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Article in English | WPRIM | ID: wpr-878305


Objective@#Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains unclear.@*Methods@#A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients' medical records. Multivariable logistic regression models were used to estimate the odds ratio ( @*Results@#Overall, 158 (13.6%) patients were diagnosed with severe illness and 32 (2.7%) had unfavorable outcomes. Hypertension (2.87, 1.30-6.32), type 2 diabetes (T2DM) (3.57, 2.32-5.49), cardiovascular disease (CVD) (3.78, 1.81-7.89), fatty liver disease (7.53, 1.96-28.96), hyperlipidemia (2.15, 1.26-3.67), other lung diseases (6.00, 3.01-11.96), and electrolyte imbalance (10.40, 3.00-26.10) were independently linked to increased odds of being severely ill. T2DM (6.07, 2.89-12.75), CVD (8.47, 6.03-11.89), and electrolyte imbalance (19.44, 11.47-32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission (5.46, 3.25-9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes (6.58, 1.46-29.64) within two weeks.@*Conclusion@#Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.

Adult , Aged , COVID-19/virology , China/epidemiology , Comorbidity , Female , Humans , Male , Middle Aged , Retrospective Studies , Severity of Illness Index , Treatment Outcome
Article in Chinese | WPRIM | ID: wpr-274764


<p><b>OBJECTIVE</b>To evaluate the effect of preventive medicine for residents living around mosquito breeding water during rest period of malaria by delimiting a certain range.</p><p><b>METHOD</b>The study adopted the stratified cluster random sampling method to select subjects from 6 counties in the high epidemic area along and north of the Huai River since March 2007. Then the villages of 6 counties were stratified into five levels according to the case reported in year 2006, and one village was randomly selected from each level, thereby 30 villages were selected in total.300-500 subjects were interviewed in each village, and in total 12 860 subjects were recruited in the study. The five selected villages in each county were allocated to three intervention groups according to the block randomization method. The first intervention group included 9 villages, 4362 people; the second intervention group was consisted of 12 villages, 4471 people; the non-intervention group had 9 villages, 4027 people. The basic information of the subjects were collected by questionnaire to analyze the relation between malaria cases and the distribution of the mosquito breeding water, then accordingly delimited the range for preventive medicine. Group 1 received the delimiting preventive medicine treatment, group 2 received routine medicine treatment, while non-treatment group received no treatment. The morbidity, standardized morbidity, net change of morbidity (the D-value of the standardized morbidity before and after the intervention), age-specified incidence, and the protective rate (PR), effectiveness index (IE) and the capture rate of the delimited method group were then calculated.</p><p><b>RESULTS</b>Group 1 had 1219 (27.9%) people taking medicine and Group 2 had 219 (4.9%) people. In 2006, before the prevention conducting, the high incidence aging group in the first, second and nonintervention group was separately people aging 50 - 59, 60 - 69 and ≥ 70 years old; whose incidence was 36.22‰ (18/497), 40.11‰ (15/374) and 34.88‰ (9/258) respectively. After the intervention, the high incidence aging groups in the first and second intervention group changed to the population over 70 years old, with incidence at 9.17‰ (3/327) and 22.01‰ (7/318) respectively; while the high incidence aging groups in the nonintervention group changed to people aging between 30-39 years old, with the rate at 24.88‰ (10/402). In 2006, the morbidity of malaria in the first, second intervention group and nonintervention group was separately 18.78‰ (83/4420), 20.27‰ (93/4587) and 14.61‰ (53/3627); while the standardized incidence was separately 18.85‰, 20.72‰ and 14.89‰. In 2007, after the prevention conducting, the morbidity in the three groups was 2.75‰ (12/4362), 11.63‰ (52/4471) and 12.17‰ (49/4027), respectively; while the standardized incidences was 2.81‰, 12.75‰ and 12.35‰, respectively. The net value of changes of morbidity in the three groups was separately 16.04%, 7.97% and 2.54%. The difference in net values of changes of morbidity between intervention group 1 and 2 had statistical significance (χ(2) = 7.74, P < 0.05). Comparing with the nonintervention group, the PR and IE in intervention group 1 was separately 84.2% and 6.31; while the capture rate was 69.2% (9/13).</p><p><b>CONCLUSION</b>The delimiting preventive medicine treatment during rest period of malaria was very effective for eliminating the potential infection source of malaria and reducing the morbidity of malaria.</p>

Adolescent , Adult , Aged , Animals , Child , Child, Preschool , China , Epidemiology , Culicidae , Physiology , Humans , Incidence , Infant , Infant, Newborn , Malaria , Drug Therapy , Epidemiology , Middle Aged , Water , Parasitology , Young Adult