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Objective Patient self‐assessed joint counts, if accurate and reliable, could potentially serve as a useful clinical assessment tool in rheumatoid arthritis (RA). This systematic review examines the effect of patient training on the inter‐rater reliability of joint counts between patients and clinicians. Methods The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. A search was performed in PubMed, Embase, Cochrane Library, and CINAHL for articles that incorporated patient training and measured the reliability of patient self‐assessed joint counts in RA. Articles were included if they reported on the inter‐rater reliability between patient and clinician joint counts in both trained and untrained patients with RA. Data were extracted on characteristics of patients, structure and components of the training interventions, joint count reliability of patients with and without training, and patient feedback on training interventions. The relevant data were summarized and described. Results Multiple training methods have been studied (n = 5), including in‐person sessions run by rheumatologists and instructional videos on the joint examination. Overall, training improved the reliability of patient self–joint counts, with more marked improvement in reliability of swollen joint counts than tender joint counts. Patients had positive feedback when surveyed on their experiences with training. Conclusion Various training modalities (in‐person and video‐based) may be effective at improving reliability of patient self–joint counts. More research is needed on this topic, with potential areas for future research including 1) comparison between the efficacy of different modalities of training, and 2) impact of patient factors (education level and disease severity) on the efficacy of training.

Introduction Inflammatory bowel disease (IBD) is a group of chronic gastrointestinal diseases with frequent systemic complications that are incurable according to current knowledge. These diseases adversely affect various areas of life, lowering patients' quality of life. One of the most frequently reported symptoms is fatigue. Aim Translation and validation of the IBD-F patient self-assessment scale with a Polish IBD population. Material and methods After consent from the author of the questionnaire had been obtained, the questionnaire was translated using the forward- and back-translation method. After arriving at the final Polish version of the questionnaire and ensuring that the questions and statements were comprehensible, the questionnaire was validated with a group of 129 IBD patients. Results High values of intraclass correlation coefficient (ICC) were achieved for overall results in both parts of the IBD-F questionnaire between test and retest (values exceeding 0.75). A high Cronbach's α consistency coefficient was achieved for the entire IBD-F questionnaire, both in the test and in the retest (0.968 and 0.975, respectively). Broken down into parts, Cronbach's α coefficient for Section I (presence and severity of fatigue) of the IBD-F questionnaire was 0.883, and for Section II (impact of fatigue on the person's life) it was 0.966. All patients evaluating the Polish version of the IBD-F questionnaire deemed the content of the questions comprehensible. Conclusions The analysis of the results obtained, the Polish version of the IBD-F questionnaire was considered valid, reliable, and clinically useful.

Background Patient waiting time at outpatient departments is directly related to patient satisfaction and quality of care, particularly in patients visiting the general internal medicine outpatient departments for the first time. Moreover, reducing wait time from arrival in the clinic to the initiation of an examination is key to reducing patients’ anxiety. The use of automated medical history–taking systems in general internal medicine outpatient departments is a promising strategy to reduce waiting times. Recently, Ubie Inc in Japan developed AI Monshin, an artificial intelligence–based, automated medical history–taking system for general internal medicine outpatient departments. Objective We hypothesized that replacing the use of handwritten self-administered questionnaires with the use of AI Monshin would reduce waiting times in general internal medicine outpatient departments. Therefore, we conducted this study to examine whether the use of AI Monshin reduced patient waiting times. Methods We retrospectively analyzed the waiting times of patients visiting the general internal medicine outpatient department at a Japanese community hospital without an appointment from April 2017 to April 2020. AI Monshin was implemented in April 2019. We compared the median waiting time before and after implementation by conducting an interrupted time-series analysis of the median waiting time per month. We also conducted supplementary analyses to explain the main results. Results We analyzed 21,615 visits. The median waiting time after AI Monshin implementation (74.4 minutes, IQR 57.1) was not significantly different from that before AI Monshin implementation (74.3 minutes, IQR 63.7) (P=.12). In the interrupted time-series analysis, the underlying linear time trend (–0.4 minutes per month; P=.06; 95% CI –0.9 to 0.02), level change (40.6 minutes; P=.09; 95% CI –5.8 to 87.0), and slope change (–1.1 minutes per month; P=.16; 95% CI –2.7 to 0.4) were not statistically significant. In a supplemental analysis of data from 9054 of 21,615 visits (41.9%), the median examination time after AI Monshin implementation (6.0 minutes, IQR 5.2) was slightly but significantly longer than that before AI Monshin implementation (5.7 minutes, IQR 5.0) (P=.003). Conclusions The implementation of an artificial intelligence–based, automated medical history–taking system did not reduce waiting time for patients visiting the general internal medicine outpatient department without an appointment, and there was a slight increase in the examination time after implementation; however, the system may have enhanced the quality of care by supporting the optimization of staff assignments.

The French Flare instrument (FI) aims to identify flares in rheumatoid arthritis between consultation. The objective of the present study was to present both concurrent and criterion validity of the Danish version of FI, as compared to DAS28-CRP. The study was a cross-sectional study comparing FI with DAS28-CRP among patients with rheumatoid arthritis (RA) in connection with the same outpatient visit. The study population consisted of 117 prevalent patients diagnosed with RA according to the ACR 1987/2010 criteria. Consecutive patients were included in the study in relation to their outpatient treatment at the Department of Rheumatology, Aarhus University Hospital, Denmark between 01 October 2012 and 31 December 2012. The sensitivity and specificity were 85.4 (95 % CI, 72.2; 93.9) and 50.7 (95 % CI, 38.4; 63.0), respectively. The positive predictive value was 53.6 (95 %CI, 47.0; 60.1) and the negative predictive value 83.9 (95 % CI, 71.7; 91.5). Positive and negative likelihood ratio were 1.73(95 % CI, 1.33; 2.26) and 0.29 (95 % CI, 0.14; 0.59). Tests with high sensitivity and small LR are most useful for ruling out the disease. Hence, our findings indicate that FI works well in ruling out a flare among patients with RA.

Logistic regression models are widely used in medicine, but difficult to apply without the aid of electronic devices. In this paper, we present a novel approach to represent logistic regression models as nomograms that can be evaluated by simple line drawings. As a case study, we show how data obtained from a questionnaire-based patient self-assessment study on the risks of developing melanoma can be used to first identify a subset of significant covariates, build a logistic regression model, and finally transform the model to a graphical format. The advantage of the nomogram is that it can easily be mass-produced, distributed and evaluated, while providing the same information as the logistic regression model it represents.

A randomised double-blind placebo-controlled trial of phenylethylmalonamide, the major metabolite of primidone was performed in eight patients with essential tremor. Phenylethylmalonamide was given in a daily dose of 400 mg for one week and 800 mg for a second week. The compound had no statistically significant effect on the amplitude of tremor assessed by an accelerometric method, tests of performance, clinical evaluation and patient self assessment. No side effects occurred. Serum levels of phenylethylmalonamide on a daily dose of 400 mg were 11-27 micrograms/ml and on 800 mg daily were 16-48.5 micrograms/ml.

Background Preoperative assessment of functional capacity is necessary to direct decisions regarding cardiac evaluation and may help identify patients at high risk for perioperative complications. Patient self-triage regarding functional capacity could be useful for discerning which patients benefit from a clinician evaluation at a Preoperative Evaluation Center prior to the day of surgery. We evaluated the feasibility of preoperative, patient self-triage regarding functional capacity. Methods Patients were recruited immediately prior to their preoperative evaluation. Study participants completed electronic versions of the Duke Activity Status Index (DASI) and the Patient-Reported Outcomes Measurement System (PROMIS)–Short Form 12a–Physical Function. DASI and PROMIS questionnaire responses were scored and evaluated for correlation with clinician assessments of functional capacity. Correlation was analyzed around the dichotomous outcome of