Multimorbidity and mortality among older patients with coronary heart disease in Shenzhen, China.

BACKGROUND: The current understanding of the magnitude and consequences of multimorbidity in Chinese older adults with coronary heart disease (CHD) is insufficient. We aimed to assess the association and population-attributable fractions (PAFs) between multimorbidity and mortality among hospitalized older patients who were diagnosed with CHD in Shenzhen, China. METHODS: We conducted a retrospective cohort study of older Chinese patients (aged ≥ 65 years) who were diagnosed with CHD. Cox proportional hazards models were used to estimate the associations between multimorbidity and all-cause and cardiovascular disease (CVD) mortality. We also calculated the PAFs. RESULTS: The study comprised 76,455 older hospitalized patients who were diagnosed with CHD between January 1, 2016, and August 31, 2022. Among them, 70,217 (91.9%) had multimorbidity, defined as the presence of at least one of the predefined 14 chronic conditions. Those with cancer, hemorrhagic stroke and chronic liver disease had the worst overall death risk, with adjusted HRs (95% CIs) of 4.05 (3.77, 4.38), 2.22 (1.94, 2.53), and 1.85 (1.63, 2.11), respectively. For CVD mortality, the highest risk was observed for hemorrhagic stroke, ischemic stroke, and chronic kidney disease; the corresponding adjusted HRs (95% CIs) were 3.24 (2.77, 3.79), 1.91 (1.79, 2.04), and 1.81 (1.64, 1.99), respectively. All-cause mortality was mostly attributable to cancer, heart failure and ischemic stroke, with PAFs of 11.8, 10.2, and 9.1, respectively. As for CVD mortality, the leading PAFs were heart failure, ischemic stroke and diabetes; the corresponding PAFs were 18.0, 15.7, and 6.1, respectively. CONCLUSIONS: Multimorbidity was common and had a significant impact on mortality among older patients with CHD in Shenzhen, China. Cancer, heart failure, ischemic stroke and diabetes are the primary contributors to PAFs. Therefore, prioritizing improved treatment and management of these comorbidities is essential for the survival prognosis of CHD patients from a holistic public health perspective.

[Expression of A-kinase anchor protein 95, cyclin E2, and connexin 43 in lung cancer tissue, clinical significance of their expression, and their expression correlation].

OBJECTIVE: To study the expression of A-kinase anchor protein 95 (AKAP95), cyclin E(2), and connexin 43 (Cx43) in lung cancer tissue, the clinical significance of their expression, and the expression correlation among the three proteins. METHODS: Fifty-one samples of lung cancer tissue were examined by immunohistochemistry to measure the expression of AKAP95, cyclin E2, and Cx43. RESULTS: The positive rate of AKAP95 expression in lung cancer tissue was significantly higher than that in paracancerous tissue (82.35% vs 33.33%, P < 0.05); AKAP95 expression was associated with the cell differentiation and histopathological type of lung cancer (P < 0.05). The positive rate of cyclin E(2) expression in lung cancer tissue was significantly higher than that in paracancerous tissue (43.14% vs 13.33%, P < 0.05); cyclin E(2) expression was associated with the lymph node metastasis and histopathological type of lung cancer (P < 0.05). The positive rate of Cx43 expression in lung cancer tissue was lower than that in paracancerous tissue (60.78% vs 80.00%); Cx43 expression was associated with the cell differentiation, lymph node metastasis, and histopathological type of lung cancer (P < 0.05). There was correlation between each two of AKAP95 expression, cyclin E(2) expression, and Cx43 expression in lung cancer tissue. CONCLUSION: High expression of AKAP95 and cyclin E(2) plays an important role in the occurrence and development of lung cancer. AKAP95 expression is associated with the cell differentiation and histopathological type of lung cancer, and cyclin E2 expression is associated with lymph node metastasis and histopathological type. There is correlation between each two of AKAP95 expression, cyclin E(2) expression, and Cx43 expression in lung cancer tissue.

[Markov process of vegetation cover change in arid area of northwest China based on FVC index].

Based on the fractional vegetation cover (FVC) data of 1982-2000 NOAA/AVHRR (National Oceanic and Atmospheric Administration/ the Advanced Very High Resolution Radiometer) images, the whole arid area of Northwest China was divided into three sub-areas, and then, the vegetation cover in each sub-area was classified by altitude. Furthermore, the Markov process of vegetation cover change was analyzed and tested through calculating the limit probability of any two years and the continuous and interval mean transition matrixes of vegetation cover change with 8 km x 8 km spatial resolution. By this method, the Markov process of vegetation cover change and its indicative significance were approached. The results showed that the vegetation cover change in the study area was controlled by some random processes and affected by long-term stable driving factors, and the transitional change of vegetation cover was a multiple Markov process. Therefore, only using two term image data, no matter they were successive or intervallic, Markov process could not accurately estimate the trend of vegetation cover change. As for the arid area of Northwest China, more than 10 years successive data could basically reflect all the factors affecting regional vegetation cover change, and using long term average transition matrix data could reliably simulate and predict the vegetation cover change. Vegetation cover change was a long term dynamic balance. Once the balance was broken down, it should be a long time process to establish a new balance.