29 research outputs found

    Some economic problems of the Illinois River Valley

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    Papers presented before the Economics Section of the Illinois State Academy of Science, Peoria, Illinois, May 8, 1931.Includes bibliographical references

    Pharmacognostical Sources of Popular Medicine To Treat Alzheimer’s Disease

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    Cumulative patient-based disease activity monitoring in rheumatoid arthritis - predicts sustained remission, flare and treatment escalation

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    Objective Patient-based Disease Activity Score 2 (PDAS2) had been developed for RA patients to self-assess and record disease activity in between clinic visits. This study explored the clinical utility of time-integrated cumulative PDAS2 (cPDAS2) on predicting sustained remission or low disease activity state (LDAS), flare and treatment escalation. Methods We recruited 100 patients to record PDAS2 at home fortnightly between two consecutive clinic visits. Rheumatologists adjusted treatment according to disease activity recorded during clinic consultation while blinded to home PDAS2 scores. cPDAS2 calculated from the area-under-curve of all PDAS2 scores were compared with disease activities at both visits. cPDAS2 and ΔcPDAS2 (change from PDAS2 at the first visit) were tested to determine their ability to predict ACR/EULAR remission, SDAI flare-up (from remission/LDAS to moderate/high disease activity) and treatment escalation. Optimal cut-points were determined by Receiver Operator Characteristic curve. Results Mean age of the patients was 59 years, mean RA duration 14 years, 90% were female, 71% seropositive and 64% in remission/LDAS. The home PDAS2 completion rate was 92%. PDAS2 scores were done 7.5 times every 15 days over a 16-week follow-up (all medians). The sensitivity of cPDAS2 in predicting Boolean/SDAI remission at two visits, DAS28, SDAI and CDAI remission or LDAS were 93%, 84%, 73% and 80% respectively. cPDAS2 ≥ 0.29 predicted flare (P = 0.04), with specificity 79% and negative predicting value (NPV) 88%. Rheumatologists' decision to escalate treatment was predicted by (cPDAS2 ≥ 4.33 and ΔcPDAS2 ≥ 0.059) (P = 0.007) with specificity 88% and NPV 89%, and (cPDAS2 ≥ 4.33 or ΔcPDAS2 ≥ 0.059) (P = 0.02) with both sensitivity and NPV 100%. Conclusion PDAS2 monitoring at home is feasible. cPDAS2 is useful to predict flare and treatment escalation
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