Smart Data Collection for the Assessment of Treatment Effects in Irritable Bowel Syndrome: Observational Study.

BACKGROUND: End-of-day symptom diaries are recommended by drug regulatory authorities to assess treatment response in patients with irritable bowel syndrome. We developed a smartphone app to measure treatment response. OBJECTIVE: Because the employment of an app to measure treatment response in irritable bowel syndrome is relatively new, we aimed to explore patients' adherence to diary use and characteristics associated with adherence. METHODS: A smartphone app was developed to serve as a symptom diary. Patients with irritable bowel syndrome (based on Rome IV criteria) were instructed to fill out end-of-day diary questionnaires during an 8-week treatment. Additional online questionnaires assessed demographics, irritable bowel syndrome symptom severity, and psychosocial comorbidities. Adherence rate to the diary was defined as the percentage of days completed out of total days. Adherence to the additional web-based questionnaires was also assessed. RESULTS: Overall, 189 patients were included (age: mean 34.0 years, SD 13.3 years; female: 147/189, 77.8%; male: 42/189, 22.2%). The mean adherence rate was 87.9% (SD 9.4%). However, adherence to the diary decreased over time (P<.001). No significant association was found between adherence and gender (P=.84), age (P=.22), or education level (lower education level: P=.58, middle education level: P=.46, versus high education level), while higher anxiety scores were associated with lower adherence (P=.03). Adherence to the online questionnaires was also high (>99%). Missing data due to technical issues were limited. CONCLUSIONS: The use of a smartphone app as a symptom diary to assess treatment response resulted in high patient adherence. The data-collection framework described led to standardized data collection with excellent completeness and can be used for future randomized controlled trials. Due to the slight decrease in adherence to diary use throughout the study, this method might be less suitable for longer trials.

Timing and risk factors for clinical fractures among postmenopausal women: a 5-year prospective study.

BACKGROUND: Many risk factors for fractures have been documented, including low bone-mineral density (BMD) and a history of fractures. However, little is known about the short-term absolute risk (AR) of fractures and the timing of clinical fractures. Therefore, we assessed the risk and timing of incident clinical fractures, expressed as 5-year AR, in postmenopausal women. METHODS: In total, 10 general practice centres participated in this population-based prospective study. Five years after a baseline assessment, which included clinical risk factor evaluation and BMD measurement, 759 postmenopausal women aged between 50 and 80 years, were re-examined, including undergoing an evaluation of clinical fractures after menopause. Risk factors for incident fractures at baseline that were significant in univariate analyses were included in a multivariate Cox survival regression analysis. The significant determinants were used to construct algorithms. RESULTS: In the total group, 12.5% (95% confidence interval (CI) 10.1-14.9) of the women experienced a new clinical fracture. A previous clinical fracture after menopause and a low BMD (T-score <-1.0) were retained as significant predictors with significant interaction. Women with a recent previous fracture (during the past 5 years) had an AR of 50.1% (95% CI 42.0-58.1) versus 21.2% (95% CI 20.7-21.6) if the previous fracture had occurred earlier. In women without a fracture history, the AR was 13.8% (95% CI 10.9-16.6) if BMD was low and 7.0% (95% CI 5.5-8.5) if BMD was normal. CONCLUSION: In postmenopausal women, clinical fractures cluster in time. One in two women with a recent clinical fracture had a new clinical fracture within 5 years, regardless of BMD. The 5-year AR for a first clinical fracture was much lower and depended on BMD.

Do clinical findings in lower respiratory tract infection help general practitioners prescribe antibiotics appropriately? An observational cohort study in general practice.

BACKGROUND: Antibiotics are over-prescribed for lower respiratory tract infection (LRTI). The influence of clinicians' history and examination findings on antibiotic prescribing for LRTI has not been directly assessed, and the extent to which these clinical findings predict appropriate antibiotic prescribing is unknown. A clearer understanding is crucial to achieving evidence-based prescribing. OBJECTIVES: To directly assess the influence of general practitioners' history and examination findings on antibiotic prescribing for LRTI, and to explore the extent to which these clinical findings predict appropriate antibiotic prescribing. METHODS: In this observational cohort study 25 GPs in The Netherlands were recruited during routine consultations and 247 adult patients with a clinical diagnosis of LRTI. The GPs recorded clinical information. Odds ratios (ORs) with 95% confidence intervals (CIs) for clinical variables predicting a prescription for an antibiotic were calculated. The relationship between antibiotic prescription and radiographic evidence of pneumonia was explored in order to gauge appropriateness of antibiotic prescribing. RESULTS: Auscultation abnormalities (OR 11.5; 95% CI 5.4-24.7), and diarrhoea (OR>11) were strongly associated with antibiotic prescribing. An antibiotic was prescribed for 195 (79%) patients. Assuming that an antibiotic definitely needs to be prescribed only for patients with pneumonia, antibiotics may have been inappropriately prescribed for 166/193 (86%) of the patients. Antibiotics were not prescribed for 5 of the 32 (16%) patients with a radiographic diagnosis of pneumonia. CONCLUSIONS: Abnormal findings on auscultation in patients with LRTI strongly predict antibiotic prescribing and this is probably inappropriate for most patients. These results should prompt GPs to consider the extent to which finding 'crackles/rhonchi on auscultation' influences their decisions to prescribe antibiotics for their patients with LRTI, and to consider the predictive value of individual clinical signs in reaching evidence-based prescribing decisions.