TrialPanorama/Dataset huggingface dataset:
Please select the outcome measures that correspond to the clinical trial below.
Title: Compensation Factors of Cognitive Ageing: Using Computer Technology to Reduce Cognitive Decline in Ageing
Brief Summary: The ageing of the population will inevitably lead to a growing number of older people living alone and in need of care. Given the high cost of geriatric care, a critical research issue is exploring ways to improve or maintain cognitive and functional status in old age. Unfortunately, it has been shown that training those specific cognitive processes most sensitive to ageing (such as speed of processing or working memory), produces only limited beneficial effects. However, research also suggests that factors such as cognitive engagement, physical activity and social context may act as more general modulators of cognitive decline. This project is a longitudinal study with experimental and control groups. It is inspired from the engagement model of cognitive optimization suggesting that a lifestyle marked by social and intellectual engagement may mitigate age-related declines on cognitive functioning. It uses new cutting-edge information computing technology (ICT) solutions to improve or simply maintain cognitive functions in the elderly. This research investigates how the treatment reduces the effects of cognitive age-related decline in executive control processes and episodic (explicit) memory using behavioral and imaging measures. The results will provide significant knowledge on the potential of new ICT technologies to delay, compensate, and even prevent common chronic problems experienced by the elderly population. The hypothesis is that cognitive training with video-games through ICT solutions will promote brain and mental health and independence. Ultimately, the objective is to contribute to the understanding of factors that help avoiding the (personal and economic) consequences of long-term care in geriatric institutions.


Options:
A: Activity Compliance (Compliance with programmed activities will be assessed at the end of participation which is expected to be at 24 weeks)
B: Useful Field of View Test (12 months)
C: Change in cognitive function summary score (12 weeks)
D: Neuropsychological testing (Baseline, 12 weeks, and 24 weeks); Oddball task (Baseline, 12 weeks, and 24 weeks); Wisconsin task (Baseline, 12 weeks, and 24 weeks); Speed of processing task (Baseline, 12 weeks, and 24 weeks); Spatial working memory (WM) (Baseline, 12 weeks, and 24 weeks)

Answer: D
Please select the outcome measures that correspond to the clinical trial below.
Title: Compensation Factors of Cognitive Ageing: Using Computer Technology to Reduce Cognitive Decline in Ageing
Brief Summary: The ageing of the population will inevitably lead to a growing number of older people living alone and in need of care. Given the high cost of geriatric care, a critical research issue is exploring ways to improve or maintain cognitive and functional status in old age. Unfortunately, it has been shown that training those specific cognitive processes most sensitive to ageing (such as speed of processing or working memory), produces only limited beneficial effects. However, research also suggests that factors such as cognitive engagement, physical activity and social context may act as more general modulators of cognitive decline. This project is a longitudinal study with experimental and control groups. It is inspired from the engagement model of cognitive optimization suggesting that a lifestyle marked by social and intellectual engagement may mitigate age-related declines on cognitive functioning. It uses new cutting-edge information computing technology (ICT) solutions to improve or simply maintain cognitive functions in the elderly. This research investigates how the treatment reduces the effects of cognitive age-related decline in executive control processes and episodic (explicit) memory using behavioral and imaging measures. The results will provide significant knowledge on the potential of new ICT technologies to delay, compensate, and even prevent common chronic problems experienced by the elderly population. The hypothesis is that cognitive training with video-games through ICT solutions will promote brain and mental health and independence. Ultimately, the objective is to contribute to the understanding of factors that help avoiding the (personal and economic) consequences of long-term care in geriatric institutions.


Options:
A: Neuropsychological testing (Baseline, 12 weeks, and 24 weeks); Oddball task (Baseline, 12 weeks, and 24 weeks); Wisconsin task (Baseline, 12 weeks, and 24 weeks); Speed of processing task (Baseline, 12 weeks, and 24 weeks); Spatial working memory (WM) (Baseline, 12 weeks, and 24 weeks)
B: Cognitive impairment assessed with a Neuropsychological Test Battery, and Stroop and Trail Making tests. (2 years)
C: Change scores of Montreal Cognitive Assessment (MoCA) (baseline, posttest (an expected average of 3 months), follow-up (up to 9 months)); Change scores of Stroop test (baseline, posttest (an expected average of 3 months), follow-up (up to 9 months)); Change scores of Dual-task test (baseline, posttest (an expected average of 3 months), follow-up (up to 9 months)); Change scores of Timed up and go (TUG) test (baseline, posttest (an expected average of 3 months), follow-up (up to 9 months))
D: cognition: MMSE, ADAS-cog. (month 0, 6, 12)

Answer: A
Please select the outcome measures that correspond to the clinical trial below.
Title: Compensation Factors of Cognitive Ageing: Using Computer Technology to Reduce Cognitive Decline in Ageing
Brief Summary: The ageing of the population will inevitably lead to a growing number of older people living alone and in need of care. Given the high cost of geriatric care, a critical research issue is exploring ways to improve or maintain cognitive and functional status in old age. Unfortunately, it has been shown that training those specific cognitive processes most sensitive to ageing (such as speed of processing or working memory), produces only limited beneficial effects. However, research also suggests that factors such as cognitive engagement, physical activity and social context may act as more general modulators of cognitive decline. This project is a longitudinal study with experimental and control groups. It is inspired from the engagement model of cognitive optimization suggesting that a lifestyle marked by social and intellectual engagement may mitigate age-related declines on cognitive functioning. It uses new cutting-edge information computing technology (ICT) solutions to improve or simply maintain cognitive functions in the elderly. This research investigates how the treatment reduces the effects of cognitive age-related decline in executive control processes and episodic (explicit) memory using behavioral and imaging measures. The results will provide significant knowledge on the potential of new ICT technologies to delay, compensate, and even prevent common chronic problems experienced by the elderly population. The hypothesis is that cognitive training with video-games through ICT solutions will promote brain and mental health and independence. Ultimately, the objective is to contribute to the understanding of factors that help avoiding the (personal and economic) consequences of long-term care in geriatric institutions.


Options:
A: Neuropsychological testing (Baseline, 12 weeks, and 24 weeks); Oddball task (Baseline, 12 weeks, and 24 weeks); Wisconsin task (Baseline, 12 weeks, and 24 weeks); Speed of processing task (Baseline, 12 weeks, and 24 weeks); Spatial working memory (WM) (Baseline, 12 weeks, and 24 weeks)
B: Useful Field of View Test (12 months)
C: Activity Compliance (Compliance with programmed activities will be assessed at the end of participation which is expected to be at 24 weeks)
D: The study investigates changes in a neuropsychological assessment battery pre-randomization; and upon the completion of training.

Answer: A
Please select the outcome measures that correspond to the clinical trial below.
Title: Compensation Factors of Cognitive Ageing: Using Computer Technology to Reduce Cognitive Decline in Ageing
Brief Summary: The ageing of the population will inevitably lead to a growing number of older people living alone and in need of care. Given the high cost of geriatric care, a critical research issue is exploring ways to improve or maintain cognitive and functional status in old age. Unfortunately, it has been shown that training those specific cognitive processes most sensitive to ageing (such as speed of processing or working memory), produces only limited beneficial effects. However, research also suggests that factors such as cognitive engagement, physical activity and social context may act as more general modulators of cognitive decline. This project is a longitudinal study with experimental and control groups. It is inspired from the engagement model of cognitive optimization suggesting that a lifestyle marked by social and intellectual engagement may mitigate age-related declines on cognitive functioning. It uses new cutting-edge information computing technology (ICT) solutions to improve or simply maintain cognitive functions in the elderly. This research investigates how the treatment reduces the effects of cognitive age-related decline in executive control processes and episodic (explicit) memory using behavioral and imaging measures. The results will provide significant knowledge on the potential of new ICT technologies to delay, compensate, and even prevent common chronic problems experienced by the elderly population. The hypothesis is that cognitive training with video-games through ICT solutions will promote brain and mental health and independence. Ultimately, the objective is to contribute to the understanding of factors that help avoiding the (personal and economic) consequences of long-term care in geriatric institutions.


Options:
A: Change in cognitive function summary score (12 weeks)
B: Neuropsychological testing (Baseline, 12 weeks, and 24 weeks); Oddball task (Baseline, 12 weeks, and 24 weeks); Wisconsin task (Baseline, 12 weeks, and 24 weeks); Speed of processing task (Baseline, 12 weeks, and 24 weeks); Spatial working memory (WM) (Baseline, 12 weeks, and 24 weeks)
C: overall cognition (2 Monhths)
D: STROOP-Negative Priming (Change from Baseline Stroop-Negative Priming task at 15 weeks and 30 weeks); ODDBALL (Change from Baseline oddball task at 15 weeks and 30 weeks); N-BACK (Change from Baseline N-back task at 15 weeks and 30 weeks); CORSI BLOCK (Participants with non-action video-game training, change from baseline Corsi block task at 15 weeks and 30 weeks)

Answer: B
Please select the outcome measures that correspond to the clinical trial below.
Title: The Effects of Shifting Sedentary Behaviors to Light Activities on Energy Expenditure: A Randomized Controlled Trial in Sedentary Adults
Brief Summary: The main purposes of this randomized cross-over trial are to test if a 3h/day reduction of time spent in sedentary behaviour (SB) through breaking up hourly and shifting it for standing and walking behaviours would substantially increase total (TEE) and PA energy expenditure (PAEE) compared to a week of habitual prolonged SB, in male and female overweight/obese inactive (which do not attained MVPA recommendations) and sedentary desk workers. Specifically using an experiment design our main aims are: a) to determine the impact of reducing SB on TEE and PAEE; b) to analyse the independent effects of interrupting SB through breaks and the overall reduction in SB on TEE and PAEE; c) To analyse the determinants for the overall reduction in SB; d) If the changes occurred in TEE and PAEE were dependent on specific covariates.


Options:
A: Change from control week and intervention week in total energy expenditure (TEE) (week 1 and week 2); Resting energy expenditure (REE) (Baseline (day 0)); Change from control week and intervention week in physical activity energy expenditure (PAEE) (week 1 and week 2); Change from control week and intervention week in daily time spent in sedentary (SB) (week 1 and week 2); Change from control week and intervention week in light (LIPA), moderate and vigorous (MVPA) intensity activities (week 1 and week 2); Change from control week and intervention week in number of breaks in sedentary time (BST) (week 1 and week 2); Change from control week and intervention week in time spent sitting (TSS) (week 1 and week 2); Change from control week and intervention week in time spent standing (TSst) (week 1 and week 2); Change from control week and intervention week in time spent walking (TSW) (week 1 and week 2); Change from control week and intervention week in number of steps (week 1 and week 2)
B: Physical Activity Behavior (3 years)
C: Changes in daily sitting time in hours and minutes (Baseline, 4 months, 10 months and 22 months)
D: Change in Hours of Sitting Time (12 weeks)

Answer: A
Please select the outcome measures that correspond to the clinical trial below.
Title: The Effects of Shifting Sedentary Behaviors to Light Activities on Energy Expenditure: A Randomized Controlled Trial in Sedentary Adults
Brief Summary: The main purposes of this randomized cross-over trial are to test if a 3h/day reduction of time spent in sedentary behaviour (SB) through breaking up hourly and shifting it for standing and walking behaviours would substantially increase total (TEE) and PA energy expenditure (PAEE) compared to a week of habitual prolonged SB, in male and female overweight/obese inactive (which do not attained MVPA recommendations) and sedentary desk workers. Specifically using an experiment design our main aims are: a) to determine the impact of reducing SB on TEE and PAEE; b) to analyse the independent effects of interrupting SB through breaks and the overall reduction in SB on TEE and PAEE; c) To analyse the determinants for the overall reduction in SB; d) If the changes occurred in TEE and PAEE were dependent on specific covariates.


Options:
A: sitting time (one week); self-reported context-specific sitting time (one week); standing time (one week); breaks from sitting (one week)
B: Change from control week and intervention week in total energy expenditure (TEE) (week 1 and week 2); Resting energy expenditure (REE) (Baseline (day 0)); Change from control week and intervention week in physical activity energy expenditure (PAEE) (week 1 and week 2); Change from control week and intervention week in daily time spent in sedentary (SB) (week 1 and week 2); Change from control week and intervention week in light (LIPA), moderate and vigorous (MVPA) intensity activities (week 1 and week 2); Change from control week and intervention week in number of breaks in sedentary time (BST) (week 1 and week 2); Change from control week and intervention week in time spent sitting (TSS) (week 1 and week 2); Change from control week and intervention week in time spent standing (TSst) (week 1 and week 2); Change from control week and intervention week in time spent walking (TSW) (week 1 and week 2); Change from control week and intervention week in number of steps (week 1 and week 2)
C: Acceptability and feasibility (3 weeks)
D: Step Watch - Physical Activity Minutes (12 weeks between baseline and post-intervention follow up)

Answer: B
Please select the outcome measures that correspond to the clinical trial below.
Title: The Effects of Shifting Sedentary Behaviors to Light Activities on Energy Expenditure: A Randomized Controlled Trial in Sedentary Adults
Brief Summary: The main purposes of this randomized cross-over trial are to test if a 3h/day reduction of time spent in sedentary behaviour (SB) through breaking up hourly and shifting it for standing and walking behaviours would substantially increase total (TEE) and PA energy expenditure (PAEE) compared to a week of habitual prolonged SB, in male and female overweight/obese inactive (which do not attained MVPA recommendations) and sedentary desk workers. Specifically using an experiment design our main aims are: a) to determine the impact of reducing SB on TEE and PAEE; b) to analyse the independent effects of interrupting SB through breaks and the overall reduction in SB on TEE and PAEE; c) To analyse the determinants for the overall reduction in SB; d) If the changes occurred in TEE and PAEE were dependent on specific covariates.


Options:
A: Change from baseline in physical activity and sedentariness at 12 months (Baseline, 12 months)
B: Incidence of CHD and other lifestyle related diseases after ten years (2012)
C: Change from control week and intervention week in total energy expenditure (TEE) (week 1 and week 2); Resting energy expenditure (REE) (Baseline (day 0)); Change from control week and intervention week in physical activity energy expenditure (PAEE) (week 1 and week 2); Change from control week and intervention week in daily time spent in sedentary (SB) (week 1 and week 2); Change from control week and intervention week in light (LIPA), moderate and vigorous (MVPA) intensity activities (week 1 and week 2); Change from control week and intervention week in number of breaks in sedentary time (BST) (week 1 and week 2); Change from control week and intervention week in time spent sitting (TSS) (week 1 and week 2); Change from control week and intervention week in time spent standing (TSst) (week 1 and week 2); Change from control week and intervention week in time spent walking (TSW) (week 1 and week 2); Change from control week and intervention week in number of steps (week 1 and week 2)
D: duration of prolonged sitting (5 days)

Answer: C
Please select the outcome measures that correspond to the clinical trial below.
Title: The Effects of Shifting Sedentary Behaviors to Light Activities on Energy Expenditure: A Randomized Controlled Trial in Sedentary Adults
Brief Summary: The main purposes of this randomized cross-over trial are to test if a 3h/day reduction of time spent in sedentary behaviour (SB) through breaking up hourly and shifting it for standing and walking behaviours would substantially increase total (TEE) and PA energy expenditure (PAEE) compared to a week of habitual prolonged SB, in male and female overweight/obese inactive (which do not attained MVPA recommendations) and sedentary desk workers. Specifically using an experiment design our main aims are: a) to determine the impact of reducing SB on TEE and PAEE; b) to analyse the independent effects of interrupting SB through breaks and the overall reduction in SB on TEE and PAEE; c) To analyse the determinants for the overall reduction in SB; d) If the changes occurred in TEE and PAEE were dependent on specific covariates.


Options:
A: change in physical activity (4 months)
B: non-exercise activity (Measured constantly during the entire control period and measured constantly during the entire intervention period and the two periods were compared to determine change in non-exercise activity)
C: Change from control week and intervention week in total energy expenditure (TEE) (week 1 and week 2); Resting energy expenditure (REE) (Baseline (day 0)); Change from control week and intervention week in physical activity energy expenditure (PAEE) (week 1 and week 2); Change from control week and intervention week in daily time spent in sedentary (SB) (week 1 and week 2); Change from control week and intervention week in light (LIPA), moderate and vigorous (MVPA) intensity activities (week 1 and week 2); Change from control week and intervention week in number of breaks in sedentary time (BST) (week 1 and week 2); Change from control week and intervention week in time spent sitting (TSS) (week 1 and week 2); Change from control week and intervention week in time spent standing (TSst) (week 1 and week 2); Change from control week and intervention week in time spent walking (TSW) (week 1 and week 2); Change from control week and intervention week in number of steps (week 1 and week 2)
D: Physical Activity (Measured 5 times over 13 months, for seven days each time. Time points = baseline, 1-2weeks, 3 months, 6 months and 12 months)

Answer: C
Please select the outcome measures that correspond to the clinical trial below.
Title: A Phase III, Open-Label, Multicenter, Randomized Study to Investigate the Efficacy and Safety of Atezolizumab (Anti-PD-L1 Antibody) Compared With Docetaxel in Patients With Non-Small Cell Lung Cancer After Failure With Platinum Containing Chemotherapy
Brief Summary: This global, multicenter, open-label, randomized, controlled study evaluated the efficacy and safety of atezolizumab (an anti-programmed death-ligand 1 \[anti-PD-L1\] antibody)compared with docetaxel in participants with locally advanced or metastatic non-small cell lung cancer (NSCLC) after failure with platinum-containing chemotherapy. Participants were randomized 1:1 to receive either docetaxel or atezolizumab. Treatment may continue as long as participants experienced clinical benefit as assessed by the investigator, i.e., in the absence of unacceptable toxicity or symptomatic deterioration attributed to disease progression.


Options:
A: Overall Survival (From randomization to last follow-up. Analysis occured after all patients were on study for 18 months. Maximum follow-up at time of analysis was 61.5 months.)
B: Percentage of Participants Who Died: PP-ITT (Baseline until death due to any cause (up to approximately 2.25 years)); Percentage of Participants Who Died: Tumor Cells (TC)1/2/3 or Tumor-Infiltrating Immune Cells (IC)1/2/3 Subgroup of PP (Baseline until death due to any cause (up to approximately 2.25 years)); Overall Survival (OS): PP-ITT (Baseline until death due to any cause (up to approximately 2.25 years)); OS: TC1/2/3 or IC1/2/3 Subgroup of PP (Baseline until death due to any cause (up to approximately 2.25 years)); OS: SP-ITT (Baseline until death due to any cause (up to approximately 2.87 years)); OS: TC1/2/3 Or IC1/2/3 Subgroup of SP (Baseline until death from any cause (approximately 2.87 years)); OS: TC2/3 or IC2/3 Subgroup of SP (Baseline until death due to any cause (up to approximately 2.87 years)); OS: TC3 or IC3 Subgroup of SP (Baseline until death due to any cause (up to approximately 2.87 years))
C: Number of Patients Reporting Confirmed Non-small-cell Lung Cancer (NSCLC) Recurrence (Over a median follow-up time of 28 months post-Dose 1)
D: Overall Survival (OS) Time (From the date of randomization until death, assessed up to 5.6 years)

Answer: B
Please select the outcome measures that correspond to the clinical trial below.
Title: EFFECT OF SHORT-TERM TREATMENT WITH THE SYNBIOTIC PROBINUL-NEUTRO® ON GASTROINTESTINAL SYMPTOMS AND CIRCULATING PLASMA p-CRESOL LEVEL IN PATIENTS WITH CHRONIC RENAL FAILURE: A RANDOMIZED DOUBLE BLIND PILOT STUDY.
Brief Summary: The interest on gastrointestinal (GI) dysfunction in CKD has been growing in the last years. it is now accepted that GI dysfunction in dialyzed patients may contribute to systemic microinflammation by promoting gut dysbiosis and bacterial translocation in the blood. Another mechanism by which GI dysfunction contributes to systemic symptoms in CKD is related to metabolic activity of the dysbiotic microflora growing in the gut of these patients to generate toxic compounds such as phenols, indoles, and amines. Epidemiological evidence has strongly linked one of these compounds, p-Cresol, to cardiovascular risk and mortality in CKD. In the present paper the investigators investigated the effect of a probiotic/prebiotic mixture on plasma p-cresol concentrations and GI symptoms and in CKD patients not on dialysis yet.


Options:
A: Change of uremic toxins from basal to 1 and 3 months (Baseline, 1 month and 3 months); Change of uremic toxins from basal to 1 and 3 months (Baseline, 1 month and 3 months)
B: Hb A1c (3 months)
C: Changes in plasma p-cresol concentration (30 days)
D: the Occurrence of Cardiovascular Event and Peritonitis Events (6 month follow-up)

Answer: C