Impact of Advanced Crohn's Disease Therapies on Sleep Quality

The goal of this observational study is to measure changes in sleep quality before and after starting treatment with advance therapy in adult with Crohn disease. The main question it aims to answer is: what is the association between response to therapy and sleeping patterns? Participants who are about to begin advanced treatment will be asked to wear a Fitbit device before end after treatment initiation to monitor sleep patterns and sleep quality, complete a sleep diary and a sleep quality questionnaire. The follow-up period will last 26 weeks, during which disease severity and response to treatment will be assessed.

Study Overview

• Status: Recruiting
• Conditions: Crohn Disease (CD)
• Intervention / Treatment: Other: Wearable activity and sleep tracker

Detailed Description

Inflammatory bowel diseases (IBD) are chronic inflammatory diseases with a relapsing remitting course. The pathogenesis of the disease is hypothesized to be abnormal host immune response to the gut microbiota, triggered by dietary, environmental or stress factors in genetically predisposed individuals. Despite the significant medical progress with the advent of therapy (e.g., TNF, integrin and cytokine inhibitors, jak inhibitors and S1P receptor modulators) there are still many caveats in the treatment of patients with IBD, including loss of response, immunogenicity, immunosuppression and side effects. Furthermore, although current therapies improve health associated quality of life, there is still unmet gap in this area with high rates of disability, sleep disturbances, fatigue, pain and other quality of life domains.

Sleep and circadian rhythm disorders effect the immune system function and are a potential cause of disease flare-ups, which in turn effect sleep pattern and quality, creating a vicious cycle. The interactions between sleep and inflammation are complex. An effective immune system affects sleep, and sleep disorders affect the functioning of the immune system. Patients with sleep disorders showed increase in inflammatory activity. However, it is difficult to dissect the cause and effect for these associations, given their complex interactions.

Studies identified several risk factors associated with sleep disorders in patients with IBD. These include depression, anxiety, active disease, older age (>52 years), CD duration (>12 years), low hemoglobin levels (<12 g/dL), elevated C-reactive protein (CRP), current corticosteroid use, ongoing anti-TNF therapy, opioid use, and smoking.

Previous studies on the association of sleep abnormalities and IBD relied on self-assessment questionnaires, such as the Pittsburgh Sleep Quality Index (PSQI), which are inherently subjective measures of sleep quality. In this study, the investigators will use the Fitbit Inspire 3 to objectively assess sleep quality, leveraging its ability to track sleep duration and stages.

Sleep is a vital physiological process encompassing two primary modes: Non-Rapid Eye Movement (NREM) and Rapid Eye Movement (REM) sleep. NREM sleep, divided into stages N1, N2, and N3. In N1, the body starts to relax; N2 brings deeper relaxation with a slower heart rate; and in N3, the deepest stage. REM sleep, characterized by vivid dreaming and heightened brain activity similar to wakefulness, is essential for cognitive functions like memory consolidation, emotional processing, and learning. Throughout the night, individuals cycle through NREM and REM phases, each contributing uniquely to physical and mental well-being, underscoring the importance of quality sleep for overall health.

Sleep stages can be estimated by monitoring heart rate, which slows progressively from light to deep sleep and fluctuates in REM, as well as movement, which decreases in deep sleep and is minimal in REM due to muscle paralysis. The Fitbit Inspire 3 measures sleep by combining motion sensing, using a 3-axis accelerometer, with heart rate variability (HRV) analysis. The device tracks subtle movements to identify periods of rest versus wakefulness, while HRV data helps estimate sleep stages based on distinct heart rate patterns during light, deep, and REM sleep. Together, these inputs allow Fitbit's algorithm to approximate sleep stages, providing insights into sleep quality and cycles for everyday health tracking, though not as precise as clinical sleep studies.

Sleep quality changes following therapy commencement will be objectively assessed, and associations between treatment response and sleep patterns before and after therapy will be evaluated.

Patients will be asked to wear the Fitbit inspire 3 on their non-dominant hand for consecutive 5 days, in three different time slots (before initiation of new treatment, at week 4 after initiation, and at week 8 after initiation). Data will be extracted from the fit bit application into out registry.

Fitbit information include: sleep onset latency, wake after sleep onset, total sleep time, time in REM, time in light sleep, time in deep sleep.

Patients will complete the PSQI questionnaire and a sleep log, documenting bed time and wake time, facilitating calculations of sleep latency time, time in bed and sleep efficiency.

At the beginning and after 8 weeks participants bowel wall thickness will be assessed by intestinal ultrasound (IUS).

Clinical score will be assessed using the Harvey-Bradshaw index (HBI) at weeks: 0, 5, and 9. Basic medical and demographic data will be collected from the hospital's data sources.

Sample size calculations were based on the hypothesis that therapy response rates are associated with changes in sleep quality, measured both objectively and subjectively. Assuming a 40% clinical response rate, 28 patients are required to detect a statistically significant difference (p<0.05) with 80% power. Allowing for a 10% attrition rate, a total of 30 patients will be enrolled.

Descriptive statistics will be calculated for each variable measured and reported as means, medians, or proportions. Univariate analyses will be performed using paired t tests or Wilcoxon rank-sum tests for means and McNemar tests for categorical variables. Comparison of sleep quality and disease activity between study visits, and evaluation of the overtime trends in these parameters, in accordance with medical treatment will be performed by using the linear mixed model analysis (for three visits) and by the paired sample T test (two visits). Statistical significance is set at P ≤ 0.05.

• Study Type: Observational
• Enrollment (Estimated): 30

Contacts and Locations

Study Locations

• Israel
  • Tel Aviv, Israel
    • Recruiting
    • Dep. of Gastroenterology, Tel Aviv Sourasky Medical Center
    • Contact: Rony Izhar, PhD; Phone Number: +97237772613; Email: ronyi@tlvmc.gov.il
    • Contact: Ayal Hirsch, MD; Phone Number: +972535289492; Email: ayalh@tlvmc.gov.il
    • Principal Investigator: Ayal Hirsch, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

CD patients receiving care at the IBD Clinic at Tel Aviv Sourasky Medical Center (TASMC)

Description

Inclusion Criteria:

• Patients with established diagnosis of Crohn's Disease
• Patients with active inflammation, defined as HBI score ≥ 5 and either CRP>5 or stool calprotectin>250 mcg/gr.
• Patients starting advanced treatment as part of routine medical care (Anti TNFs, vedolizumab, Ustekinumab, IL-23 inhibitors, Jak inhibitors or S1P inhibitors).

Exclusion Criteria:

• Inability to give informed consent and complete the study protocol.
• Pregnant or lactating women
• Inability or reluctance to follow through with the study protocol, including (but not exclusive) to: questionnaires, wearing the watch while sleeping.
• Patients diagnosed with UC or indeterminate IBD.
• Other sleep disorders Obstructive sleep apnea overactive bladder insomnia shift work disorder restless leg syndrome Periodic limb movement of sleep Narcolepsy
• Use of sleep medication - such as benzodiazepines or cannabis.
• Recent abdominal surgery - previous 4 weeks.
• Severe systemic disease - CVD, Kidney, liver - as jugged by physician's discretion.
• Patients with ileostomy or short bowl syndrome.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Crohn disease patients; Patients starting advanced treatment as part of routine medical care	Other: Wearable activity and sleep tracker; Patients will be asked to wear the Fitbit inspire 3 on their non-dominant hand for consecutive 5 days, in three different time slots (before initiation of new treatment, at week 4 after initiation, and at week 8 after initiation); Other Names: Fitbit inspire 3

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Improved sleep quality according to the Pittsburgh Sleep Quality Index (PSQI)	Proportion of patients achieving improved sleep quality according to the Pittsburgh Sleep Quality Index (PSQI). Improvement is defined as a decrease of ≥3 points from baseline PSQI global score. Scores range from 0 to 21, with higher scores indicating worse sleep quality and greater sleep disturbance.	Week 8

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Improved sleep quality according to the Pittsburgh Sleep Quality Index (PSQI)	Proportion of patients achieving improved sleep quality according to the Pittsburgh Sleep Quality Index (PSQI). Improvement is defined as a decrease of ≥3 points from baseline PSQI global score. Scores range from 0 to 21, with higher scores indicating worse sleep quality and greater sleep disturbance.	Week 4
Change in sleep onset latency	Average change from baseline in sleep onset latency. Sleep onset latency is the length of time it takes to transition from full wakefulness to the lightest stage of sleep. Sleep onset latency will be calculated as the time interval between the bedtime reported by participants in the sleep diary and the time of sleep onset as determined from Fitbit data.	Week 4
Change in sleep onset latency	Average change from baseline in sleep onset latency. Sleep onset latency is the length of time it takes to transition from full wakefulness to the lightest stage of sleep. Sleep onset latency will be calculated as the time interval between the bedtime reported by participants in the sleep diary and the time of sleep onset as determined from Fitbit data.	Week 8
Change in wake after sleep onset (WASO)	Average change from baseline in wake after sleep onset. Wake after sleep onset will be calculated as the total time spent awake after sleep onset and before final awakening, as determined from Fitbit data. A low WASO indicates continuous, restorative sleep, whereas a high WASO points to sleep fragmentation.	Week 4
Change in wake after sleep onset (WASO)	Average change from baseline in wake after sleep onset. Wake after sleep onset will be calculated as the total time spent awake after sleep onset and before final awakening, as determined from Fitbit data. A low WASO indicates continuous, restorative sleep, whereas a high WASO points to sleep fragmentation.	Week 8
Change in total sleep time	Average change from baseline in total sleep time. Total sleep time will be defined as the total duration of sleep during the sleep period, as determined from Fitbit data.	Week 4
Change in total sleep time	Average change from baseline in total sleep time. Total sleep time will be defined as the total duration of sleep during the sleep period, as determined from Fitbit data.	Week 8
Time in Rapid Eye Movement (REM) sleep	Average change from baseline in time spent in REM sleep. REM sleep duration will be determined from Fitbit data.	Week 4
Time in Rapid Eye Movement (REM) sleep	Average change from baseline in time spent in REM sleep. REM sleep duration will be determined from Fitbit data.	Week 8
Time in light sleep	Average change from baseline in time in light sleep. Light sleep duration will be determined from Fitbit data.	Week 4
Time in light sleep	Average change from baseline in time in light sleep. Light sleep duration will be determined from Fitbit data.	Week 8
Time in deep sleep	Average change from baseline in time in deep sleep. Deep sleep duration will be determined from Fitbit data.	Week 4
Time in deep sleep	Average change from baseline in time in deep sleep. Deep sleep duration will be determined from Fitbit data.	Week 8
Fecal calprotectin	Change from baseline in stool calprotectin levels	Week 4
Fecal calprotectin	Change from baseline in stool calprotectin levels	Week 8
C-reactive protein (CRP)	Change from baseline in serum CRP levels	Week 4
C-reactive protein (CRP)	Change from baseline in serum CRP levels	Week 8
Harvey bradshaw index (HBI)	Change from baseline in HBI score. HBI is a clinical tool used to measure the severity of Crohn's Disease. The total HBI score ranges from 0 to >16, with higher scores indicating a worse outcome. A total HBI score of <5 indicates remission, 5-7 suggests mild severity, 8-16 denotes moderate severity, and ≥16 demarks severe disease.	Week 4
Harvey bradshaw index (HBI)	Change from baseline in HBI score. HBI is a clinical tool used to measure the severity of Crohn's Disease. The total HBI score ranges from 0 to >16, with higher scores indicating a worse outcome. A total HBI score of <5 indicates remission, 5-7 suggests mild severity, 8-16 denotes moderate severity, and ≥16 demarks severe disease.	Week 8
Clinical remission according to HBI	Proportion of patients with HBI score <5. The total HBI score ranges from 0 to >16, with higher scores indicating a worse outcome. A total HBI score of <5 indicates remission, 5-7 suggests mild severity, 8-16 denotes moderate severity, and ≥16 demarks severe disease.	Week 4
Clinical remission according to HBI	Proportion of patients with HBI score <5. The total HBI score ranges from 0 to >16, with higher scores indicating a worse outcome. A total HBI score of <5 indicates remission, 5-7 suggests mild severity, 8-16 denotes moderate severity, and ≥16 demarks severe disease.	Week 8

Collaborators and Investigators

• Sponsor: Shmuel Kivity, MD

Study record dates

Study Major Dates

• Study Start (Actual): August 6, 2025
• Primary Completion (Estimated): October 1, 2027
• Study Completion (Estimated): December 1, 2027

Study Registration Dates

• First Submitted: May 28, 2026
• First Submitted That Met QC Criteria: June 14, 2026
• First Posted (Actual): June 16, 2026

Study Record Updates

• Last Update Posted (Actual): June 16, 2026
• Last Update Submitted That Met QC Criteria: June 14, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: CD; Fitbit; Response to treatment; Sleep qulity
• Additional Relevant MeSH Terms: Intestinal Diseases; Digestive System Diseases; Gastrointestinal Diseases; Gastroenteritis; Inflammatory Bowel Diseases; Crohn Disease
• Other Study ID Numbers: 0167-25-TLV; MOH_2025-06-19_014152 (Other Identifier: Israeli ministry of health)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED
• IPD Plan Description: At this time, there are no plans for data sharing or external collaborations. If data sharing is pursued in the future, only de-identified participant data will be shared, including demographic information, clinical indices, questionnaire scores, and wearable device data.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No