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

[This corrects the article DOI: 10.2196/19696.].

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.

Influence of watchful waiting on satisfaction and anxiety among patients seeking care for unexplained complaints.

PURPOSE: We undertook a study to determine whether test-ordering strategy and other consultation-related factors influence satisfaction with and anxiety after a consultation among patients seeking care for unexplained complaints. METHODS: A cluster-randomized clinical trial was conducted in family medicine practices in the Netherlands. Participants were 498 patients with unexplained complaints seen by 63 primary care physicians. Physicians either immediately ordered a blood test for patients or followed a 4-week watchful waiting approach. Physicians and patients completed questionnaires asking about their characteristics, satisfaction with care, and anxiety, and aspects of the consultation. The main outcomes were patient satisfaction and anxiety. Data were analyzed by multilevel logistic regression analysis. RESULTS: Patients were generally satisfied with their consultation and had moderately low anxiety afterward (mean scores on 11-point scales, 7.3 and 3.1, respectively), with no difference between the immediate testing and watchful waiting groups (chi(2) = 2.4 and 0.3, respectively). The factors associated with higher odds of satisfaction were mainly related to physician-patient communication: patients' satisfaction with their physician generally, feeling taken seriously, and knowing the seriousness of complaints afterward; physicians' discussing testing and not considering complaints bearable; and older physician age. The same was true for factors associated with higher odds of anxiety: patients expecting testing or referral, patients not knowing the seriousness of their complaints afterward, and physicians not seeing a cause for alarm. CONCLUSIONS: Test-ordering strategy does not influence patients' satisfaction with and anxiety after a consultation. Instead, specific aspects of physician-patient communication are important. Apparently, primary care physicians underestimate how much they can contribute to the well-being of their patients by discussing their worries.

Risk factors for clinical fractures among postmenopausal women: a 10-year prospective study.

OBJECTIVE: Only scarce data are available on the long-term absolute risk (AR) of all clinical fractures, taking into account the time when they occurred. Therefore, we assessed during a 10-year follow-up the risk factors associated with the occurrence of any first or second clinical fracture. STUDY DESIGN: This was a population-based study in 10 general practice centres. The sample comprised 2372 postmenopausal women, aged between 50 and 80 years at baseline, who completed a questionnaire about the incidence of radiographically confirmed fractures and fracture risks, analysed by multiple Cox regression. MAIN OUTCOME MEASURE: AR for any clinical fracture. RESULTS: During the 10-year follow-up, 380 women (16%) had a fracture. A first fracture occurred in 267 women (11%). Osteoporosis at the lumbar spine (T-score <-2.5; hazard ratio (HR) 1.8, 95% confidence interval (CI) 1.4-2.3) and age over 60 years (HR1.4, 95% CI 1.1-1.8) were the only risk factors retained in the Cox analysis. The AR in the lowest-risk group was 10%, and it was 23% in the highest-risk group. A second fracture occurred in 113 women during follow-up (5%). The time when a fracture occurred was the only risk factor retained in the Cox analysis. The AR for a second fracture was 41% in the five years after any first fracture before baseline and 25% if the first fracture had occurred earlier (HR 1.8, 95% CI 1.3-2.7). CONCLUSION: In postmenopausal women, over a 10-year follow-up, the AR of a second clinical fracture is highest in the five years after any first clinical fracture. The AR for a first clinical fracture is lower and depends on osteoporosis and age.

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.