatch
  • Inability to comply with study procedures (e.g., due to language, psychiatric illness, or inability to attend study site)

Treatment and study plan

Primary outcomes

  1. Number of Respiratory Tract Infection (RTI) Episodes per Participant Over 6 Months

    Time frame: 6 months from enrollment (per participant)

    Count of RTI episodes per participant during the 6-month observation period.

    An RTI episode is defined as the period beginning with participant-reported symptom onset and ending when:

    • all symptoms return to baseline, or
    • a maximum of 10 days of residual symptoms has elapsed.

    Symptom presence is documented via daily responses to the Wisconsin Upper Respiratory Symptoms Survey-21 (WURSS-21).

  2. Cumulative Symptom Severity Score of All RTI Episodes Over 6 Months

    Time frame: 6 months from enrollment (per participant)

    Cumulative RTI severity, calculated as the sum of daily WURSS-21 scores across all RTI episodes occurring during the 6-month observation period.

    The WURSS-21 (Wisconsin Upper Respiratory Symptom Survey-21) is a validated instrument containing 21 items scored from 0 to 7 each:

    • 0 = "not at all" (no symptom / no functional impact)
    • 7 = "severe" Higher scores indicate worse symptoms and greater functional impairment.

    Per-episode scoring begins on the first day of participant-reported symptom onset and continues until resolution or up to 10 days of persistent residual symptoms.

Secondary outcomes

  1. Daily Individual Probability of Respiratory Tract Infection (RTI) Onset Based on Integrated Participant-Level and Environmental Data

    Time frame: 6 months after enrollment (per participant)

    For each participant and each study day, a continuous RTI-risk probability (unit: probability, 0-1) will be generated by statistical/machine-learning models.

    Predictors include:

    • wearable-derived physiological parameters (resting heart rate, respiration rate, sleep phase durations, step count, stress index)
    • questionnaire-derived behavioral, psychosocial, medical, and social variables
    • laboratory-measured biological variables (e.g., hormone concentrations, in original units) environmental/epidemiological variables (temperature [°C], humidity [%], PM10 [µg/m³], circulating respiratory viruses detected in national surveillance).

    Unit of Measure: Probability (0-1) per participant per day.

  2. Correlation Between Participant-Level Characteristics and Number of RTI Episodes

    Time frame: Time Frame: 6 months after enrollment (per participant)

    The RTI count is defined as the number of RTI episodes per participant over 6 months, as ascertained through:

    • daily WURSS-21 reporting,
    • Jackson-scale symptom onset rules,
    • nasal swab confirmation when available.

    For each participant characteristic (predictor), the association will be quantified via regression coefficients from generalized linear models with Poisson distribution.

    Predictors include:

    • biological measures (e.g., hormone concentrations, in pg/mL or IU/L),
    • medical history variables (binary/continuous),
    • psychosocial questionnaire scales (e.g., PHQ-9 score, 0-27),
    • lifestyle/behavior measures (sleep duration from wearable, minutes/day; step - count/day; stress index score 1-100),
    • social context variables (household size: number of cohabitants).

    Unit of Measure: Regression coefficient (unitless) per predictor describing effect on RTI count.

  3. Correlation Between Participant-Level Characteristics and Cumulative RTI Severity

    Time frame: 6 months after enrollment (per participant)

    Cumulative RTI severity is defined as the sum of daily WURSS-21 scores (range 0-140 per day) across all RTI days during the 6-month observation period.

    Associations with participant characteristics will be quantified as regression coefficients from generalized linear models assuming a Tweedie compound-Poisson distribution.

    Predictor variables and measurement tools (same categories as 4):

    • hormone concentrations (IU/L or pg/mL),
    • medical history variables,
    • psychosocial scales (PHQ-9),
    • lifestyle/behavior variables (sleep, steps, stress index),
    • social context variables (household size).

    Unit of Measure: Regression coefficient (unitless) per predictor describing effect on cumulative WURSS-21 severity score.

  4. Aggregate Pre-Symptomatic Deviation of Physiological and Questionnaire-Derived Signals During the 14 Days Prior to RTI Symptom Onset

    Time frame: 6 months after enrollment (per participant)

    For each confirmed RTI episode, wearable-derived parameters and weekly questionnaire variables will be evaluated in the 14 days preceding the first reported RTI symptoms (WURSS-21 start date).

    The following raw indicators will be extracted but converted into standardized deviations relative to each participant's personal 30-day baseline (unit: z-score, unitless):

    • resting heart rate (beats/min),
    • respiration rate (breaths/min),
    • sleep structure (minutes in REM/light/deep),
    • stress index (1-100 score),
    • step count (steps/day),
    • participant-reported stress level (Likert scale),
    • sleep quality (Likert scale),
    • lifestyle behaviors (binary/ordinal). These will be aggregated into one composite pre-symptomatic deviation score, calculated as the mean z-standardized deviation of all included signals across the 14-day pre-onset window.

    Unit of Measure: Composite standardized deviation score (unitless z-score).

Study contacts

Contact information is provided by the study sponsor or research team.

Petra Stute, Prof. Dr. med.

CONTACT

[email protected]

+41 31 632 1010

Sponsors and collaborators

Lead sponsor

Insel Gruppe AG, University Hospital Bern

Other

Registry information

Official study title

Comparing and Predicting the Risk of Respiratory Tract Infection (RTI) Among Post-menopausal Women on or Without Hormone Replacement Therapy (HRT): an Observational Cohort Study (Meno_Flu)

Acronym: Meno_Flu

Important dates

Study start
2024
Primary completion
2025
Study completion
2026
First posted
Dec 18, 2025
Registry last updated
Dec 18, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Related clinical trials

Published trials that share one or more normalized conditions with this study.