MATERIALS AND METHODS: This retrospective review concerned data for patients diagnosed with colorectal cancer in the years 1995 to 2011 collected from the Wilayah Persekutuan Health Office, taken from the cancer notification form (NCR-2), and patient medical records from the Surgical Department, Universiti Kebangsaan Malaysia Medical Centre (UKMMC). A total of 146 cases were analyzed. All the data collected were analysed using ArcGIS version 10.0 and SPSS version 19.0.
RESULTS: Patients aged 60 to 69 years accounted for the highest proportion of cases (34.2%) and males slightly predominated 76 (52.1%), Chinese had the highest number of registered cases at 108 (74.0%) and staging revealed most cases in the 3rd and 4th stages. Kernel density analysis showed more cases are concentrated up in the northern area of Petaling and Kuala Lumpur subdistricts. Spatial global pattern analysis by average nearest neighbour resulted in nearest neighbour ratio of 0.75, with Z-score of -5.59, p value of <0.01 and the z-score of -5.59. Spatial autocorrelation (Moran's I) showed clustering significant with p<0.01, Z score 3.14 and Moran's Index of 0.007. When mapping clusters with hotspot analysis (Getis-Ord Gi), hot and cold spots were identified. Hot spot areas fell on the northeast side of KL.
CONCLUSIONS: This study demonstrated significant spatial patterns of cancer incidence in KL. Knowledge about these spatial patterns can provide useful information to policymakers in the planning of screening of CRC in the targeted population and improvement of healthcare facilities to provide better treatment for CRC patients.
METHODS: Data for 91 countries were obtained from United Nations agencies. The response variable was life expectancy, and the determinant factors were demographic events (total fertility rate and adolescent fertility rate), socioeconomic status (mean years of schooling and gross national income per capita), and health factors (physician density and human immunodeficiency virus [HIV] prevalence rate). Path analysis was used to determine the direct, indirect, and total effects of these factors on life expectancy.
RESULTS: All determinant factors were significantly correlated with life expectancy. Mean years of schooling, total fertility rate, and HIV prevalence rate had significant direct and indirect effects on life expectancy. The total effect of higher physician density was to increase life expectancy.
CONCLUSIONS: We identified several direct and indirect pathways that predict life expectancy. The findings suggest that policies should concentrate on improving reproductive decisions, increasing education, and reducing HIV transmission. In addition, special attention should be paid to the emerging need to increase life expectancy by increasing physician density.
METHODS: A broad search strategy using key terms for MGUS, multiple myeloma, and 50 autoimmune diseases was used to search four electronic databases (PubMed, Medline, Embase, and Web of Science) from inception through November 2011.
RESULTS: A total of 52 studies met the inclusion criteria, of which 32 were suitably comparable to perform a meta-analysis. "Any autoimmune disorder" was associated with an increased risk of both MGUS [n = 760 patients; pooled relative risk (RR) 1.42; 95% confidence interval (CI), 1.14-1.75] and multiple myeloma (n>2,530 patients; RR 1.13, 95% CI, 1.04-1.22). This risk was disease dependent with only pernicious anemia showing an increased risk of both MGUS (RR 1.67; 95% CI, 1.21-2.31) and multiple myeloma (RR 1.50; 95% CI, 1.25-1.80).
CONCLUSIONS: Our findings, based on the largest number of autoimmune disorders and patients with MGUS/multiple myeloma reported to date, suggest that autoimmune diseases and/or their treatment may be important in the etiology of MGUS/multiple myeloma. The strong associations observed for pernicious anemia suggest that anemia seen in plasma cell dyscrasias may be of autoimmune origin.
IMPACT: Underlying mechanisms of autoimmune diseases, general immune dysfunction, and/or treatment of autoimmune diseases may be important in the pathogenesis of MGUS/multiple myeloma.
MATERIALS AND METHODS: This is prospective controlled trial. Peripheral venous blood sample is obtained from 20 patients with AAA and 36 normal control subjects. MMP-9 concentration levels were determined by an enzyme-linked immunosorbent assay and compared with subjects abdominal ultrasonography or computed tomography of abdomen.
RESULTS: Mean (± SE) MMP-9 was 23.94 ± 0.60 ng/mL in normal control subjects and 21.39 ± 1.03 ng/mL in patients with AAAs (p ← 0.05 versus normal control subjects). MMP-9 correlate significantly with AAA (p=0.004). There was no correlation of MMP-9 levels with age, gender, or other risk factors. The cutoff point is 12.54 for aorta size <3.0 cm. The sensitivity and specificity of MMP-9 were 60% and 64% respectively.
CONCLUSIONS: MMP-9 levels correlate significantly with AAA with a cutoff point of 12.54. However, the utility of MMP-9 as a diagnostic test is limited due to low sensitivity and specificity. An elevated MMP-9 has limited use to predict the presence of AAA (positive predictive value: 60%) and a normal MMP-9 level was insufficient to determine the absence of AAA (negative predictive value: 36.1%).
AIMS: We assessed outcomes of a pilot long-term stroke care clinic which combined secondary prevention and rehabilitation at community level.
SETTINGS AND DESIGN: A prospective observational study of stroke patients treated between 2008 and 2010 at a primary care teaching facility.
SUBJECTS AND METHODS: Analysis of patients was done at initial contact and at 1-year post treatment. Clinical outcomes included stroke risk factor(s) control, depression according to Patient Health Questionnaire (PHQ9), and level of independence using Barthel Index (BI).
STATISTICAL ANALYSIS USED: Differences in means between baseline and post treatment were compared using paired t-tests or Wilcoxon-signed rank test. Significance level was set at 0.05.
RESULTS: Ninety-one patients were analyzed. Their mean age was 62.9 [standard deviation (SD) 10.9] years, mean stroke episodes were 1.30 (SD 0.5). The median interval between acute stroke and first contact with the clinic 4.0 (interquartile range 9.0) months. Mean systolic blood pressure decreased by 9.7 mmHg (t = 2.79, P = 0.007), while mean diastolic blood pressure remained unchanged at 80mmHg (z = 1.87, P = 0.06). Neurorehabilitation treatment was given to 84.6% of the patients. Median BI increased from 81 (range: 2-100) to 90.5 (range: 27-100) (Z = 2.34, P = 0.01). Median PHQ9 scores decreased from 4.0 (range: 0-22) to 3.0 (range: 0-19) though the change was not significant (Z= -0.744, P = 0.457).
CONCLUSIONS: Primary care-driven long-term stroke care services yield favorable outcomes for blood pressure control and functional level.