Canadian Emergency Department Triage and Acuity Scale: implementation in a tertiary care center in Saudi Arabia.

BACKGROUND: The Canadian Emergency Department Triage and Acuity Scale (CTAS) is a well recognized and validated triage system that prioritizes patient care by severity of illness. The aim of this study was to describe the results of Emergency Department (ED) waiting times after the implementation of the CTAS in a major tertiary care hospital emergency department outside of Canada. METHODS: A total of 1206 charts were randomly selected and retrospectively reviewed for triage performance. The indicators were: time to triage, triage duration, waiting time to be evaluated by a physician, and proportion of patients who left without being seen by a physician. Waiting times were stratified by triage level and reported as fractile response rates. RESULTS: The approximate time to triage was ≤ 10 minutes for 71% and ≤ 15 minutes for 82.8% of the patients. Fifty-three percent (53.5%) completed their triage process within 5 minutes. Waiting times evaluated by a physician was 100% within CTAS time objectives in category I patients, however, this was not the case for the other 4 categories. The overall left without being seen (LWBS) rate was 9.8%; 11.9% were in Level III, 20.3% in Level IV, and 67.8% in Level V. Median length of stay (LOS) was 144 minutes for the study sample as a whole. CONCLUSION: The CTAS may be adapted, with achievable objectives, in hospitals outside Canada as well. Time to see physician, total LOS, and LWBS are effective markers of ED performance and the quality of triage. Registration-to-physician time (RTP) and LOS profiles, stratified by triage level, are essential indicative markers for ED performance and should be used in improving patients flow through collaborative efforts.

Prospective phase II study of neoadjuvant doxorubicin followed by cisplatin/docetaxel in locally advanced breast cancer.

The objective of this study is to evaluate the efficacy and safety profile of the doxorubicin followed by cisplatin/docetaxel as primary chemotherapy for patients with locally advanced breast cancer (LABC). For this evaluation, 59 patients with LABC (T2-T4, N0-N2, M0) received three cycles of doxorubicin, followed by three cycles of cisplatin/docetaxel and followed by definitive surgery and locoregional radiotherapy with or without tamoxifen. The primary end point was pathologic complete response (pCR) in breast and axilla. Fifty-nine patients were evaluable for analysis: median age: 41 years, premenopausal: 68%, median tumor size: 6.0 cm (4-10), Stage IIB: 32% and IIIA/IIIB: 68%, both ER/PR positive: 53%, Her2/neu (3+) by IHC staining: 29%. Clinical complete response was seen in 44%, and clinical partial response was seen in 56%. Breast conserving surgery was performed in 44%, and MRM in 56%. pCR in the breast was 30.5%, in axilla was 37%, and pCR in both breast and axilla was 24%. Overall at follow-up of 60 months, the disease-free (DFS) and overall survival (OS) were 70 and 82%, respectively. The DFS and OS of patients who achieved complete pathologic response in breast and axilla were 78 and 100%, respectively, while 14 patients relapsed of which 46% were Her2 positive. Sequential combination of doxorubicin followed by docetaxel/cisplatin is a safe, feasible, and active combination, which offers the possibility of conservative surgery and is associated with high clinical and pathologic response rates, with promising and encouraging survival outcomes.

Analyzing biological rhythms in clinical trials.

BACKGROUND: The human body exhibits a variety of biological rhythms. There are patterns that correspond, among others, to the daily wake / sleep cycle, a yearly seasonal cycle and, in women, the menstrual cycle. Sine/cosine functions are often used to model biological patterns for continuous data, but this model is not appropriate for analysis of biological rhythms in failure time data. METHODS: We consider a method appropriate for analysis of biological rhythms in clinical trials. We present a method to provide an estimate and confidence interval of the time when the minimum hazard is achieved. A motivating example from a clinical trial of adjuvant of pre-menopausal breast cancer patients provides an important illustration of the methodology in practice. RESULTS: Adapting the Cosinor method to the Weibull proportional hazards model is proposed as useful way of modeling the biological rhythm data. It presents a method to estimate the time that achieves the minimum hazard along with its associated confidence interval. The application of this technique to the breast cancer data revealed that the optimal day for pre-resection incisional or excisional biopsy of 28-day cycle (i.e. the day associated with the lowest recurrence rate) is day 8 with 95% CI 5-10. We found that older age, fewer positive nodes, smaller tumor size, and experimental treatment are important prognostic factors of longer relapse-free survival. CONCLUSIONS: The analysis of biological/circadian rhythms is usually handled by Cosinor rhythmometry method. However, in FTD this is simply not possible. In this case, we propose to adapt the Cosinor method to the Weibull proportional hazard model. The advantage of the proposed method is its ability to model survival data. This method is not limited to breast cancer data, and may be applied to any biological rhythms linked to right censored data.

Modeling biological rhythms in failure time data.

BACKGROUND: The human body exhibits a variety of biological rhythms. There are patterns that correspond, among others, to the daily wake/sleep cycle, a yearly seasonal cycle and, in women, the menstrual cycle. Sine/cosine functions are often used to model biological patterns for continuous data, but this model is not appropriate for analysis of biological rhythms in failure time data. METHODS: We adapt the cosinor method to the proportional hazards model and present a method to provide an estimate and confidence interval of the time when the minimum hazard is achieved. We then apply this model to data taken from a clinical trial of adjuvant of pre-menopausal breast cancer patients. RESULTS: The application of this technique to the breast cancer data revealed that the optimal day for pre-resection incisional or excisional biopsy of 28-day cycle (i. e. the day associated with the lowest recurrence rate) is day 8 with 95% confidence interval of 4-12 days. We found that older age, fewer positive nodes, smaller tumor size, and experimental treatment were predictive of longer relapse-free survival. CONCLUSION: In this paper we have described a method for modeling failure time data with an underlying biological rhythm. The advantage of adapting a cosinor model to proportional hazards model is its ability to model right censored data. We have presented a method to provide an estimate and confidence interval of the day in the menstrual cycle where the minimum hazard is achieved. This method is not limited to breast cancer data, and may be applied to any biological rhythms linked to right censored data.