Mid-gestation intra-amniotic infection with Ureaplasma parvum is resolved within spiny mice (Acomys cahirinus) by term delivery: but caused chronic infection of fetal lungs and placentae

Background: Ureaplasma species in amniotic fluid at the time of second-trimester amniocentesis increases the risk of preterm birth, but most affected pregnancies continue to term (Gerber et al. J Infect Dis 2003). We aimed to model intra-amniotic (IA) ureaplasma infection in spiny mice, a species with a relatively long gestation (39 days) that allows investigation of the disposition and possible clearance of ureaplasmas in the feto-placental compartment. Method: Pregnant spiny mice received IA injections of U. parvum serovar 6 (10µL, 1x104 colony-forming-units in PBS) or 10B media (10µL; control) at 20 days (d) of gestation (term=39d). At 37d fetuses (n=3 ureaplasma, n=4 control) were surgically delivered and tissues were collected for; bacterial culture, ureaplasma mba and urease gene expression by PCR, tissue WBC counts and indirect fluorescent antibody (IFA) staining using anti-ureaplasma serovar 6 (rabbit) antiserum. Maternal and fetal plasma IgG was measured by Western blot. Results: Ureaplasmas were not detected by culture or PCR in fetal or maternal tissues but were visualized by IFA within placental and fetal lung tissues, in association with inflammatory changes and elevated WBC counts (p<0.0001). Anti-ureaplasma IgG was detected in maternal (2/2 tested) and fetal (1/2 tested) plasma but not in controls (0/3). Conclusions: IA injection of ureaplasmas in mid-gestation spiny mice caused persistent fetal lung and placental infection even though ureaplasmas were undetectable using standard culture or PCR techniques. This is consistent with resolution of IA infection, which may occur in human pregnancies that continue to term despite detection of ureaplasmas in mid-gestation.

Reply - Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality

Dear Editor We thank Dr Klek for his interest in our article and giving us the opportunity to clarify our study and share our thoughts. Our study looks at the prevalence of malnutrition in an acute tertiary hospital and tracked the outcomes prospectively.1 There are a number of reasons why we chose Subjective Global Assessment (SGA) to determine the nutritional status of patients. Firstly, we took the view that nutrition assessment tools should be used to determine nutrition status and diagnose presence and severity of malnutrition; whereas the purpose of nutrition screening tools are to identify individuals who are at risk of malnutrition. Nutritional assessment rather than screening should be used as the basis for planning and evaluating nutrition interventions for those diagnosed with malnutrition. Secondly, Subjective Global Assessment (SGA) has been well accepted and validated as an assessment tool to diagnose the presence and severity of malnutrition in clinical practice.2, 3 It has been used in many studies as a valid prognostic indicator of a range of nutritional and clinical outcomes.4, 5, 6 On the other hand, Malnutrition Universal Screening Tool (MUST)7 and Nutrition Risk Screening 2002 (NRS 2002)8 have been established as screening rather than assessment tools.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

Extremely cold and hot temperatures increase the risk of ischaemic heart disease mortality : epidemiological evidence from China

Objective: To examine the effects of extremely cold and hot temperatures on ischaemic heart disease (IHD) mortality in five cities (Beijing, Tianjin, Shanghai, Wuhan and Guangzhou) in China; and to examine the time relationships between cold and hot temperatures and IHD mortality for each city. Design: A negative binomial regression model combined with a distributed lag non-linear model was used to examine city-specific temperature effects on IHD mortality up to 20 lag days. A meta-analysis was used to pool the cold effects and hot effects across the five cities. Patients: 16 559 IHD deaths were monitored by a sentinel surveillance system in five cities during 2004–2008. Results: The relationships between temperature and IHD mortality were non-linear in all five cities. The minimum-mortality temperatures in northern cities were lower than in southern cities. In Beijing, Tianjin and Guangzhou, the effects of extremely cold temperatures were delayed, while Shanghai and Wuhan had immediate cold effects. The effects of extremely hot temperatures appeared immediately in all the cities except Wuhan. Meta-analysis showed that IHD mortality increased 48% at the 1st percentile of temperature (extremely cold temperature) compared with the 10th percentile, while IHD mortality increased 18% at the 99th percentile of temperature (extremely hot temperature) compared with the 90th percentile. Conclusions: Results indicate that both extremely cold and hot temperatures increase IHD mortality in China. Each city has its characteristics of heat effects on IHD mortality. The policy for response to climate change should consider local climate–IHD mortality relationships.

Accelerometer-based fetal movement detection

Monitoring fetal wellbeing is a compelling problem in modern obstetrics. Clinicians have become increasingly aware of the link between fetal activity (movement), well-being, and later developmental outcome. We have recently developed an ambulatory accelerometer-based fetal activity monitor (AFAM) to record 24-hour fetal movement. Using this system, we aim at developing signal processing methods to automatically detect and quantitatively characterize fetal movements. The first step in this direction is to test the performance of the accelerometer in detecting fetal movement against real-time ultrasound imaging (taken as the gold standard). This paper reports first results of this performance analysis.

Mortality and cost outcomes of elderly trauma patients admitted to intensive care and the general wards of an Australian tertiary referral hospital

Mortality and cost outcomes of elderly intensive care unit (ICU) trauma patients were characterised in a retrospective cohort study from an Australian tertiary ICU. Trauma patients admitted between January 2000 and December 2005 were grouped into three major age categories: aged ≥65 years admitted into ICU (n=272); aged ≥65 years admitted into general ward (n=610) and aged <65 years admitted into ICU (n=1617). Hospital mortality predictors were characterised as odds ratios (OR) using logistic regression. The impact of predictor variables on (log) total hospital-stay costs was determined using least squares regression. An alternate treatment-effects regression model estimated the mortality cost-effect as an endogenous variable. Mortality predictors (P ≤0.0001, comparator: ICU ≥65 years, ventilated) were: ICU <65 not-ventilated (OR 0.014); ICU <65 ventilated (OR 0.090); ICU age ≥65 not-ventilated (OR 0.061) and ward ≥65 (OR 0.086); increasing injury severity score and increased Charlson comorbidity index of 1 and 2, compared with zero (OR 2.21 [1.40 to 3.48] and OR 2.57 [1.45 to 4.55]). The raw mean daily ICU and hospital costs in A$ 2005 (US$) for age <65 and ≥65 to ICU, and ≥65 to the ward were; for year 2000: ICU, $2717 (1462) and $2777 (1494); hospital, $1837 (988) and $1590 (855); ward $933 (502); for year 2005: ICU, $3202 (2393) and $3086 (2307); hospital, $1938 (1449) and $1914 (1431); ward $1180 (882). Cost increments were predicted by age ≥65 and ICU admission, increasing injury severity score, mechanical ventilation, Charlson comorbidity index increments and hospital survival. Mortalitycost-effect was estimated at -63% by least squares regression and -82% by treatment-effects regression model. Patient demographic factors, injury severity and its consequences predict both cost and survival in trauma. The cost mortality effect was biased upwards by conventional least squares regression estimation.

Repeated intrauterine exposures to inflammatory stimuli attenuated transforming growth factor-β signaling in the ovine fetal lung

Background: Bronchopulmonary dysplasia (BPD) is one of the most common complications after preterm birth and is associated with intrauterine exposure to bacteria. Transforming growth factor-β (TGFβ) is implicated in the development of BPD. Objectives: We hypothesized that different and/or multiple bacterial signals could elicit divergent TGFβ signaling responses in the developing lung. Methods: Time-mated pregnant Merino ewes received an intra-amniotic injection of lipopolysaccharide (LPS) and/or Ureaplasma parvum serovar 3 (UP) at 117 days' and/or 121/122 days' gestational age (GA). Controls received an equivalent injection of saline and or media. Lambs were euthanized at 124 days' GA (term = 150 days' GA). TGFβ1, TGFβ2, TGFβ3, TGFβ receptor (R)1 and TGFβR2 protein levels, Smad2 phosphorylation and elastin deposition were evaluated in lung tissue. Results: Total TGFβ1 and TGFβ2 decreased by 24 and 51% after combined UP+LPS exposure, whereas total TGFβ1 increased by 31% after 7 days' LPS exposure but not after double exposures. Alveolar expression of TGFβR2 decreased 75% after UP, but remained unaltered after double exposures. Decreased focal elastin deposition after single LPS exposure was prevented by double exposures. Conclusions: TGFβ signaling components and elastin responded differently to intrauterine LPS and UP exposure. Multiple bacterial exposures attenuated TGFβ signaling and normalized elastin deposition.

Spatiotemporal model or time series model for assessing city-wide temperature effects on mortality?

Most studies examining the temperature–mortality association in a city used temperatures from one site or the average from a network of sites. This may cause measurement error as temperature varies across a city due to effects such as urban heat islands. We examined whether spatiotemporal models using spatially resolved temperatures produced different associations between temperature and mortality compared with time series models that used non-spatial temperatures. We obtained daily mortality data in 163 areas across Brisbane city, Australia from 2000 to 2004. We used ordinary kriging to interpolate spatial temperature variation across the city based on 19 monitoring sites. We used a spatiotemporal model to examine the impact of spatially resolved temperatures on mortality. Also, we used a time series model to examine non-spatial temperatures using a single site and the average temperature from three sites. We used squared Pearson scaled residuals to compare model fit. We found that kriged temperatures were consistent with observed temperatures. Spatiotemporal models using kriged temperature data yielded slightly better model fit than time series models using a single site or the average of three sites' data. Despite this better fit, spatiotemporal and time series models produced similar associations between temperature and mortality. In conclusion, time series models using non-spatial temperatures were equally good at estimating the city-wide association between temperature and mortality as spatiotemporal models.

Assessing the short-term effects of heatwaves on mortality and morbidity in Brisbane, Australia : comparison of case-crossover and time series analyses

Background Heat-related impacts may have greater public health implications as climate change continues. It is important to appropriately characterize the relationship between heatwave and health outcomes. However, it is unclear whether a case-crossover design can be effectively used to assess the event- or episode-related health effects. This study examined the association between exposure to heatwaves and mortality and emergency hospital admissions (EHAs) from non-external causes in Brisbane, Australia, using both case-crossover and time series analyses approaches. Methods Poisson generalised additive model (GAM) and time-stratified case-crossover analyses were used to assess the short-term impact of heatwaves on mortality and EHAs. Heatwaves exhibited a significant impact on mortality and EHAs after adjusting for air pollution, day of the week, and season. Results For time-stratified case-crossover analysis, odds ratios of mortality and EHAs during heatwaves were 1.62 (95% confidence interval (CI): 1.36–1.94) and 1.22 (95% CI: 1.14–1.30) at lag 1, respectively. Time series GAM models gave similar results. Relative risks of mortality and EHAs ranged from 1.72 (95% CI: 1.40–2.11) to 1.81 (95% CI: 1.56–2.10) and from 1.14 (95% CI: 1.06–1.23) to 1.28 (95% CI: 1.21–1.36) at lag 1, respectively. The risk estimates gradually attenuated after the lag of one day for both case-crossover and time series analyses. Conclusions The risk estimates from both case-crossover and time series models were consistent and comparable. This finding may have implications for future research on the assessment of event- or episode-related (e.g., heatwave) health effects.

Effects of temperature on mortality in Chiang Mai city, Thailand : a time series study

Background The association between temperature and mortality has been examined mainly in North America and Europe. However, less evidence is available in developing countries, especially in Thailand. In this study, we examined the relationship between temperature and mortality in Chiang Mai city, Thailand, during 1999–2008. Method A time series model was used to examine the effects of temperature on cause-specific mortality (non-external, cardiopulmonary, cardiovascular, and respiratory) and age-specific non-external mortality (<=64, 65–74, 75–84, and > =85 years), while controlling for relative humidity, air pollution, day of the week, season and long-term trend. We used a distributed lag non-linear model to examine the delayed effects of temperature on mortality up to 21 days. Results We found non-linear effects of temperature on all mortality types and age groups. Both hot and cold temperatures resulted in immediate increase in all mortality types and age groups. Generally, the hot effects on all mortality types and age groups were short-term, while the cold effects lasted longer. The relative risk of non-external mortality associated with cold temperature (19.35°C, 1st percentile of temperature) relative to 24.7°C (25th percentile of temperature) was 1.29 (95% confidence interval (CI): 1.16, 1.44) for lags 0–21. The relative risk of non-external mortality associated with high temperature (31.7°C, 99th percentile of temperature) relative to 28°C (75th percentile of temperature) was 1.11 (95% CI: 1.00, 1.24) for lags 0–21. Conclusion This study indicates that exposure to both hot and cold temperatures were related to increased mortality. Both cold and hot effects occurred immediately but cold effects lasted longer than hot effects. This study provides useful data for policy makers to better prepare local responses to manage the impact of hot and cold temperatures on population health.

Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality

Background & aims The confounding effect of disease on the outcomes of malnutrition using diagnosis-related groups (DRG) has never been studied in a multidisciplinary setting. This study aims to determine the impact of malnutrition on hospitalisation outcomes, controlling for DRG. Methods Subjective Global Assessment was used to assess the nutritional status of 818 patients within 48 hours of admission. Prospective data were collected on cost of hospitalisation, length of stay (LOS), readmission and mortality up to 3 years post-discharged using National Death Register data. Mixed model analysis and conditional logistic regression matching by DRG were carried out to evaluate the association between nutritional status and outcomes, with the results adjusted for gender, age and race. Results Malnourished patients (29%) had longer hospital stays (6.9±7.3 days vs. 4.6±5.6 days, p<0.001) and were more likely to be readmitted within 15 days (adjusted relative risk = 1.9, 95%CI 1.1–3.2, p=0.025). Within a DRG, the mean difference between actual cost of hospitalisation and the average cost for malnourished patients was greater than well-nourished patients (p=0.014). Mortality was higher in malnourished patients at 1 year (34% vs. 4.1 %), 2 years (42.6% vs. 6.7%) and 3 years (48.5% vs. 9.9%); p<0.001 for all. Overall, malnutrition was a significant predictor of mortality (adjusted hazard ratio = 4.4, 95%CI 3.3-6.0, p<0.001). Conclusions Malnutrition was evident in up to one third of inpatients and led to poor hospitalisation outcomes, even after matching for DRG. Strategies to prevent and treat malnutrition in the hospital and post-discharge are needed.

An analysis on trend of malignancies incidence and mortality in Linqu County, Shandong Province [山东省临朐县恶性肿瘤发病与 死亡趋势分析]

Purpose To investigate the trend of malignancies incidence and mortality in Linqu county, and to provide scientific evidence for the government to design and adjust polices on cancer prevention and control. [Methods] The cancer registration data of new cases from 1995 to 2004 and death cases from 1998 to 2004 were used to analyse the incidence and mortality and the trend in Linqu county. Results Cancer general incidence significantly increased from 1995 to 2004 (P<0.05). The increasing speed incidence in male was faster than that in female. The incidence of lung cancer, colon/rectum cancer and pancreas cancer increased significantly (P<0.05), especially of lung cancer with an acceleration incidence rate of 2.12/100,000 peryear in average. The general mortality increased gradually from 1998 to 2004 with no significance (P>0.05). Both incidence and mortality in population aged 80 or over increased significantly (P<0.05). Conclusion The cancer incidence is rising during recent 10 years , and the prevention and control for lung cancer are getting increasingly important. [目的] 了解临朐县恶性肿瘤发病与死亡趋势,为政府制订和调整防治对策提供科学依据. [方法] 利用临朐县1995～2004年恶性肿瘤发病登记资料和1998～2004年的死亡登记资料,计算各种癌症发病率和死亡率,并做趋势分析. [结果] 1995～2004年临朐县恶性肿瘤总发病率呈明显上升趋势(P＜0.05),男性发病率上升速度高于女性.肺癌、肠癌、胰腺癌发病率上升显著(P＜0.05),以肺癌最为迅速(年均升高2.12/10万).1998～2004年恶性肿瘤总死亡率略有上升,但无显著性(P＞0.05);80岁及以上人群恶性肿瘤发病率与死亡率均呈上升趋势. [结论] 临朐县恶性肿瘤发病率近10年来呈现上升趋势,肺癌防治地位日益突出.