A COMPARATIVE STUDY OF UNIVARIATE TIME SERIES MODELLING FOR NATURAL RUBBER PRODUCTION IN MALAYSIA

Malaysia is one of the top countries that produces natural rubber and was ranked sixth place globally. The earnings from natural rubber products are making billions of ringgit for the country. However, over the past years the natural rubber production in Malaysia has been inconsistent and the deficiencies in the production can affect Malaysia’s economy. Therefore, it is important for relevant agencies and departments to understand the patterns and trends of natural rubber production in Malaysia besides having the ability to forecast. Hence, the integrated autoregressive moving average (ARIMA), seasonal autoregressive moving average (SARIMA) and the seasonal Holt-Winter’s model were being considered for the purpose of modelling and forecasting this study. The forecast accuracy criteria used to evaluate the performance of the models are the root mean square error (RMSE) and mean absolute percentage error (MAPE). The results showed that the seasonal Holt-Winter’s model appeared to be the best model as it yielded the lowest RMSE and MAPE values. The seasonal Holt-Winter’s model, however, is not a good choice of model as it was unable to forecast six months ahead values. On the other hand, the SARIMA model had a better forecast ability when forecasting the values for the same duration. Therefore, the SARIMA model is taken to be the model in forecasting the natural rubber production in Malaysia for that period. This study has shown that the best fit model that fulfil all the forecast accuracy criteria may not have the best forecast ability

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Psychiatric co-morbidity and asthma: A pilot study utilizing a free use tool to improve asthma care

Purpose: To assess the prevalence of co-morbid psychiatric disorders in asthmatic patients in a Western Canadian Regional Severe Asthma Center. Methods: A prospective study was completed of patients evaluated through the Edmonton Regional Severe Asthma Clinic (ERSAC). A standardised evaluation, the Mini International Neuropsychiatric Interview (MINI) screen was used to identify possible psychiatric disorders. Results: Twenty-four individuals with moderate to severe asthma, who presented for treatment at ERSAC, were recruited and underwent assessment with the MINI screen. The average patient age was 48 years (range 18–81 years). Nine patients were male and fifteen were female. Twenty subjects (83%) screened positive for a possible psychiatric co-morbidity using the MINI screen. The most common psychiatric co-morbidities identified were post-traumatic stress disorder (50% of the sampled population), depressive episode or persistent depressive disorder (42%), substance/alcohol abuse (33%), generalized anxiety disorder (335), manic episode (25%), agoraphobia (21%), panic disorder (21%) and obsessive-compulsive disorder (17%). Some individuals had more than one concomitant possible psychiatric co-morbidity identified by the MINI screen. Conclusions: Psychiatric co-morbidity was confirmed to be common in patients with moderate-severe asthma. In individuals with asthma, the MINI screen appeared to be a simple and useful clinical tool to screen for untreated/sub-optimally-managed psychiatric co-morbidities that may impact management