Sea level nocturnal minimal oxygen saturation can accurately detect the presence of obstructive sleep apnea in a population with high pretest probability.

PURPOSE: To evaluate whether a predictive model based on nocturnal minimal oxygen saturation (SpO2) alone can accurately detect the presence of obstructive sleep apnea (OSA) in a population with suspected OSA. METHODS: A total of 4297 participants with suspected OSA were enrolled in this study, and laboratory-based polysomnography (PSG) tests were performed at sea level in all subjects. Nocturnal minimal SpO2 was obtained automatically as part of the PSG test. Stratified sampling was used to divide the participants' data into the training set (75%) and the test set (25%). An OSA detection model based on minimal SpO2 alone was created using the training set data and its performance was evaluated using the independent test set data ("hold-out" evaluation). Gender-specific models, and models based on minimal SpO2 in combination with other predictive factors (age, body mass index, waist-to-hip ratio, snoring grade, Epworth Sleepiness Scale score, and comorbidities), were also created and compared in terms of OSA detection performance. RESULTS: The prevalence of OSA was 85.6% in our study population. The models including multiple predictors, and the gender-specific models, failed to outperform the model based solely on minimal SpO2, which showed good predictive performance (C statistic, 0.922) having an overall accuracy rate of 0.86, sensitivity of 0.87, specificity of 0.84, positive predictive value of 0.97, and positive likelihood ratio of 5.34. In addition, the model based on minimal SpO2 alone could also accurately predict the presence of moderate-to-severe OSA and severe OSA, with C statistics of 0.914 and 0.900, respectively. CONCLUSIONS: A predictive model based on nocturnal minimal SpO2 alone may be an alternative option to detect the presence of OSA in a high-risk population when standard diagnostic tests are unavailable.

The association between obesity indices and obstructive sleep apnea is modified by age in a sex-specific manner.

BACKGROUND: The beneficial effects of weight reduction on obstructive sleep apnea (OSA) are highly variable. Whether or not the variability is associated with the effects of age and sex remains unclear. This study examined this issue with large cross-sectional data. METHOD: Anthropometric measurements, polysomnographic variables, biochemical indicators, and medical history were collected for each participant. Multivariable linear regression with interaction terms was used to estimate the modification effect of age on the associations between OSA severity (assessed by apnea-hypopnea index, AHI) with obesity indices (body mass index, BMI; neck circumference, NC; waist circumference, WC; waist-to-hip ratio, WHR) in a sex-specific manner, and vice versa. To facilitate interpretation of the results, participants were further classified into six subpopulations according to both sex and age, and population-specific beta-coefficients were calculated and compared. RESULTS: A total of 5756 adults (4600 men) with suspected OSA were included in the study. BMI, NC, WC, and WHR were all positively correlated with AHI after adjusting for potential confounders in all populations. In men, these associations were much stronger and more significant in younger than older individuals (P for interaction < 0.001). For example, a 10% increase in BMI was independently associated with a 32% increase in AHI for men < 40 years old, whereas the corresponding increases were 21% and 17% for men 40-60 and > 60 years old, respectively. By contrast, no modification effect of age was observed in women (P for interaction > 0.05). A 10% increase in BMI was associated with 26%, 27%, and 24% increases in AHI for women < 40, 40-60, and > 60 years old, respectively. CONCLUSIONS: Age modifies the associations between obesity indices and OSA severity in a sex-specific manner. These findings may broaden the understanding of age- and sex-related heterogeneities in the pathogenic role of obesity in OSA, and may be beneficial for individualized risk evaluation and treatment management for patients with OSA.

Interrelationships among common predictors of cardiovascular diseases in patients of OSA: A large-scale observational study.

BACKGROUND AND AIMS: The apolipoprotein B/apolipoprotein A-I (ApoB/ApoA-I) and insulin resistance has been recognized as common cardiovascular diseases (CVD) risk factors. However, whether they were biomarkers for 10-year CVD risk in obstructive sleep apnea (OSA) had been rarely studied. Besides, interrelationships between the ApoB/ApoA-I, insulin resistance and OSA remain unclear. METHODS AND RESULTS: A total of 4010 subjects were finally included. Anthropometric, fasting biochemical, and polysomnographic parameters were collected. 10-year Framingham CVD risk score (FRS) was calculated for each subjects. The relationships between insulin resistance, OSA risk and the ApoB/ApoA-I was evaluated through logistic regressions analysis, restricted cubic spline (RCS) analysis and mediation analysis. ApoB/ApoA-I, HOMA-IR and AHI were all risk factors for high10-year CVD risk as assessed by FRS (odds ratios (OR) = 5.365, 1.094, 1.010, respectively, all P < 0.001)). The fully adjusted OR (95% confidence intervals) for both OSA [1 (reference), 1.308 (1.027-1.665), 1.517 (1.178-1.953), and 1.803 (1.371-2.372)] and insulin resistance [1 (reference), 1.457 (1.173-1.711), 1.701 (1.369-2.113), 2.051(1.645-2.558)] increased from the first to the fourth quartiles of the ApoB/ApoA-I. The RCS mapped a nonlinear dose-effect relationship between the ApoB/ApoA-I and risk of insulin resistance and OSA. Mediation analyses showed HOMA-IR explain 9.7%, 4.7% and 10.8% of the association between apnea-hypopnea index, oxygen desaturation index, micro-arousal index and ApoB/ApoA-I, respectively. CONCLUSIONS: Our study revealed that ApoB/ApoA-I, insulin resistance and OSA were risk factors for CVD. Insulin resistance may serve as a potential mediator in OSA-related lipoprotein disorders and further increase CVD risk.

The use of visceral adiposity variables in the prediction of obstructive sleep apnea: evidence from a large cross-sectional study.

PURPOSE: The purposes of this study were to evaluate the ability of visceral adiposity variables [the lipid accumulation product (LAP), the visceral adiposity index (VAI), and the triglyceride-glucose index (TyG)] in predicting obstructive sleep apnea hypopnea syndrome (OSAHS) and to determine the effect of sex on the prediction. METHODS: A total of 5539 subjects admitted to the sleep center for suspected OSAHS were consecutively recruited from 2007 to 2016. Anthropometric measurements, biological indicators, Epworth sleepiness scale score, and polysomnographic variables were collected. Prediction models for diagnosing OSAHS were established in the test group by logistic regression and verified in the validation group by receiver operating characteristic (ROC) curves. RESULTS: A total of 4703 patients were included in total. LAP and TyG were of moderate diagnostic accuracy for OSAHS, with the diagnostic efficiency differing between men and women. A prediction model was developed that combined visceral adiposity indicators with waist circumstance and the lowest SpO2. The sensitivity of those indicators were both 84% in men and women, respectively, and their specificity were both 90%. In addition, the model was confirmed in the validation group with a sensitivity and specificity of 83% and 85% in men and 85% and 84% in women. CONCLUSIONS: LAP and TyG were of moderate efficiency in screening for OSAHS. The prediction model provides a simple and practical screening tool for OSAHS.

Excessive daytime sleepiness, metabolic syndrome, and obstructive sleep apnea: two independent large cross-sectional studies and one interventional study.

BACKGROUND: Obstructive sleep apnea (OSA) and excessive daytime sleepiness (EDS) were considered to contribute to MetS. This study was performed to assess the association between MetS and EDS in two independent large-scale populations, and in subjects who underwent upper-airway surgery. METHODS: A total of 6312 patients without self-reported depression and 3578 suspected OSA patients were consecutively recruited, during health screening examinations and from our sleep center, respectively. A total of 57 subjects with OSA who underwent upper-airway surgery were also included. Demographic, anthropometric, biochemical, and polysomnographic data were obtained. RESULTS: In the health screening examination group, 233 (9.23%) women and 350 (10.93%) men had complaints of EDS. A total of 229 (7.04%) women and 1182 (36.88%) men met the criteria for MetS. In the OSA group, 147 (21.18%) women and 1058 (36.69%) men reported EDS. In addition, 93 (13.4%) women and 1368 (47.43%) men reported MetS. In the health screening examination group, EDS did not contribute significantly to MetS (OR = 1.125, 95% CI: 0.907-1.395; p = 0.283). In the OSA group, EDS significantly contributed to MetS (OR = 1.249, 95% CI: 1.063-1.468; p = 0.007); however, the results were not significant after adjusting for sleep variables (OR = 1.071, 95% CI: 0.905-1.268; p = 0.423). Upper-airway surgery did not affect cardio-metabolic variables in OSA patients with or without EDS. CONCLUSIONS: EDS was not associated with MetS in two independent large-scale cohorts. In addition, upper-airway surgery did not affect components of MetS in OSA patients with and without EDS.

The association between obstructive sleep apnea syndrome and metabolic syndrome: a confirmatory factor analysis.

BACKGROUND: Growing evidence suggests an independent relationship between obstructive sleep apnea syndrome (OSAS) and metabolic syndrome (MS). Patients with OSAS always show clustering of metabolic components. However, the understanding of interplay between OSAS and metabolic components is still lacking. METHODS: Participants were consecutively enrolled from our sleep center during the period 2009-2013. Anthropometric variables, metabolic indicators, and sleep parameters were collected from all participants. The factor structure for MS in OSAS and non-OSAS was examined by confirmatory factor analysis. RESULTS: The OSAS and non-OSAS demonstrated clustering of metabolic components. MS in patients with OSAS was strongly associated with insulin resistance (standardized factor loading = 0.93, p < 0.001), obesity (loading = 0.92, p < 0.001), and the lipid profile (loading = 0.72, p < 0.001). Furthermore, insulin resistance was correlated with obesity and lipid profile (r = 0.86, p < 0.001; r = 0.68, p < 0.001, respectively). Obesity and lipid profile were also highly correlated in OSAS (r = 0.66, p < 0.001). In non-OSAS, MS was strongly associated with insulin resistance, obesity, and lipid profile (loading = 0.95, p < 0.001; loading = 0.74, p < 0.001; loading = 0.68, p < 0.001, respectively). Insulin resistance was most strongly associated with fasting insulin (loading = 0.65, p < 0.001). Lipid profile was most strongly associated with TG (loading = 0.88, p < 0.001). Obesity was most strongly associated with BMI (loading = 0.80, p < 0.001). CONCLUSIONS: OSAS is more prone to show clustering of metabolic components compared with non-OSAS. In particular, insulin resistance, obesity, and the lipid profile were independently and strongly correlated with MS in OSAS.

Development and validation of a simple-to-use clinical nomogram for predicting obstructive sleep apnea.

BACKGROUND: The high cost and low availability of polysomnography (PSG) limits the timely diagnosis of OSA. Herein, we developed and validated a simple-to-use nomogram for predicting OSA. METHODS: We collected and analyzed the cross-sectional data of 4162 participants with suspected OSA, seen at our sleep center between 2007 and 2016. Demographic, biochemical and anthropometric data, as well as sleep parameters were obtained. A least absolute shrinkage and selection operator (LASSO) regression model was used to reduce data dimensionality, select factors, and construct the nomogram. The performance of the nomogram was assessed using calibration and discrimination. Internal validation was also performed. RESULTS: The LASSO regression analysis identified age, sex, body mass index, neck circumference, waist circumference, glucose, insulin, and apolipoprotein B as significant predictive factors of OSA. Our nomogram model showed good discrimination and calibration in terms of predicting OSA, and had a C-index value of 0.839 according to the internal validation. Discrimination and calibration in the validation group was also good (C-index = 0.820). The nomogram identified individuals at risk for OSA with an area under the curve (AUC) of 0.84 [95% confidence interval (CI), 0.83-0.86]. CONCLUSIONS: Our simple-to-use nomogram is not intended to replace standard PSG, but will help physicians better make decisions on PSG arrangement for the patients referred to sleep center.

Association between N-Acetyltransferase 2 Polymorphism and Bladder Cancer Risk: a Meta-Analysis in a Single Ethnic Group.

BACKGROUND: Many studies have evaluated the correlation between N-acetyltransferase 2 (NAT2) slow acetylation genotype and bladder cancer risk. However, the results are inconsistent and remain to be confirmed in each ethnic group. To assess the effects of NAT2 acetylation status on the risk of bladder cancer in the Chinese population, a meta-analysis was performed. METHODS: Studies were identified using PubMed and Chinese databases through February 2016. The associations were assessed with pooled odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: This meta-analysis included 10 studies with 896 bladder cancer cases and 1188 controls. In the overall analysis, NAT2 slow acetylation phenotype was significantly associated with an increased risk of bladder cancer in the Chinese population (OR = 1.68, 95% CI = 1.11 - 2.53). In the subgroup analyses by geographic areas and sources of controls, significant risk was found in Mainland China (OR = 1.83, 95% CI = 1.04 - 3.20) and hospitalbased studies (OR = 1.74, 95% CI = 1.27 - 2.38), but not in Taiwan China. CONCLUSIONS: This meta-analysis suggested that the NAT2 slow acetylation genotype is associated with an increased bladder cancer risk in Chinese individuals.

Patients with Obstructive Sleep Apnea Display Decreased Flow-Mediated Dilatation: Evidence from a Meta-Analysis.

BACKGROUND Endothelial dysfunction, which can be measured by flow-mediated dilatation (FMD), is an early clinical marker of atherosclerosis, which is considered to be the main cause of the observed cardiovascular complications in obstructive sleep apnea (OSA) patients. The association between OSA and endothelial dysfunction has been reported in a number of studies; however, the findings are not entirely consistent. Our aim was to meta-analytically synthesize the existing evidence to explore the association between OSA and endothelial dysfunction. MATERIAL AND METHODS Data from PubMed, EMBASE, the Cochrane library, and Google Scholar for all trials that investigated the relationship between endothelial dysfunction and OSA were systematically reviewed. The minimum inclusion criteria for the studies were reporting of the Apnea-Hypopnea Index (AHI) and FMD measurements (as an indicator of endothelial dysfunction) for both OSA and control groups. Data from case-control studies that met the inclusion criteria were extracted. RESULTS Twenty-eight studies comprising a total of 1496 OSA patients and 1135 controls were included in the meta-analysis. A random-effects model was used. The weighted mean difference in the FMD measurements was -3.07 and the 95% confidence interval was -3.71 to -2.43 (P<0.01). Meta-regression analysis showed that age, sex, body mass index (BMI), blood pressure, glucose, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol did not explain the heterogeneity. CONCLUSIONS This meta-analysis showed that patients with OSA have decreased FMD, which may contribute to the development of atherosclerosis.

[Research Progress on the Role of Small Non-coding RNA in Schistosoma Infection].

Small non-coding RNA controls the expression of target genes and is related with mRNA degradation, chromatin modification and genome stability. Recent studies showed that small non-coding RNA is not only associated with the incidence of schistosomiasis, but also acts as a potential biomarker. In this article, we will review the applications of small non-coding RNA in schistosomiasis diagnosis and its potential role in schistosome development and pathogenesis, in the aim to provide hints for developing detection methods and vaccines for schistosomiasis and for drug development.

[Endemic situation and control progress of taeniasis in western China].

Taeniasis, caused by Taenia species, is one of the common zoonoses in China, particularly in the western region of China. Up to now, not enough attention has been given in the high prevalence and high burden of the diseases. In order to study the endemic patterns and control strategies of taeniasis, a series of epidemiological investigations, molecular researches and pilot control activities have been conducted in recent years. This paper reviews the relevant publications in taeniasis research over the last 10 years.

[Risk assessment for malaria elimination in P. R. China].

OBJECTIVE: To identify the risk area in China during the malaria elimination process, and provide the evidence for promotion of the national malaria elimination programme and implementation of elimination strategy. METHODS: Data collection was conducted in 24 endemic provinces in 2010, including data of transmission capacity, potential risk of malaria transmission and the capacity of health professional team at county level. Quantitative assessment of the malaria transmission risk as well as the capacity of health facilities were conducted based on the calculation of malaria transmission risk index (MTI) and health facilities capacity index (CI). ArcGIS 10.0 was used to develop the risk map based on the outcome of quantitative assessment. RESULTS: The data of transmission capacity, potential risk of transmission and the capacity of health professional team were collected from 2147 counties in 24 provinces. Based on MTI and CI calculated for each county, statistic results showed that about 40% of the counties were under the average level of both MTI and CI. The relationship among potential risk of transmission, the capacity of health professional team and malaria incidence were analyzed in three dimensions, and four types were categorized among 2147 counties. Type I (super-high risk area) counties (20) distributed in Yunnan (9), Guangxi (5), Henan (1), Hunan (1), Hebei (1), Sichuan (1), Chongqing (1), and Tibet (1). 17 counties were classified into type II (high risk area) area, distributed in Yunnan (3), Guangxi (2), Guizhou (2), Shaanxi (2), Guangdong (1), Jiangxi (1), Hubei (1), Sichuan (1), Gansu (1), Hebei (1), Fujian (1) and Tibet (1). A total of 170 type III (moderate risk area) counties distributed in 19 provinces including Yunnan (15), Guizhou (14), Hebei (14), Sichuan (13), Shanxi (10), Guangxi (9), Hunan (9), Anhui (9), Jiangsu (9), Shaanxi (9), Shandong (9), Chongqing (8), Gansu (8), Jiangxi (7), Henan (7), Fujian (6), Guangdong (5), Hubei (5), and Zhejiang (4). 1940 type IV (low risk area) counties distributed in 24 provinces. CONCLUSION: The distribution of four types of risk area for malaria elimination is identified in China.

[Application of space-time scan statistics in the analysis of spatial and temporal distribution of Oncomelania hupensis snails in Gaoyou County, Jiangsu Province].

OBJECTIVE: To investigate the distribution features of Oncomelania hupensis infested areas in Gaoyou County so as to formulate surveillance and intervention strategies. METHODS: A database was established through collecting data of the snail infested areas during 1970-2009 in the County. The data were input into SaTScan 9.2 software for spatial-temporal cluster analysis to determine the spatial and temporal cluster of the snail habitats. The results were displayed by ArcGIS 10.1 software. RESULTS: There were historically 720 snail habitats in the County in 1970-2009 including 521 in plain region with water networks and 199 in lake & marshland region. Those in water networks covered an area of 456.62 ha distributing mainly in the northern towns/townships of the County, and the latters distributed in the Xinmin Beach between Gaoyou Lake and Shaobo Lake, and Qiaojian Beach close to Tianchang County of Anhui Province with an area of 4 495.75 ha. The spatial-temporal cluster analysis revealed that among all the historical snail habitats, there were two prominent spatial-temporal clusters with a relative risk of >3. One cluster appeared in Xinmin Beach in 1983-2002 and another one located in the north of Gaoyou in 1970-1973. Separate analysis was performed by the regions of water network or lake & marshland, indicating 2 clusters in each of the regions. During 1970-2009, 244 snail habitats were newly found in the County with 130 in water network region and 114 in lake & marshland region. Again, the spatial-temporal cluster analysis displayed 2 prominent clusters. By separate analysis, 2 clusters existed in each of the regions. CONCLUSION: The space-time scan statistics can be applied in detecting the cluster of snail infested areas in two dimensions, which will provide information for guiding specific measures of surveillance and control.

[Design and implementation of command system for emergency events of parasitic diseases].

Based on the requirement analysis and functional design of the command system for parasitic disease outbreaks, the system was constructed by workflow technique, function modules and technical architecture. The command system was a multi-platform system, could achieve multiple functions, such as monitoring and early warning of parasitic diseases, emergency video communication, emergency dispatcher, and emergency management. The system can meet the needs in emergency events of parasitic diseases, and increase preparedness level.

Schistosomiasis transmission in Zimbabwe: Modelling based on machine learning.

Zimbabwe, located in Southern Africa, faces a significant public health challenge due to schistosomiasis. We investigated this issue with emphasis on risk prediction of schistosomiasis for the entire population. To this end, we reviewed available data on schistosomiasis in Zimbabwe from a literature search covering the 1980-2022 period considering the potential impact of 26 environmental and socioeconomic variables obtained from public sources. We studied the population requiring praziquantel with regard to whether or not mass drug administration (MDA) had been regularly applied. Three machine-learning algorithms were tested for their ability to predict the prevalence of schistosomiasis in Zimbabwe based on the mean absolute error (MAE), the root mean squared error (RMSE) and the coefficient of determination (R2). The findings revealed different roles of the 26 factors with respect to transmission and there were particular variations between Schistosoma haematobium and S. mansoni infections. We found that the top-five correlation factors, such as the past (rather than current) time, unsettled MDA implementation, constrained economy, high rainfall during the warmest season, and high annual precipitation were closely associated with higher S. haematobium prevalence, while lower elevation, high rainfall during the warmest season, steeper slope, past (rather than current) time, and higher minimum temperature in the coldest month were rather related to higher S. mansoni prevalence. The random forest (RF) algorithm was considered as the formal best model construction method, with MAE = 0.108; RMSE = 0.143; and R2 = 0.517 for S. haematobium, and with the corresponding figures for S. mansoni being 0.053; 0.082; and 0.458. Based on this optimal model, the current total schistosomiasis prevalence in Zimbabwe under MDA implementation was 19.8%, with that of S. haematobium at 13.8% and that of S. mansoni at 7.1%, requiring annual MDA based on a population of 3,003,928. Without MDA, the current total schistosomiasis prevalence would be 23.2%, that of S. haematobium 17.1% and that of S. mansoni prevalence at 7.4%, requiring annual MDA based on a population of 3,521,466. The study reveals that MDA alone is insufficient for schistosomiasis elimination, especially that due to S. mansoni. This study predicts a moderate prevalence of schistosomiasis in Zimbabwe, with its elimination requiring comprehensive control measures beyond the currently used strategies, including health education, snail control, population surveillance and environmental management.

[Establishment of policy indicators of adaptation to the impact of climate change on the transmission of schistosomiasis and malaria in China].

OBJECTIVE: To set up a framework of indicators for schistosomiasis and malaria to guide the formulation and evaluation of vector-borne disease control policies focusing on adaptation to the negative impact of climate change. METHODS: A 2-level indicator framework was set up on the basis of literature review, and Delphi method was applied to a total of 22 and 19 experts working on schistosomiasis and malaria, respectively. The result was analyzed to calculate the weight of various indicators. RESULTS: A total of 41 questionnaires was delivered, and 38 with valid response (92.7%). The system included 4 indicators at first level, i.e. surveillance, scientific research, disease control and intervention, and adaptation capacity building, with 25 indicators for schistosomiasis and 21 for malaria at the second level. Among indicators at the first level, disease surveillance ranked first with a weight of 0.32. Among the indicators at the second level, vector monitoring scored the highest in terms of both schistosomiasis and malaria. CONCLUSION: The indicators set up by Delphi method are practical,universal and effective ones using in the field, which is also useful to technically support the establishment of adaptation to climate change in the field of public health.

[Rapid risk assessment on the import of American trypanosomiasis to China].

American trypanosomiasis, as one of the "neglected tropical diseases", is a zoonosis induced by Trypanosoma cruzi. It is endemic in 18 countries in the Central and South America, especially in rural areas. A rapid risk assessment was carried out to analyze the potential threat of imported cases to China, which would provide information to policy makers in health authorities.

The Global Spread Pattern of Rat Lungworm Based on Mitochondrial Genetics.

Eosinophilic meningitis due to rat lungworm, Angiostrongylus cantonensis, is a global public health concern. Human cases and outbreaks have occurred in the new endemic areas, including South America and Spain. The growing genetic data of A. cantonensis provides a unique opportunity to explore the global spread pattern of the parasite. Eight more mitochondrial (mt) genomes were sequenced by the present study. The phylogeny of A. cantonensis by Bayesian inference showed six clades (I-VI) determined by network analysis. A total of 554 mt genomes or fragments, which represented 1472 specimens of rat lungworms globally, were used in the present study. We characterized the gene types by mapping a variety of mt gene fragments to the known complete mt genomes. Six more clades (I2, II2, III2, V2, VII and VIII) were determined by network analysis in the phylogenies of cox1 and cytb genes. The global distribution of gene types was visualized. It was found that the haplotype diversity of A. cantonensis in Southeast and East Asia was significantly higher than that in other regions. The majority (78/81) of samples beyond Southeast and East Asia belongs to Clade II. The new world showed a higher diversity of Clade II in contrast with the Pacific. We speculate that rat lungworm was introduced from Southeast Asia rather than the Pacific. Therefore, systematic research should be conducted on rat lungworm at a global level in order to reveal the scenarios of spread.

Evaluation of an Innovative Point-of-Care Rapid Diagnostic Test for the Identification of Imported Malaria Parasites in China.

BACKGROUND: China was certified malaria-free by the World Health Organization on 30 June 2021. However, due to imported malaria, maintaining a malaria-free status in China is an ongoing challenge. There are critical gaps in the detection of imported malaria through the currently available tools, especially for non-falciparum malaria. In the study, a novel point-of-care Rapid Diagnostic Test designed for the detection of imported malaria infections was evaluated in the field. METHODS: Suspected imported malaria cases reported from Guangxi and Anhui Provinces of China during 2018-2019 were enrolled to evaluate the novel RDTs. Diagnostic performance of the novel RDTs was evaluated based on its sensitivity, specificity, positive and negative predictive values, and Cohen's kappa coefficient, using polymerase chain reaction as the gold standard. The Additive and absolute Net Reclassification Index were calculated to compare the diagnostic performance between the novel RDTs and Wondfo RDTs (control group). RESULTS: A total of 602 samples were tested using the novel RDTs. Compared to the results of PCR, the novel RDTs presented sensitivity, specificity, PPV, NPV, and diagnostic accuracy rates of 78.37%, 95.05%, 94.70%, 79.59%, and 86.21%, respectively. Among the positive samples, the novel RDTs found 87.01%, 71.31%, 81.82%, and 61.54% of P. falciparum, P. ovale, P. vivax, and P. malariae, respectively. The ability to detect non-falciparum malaria did not differ significantly between the novel and Wondfo RDTs (control group). However, Wondfo RDTs can detect more P. falciparum cases than the novel RDTs (96.10% vs. 87.01%, p < 0.001). After the introduction of the novel RDTs, the value of the additive and absolute Net Reclassification Index is 1.83% and 1.33%, respectively. CONCLUSIONS: The novel RDTs demonstrated the ability to distinguish P. ovale and P. malariae from P. vivax which may help to improve the malaria post-elimination surveillance tools in China.

Isolation and characterization of 15 new microsatellite markers in Oncomelania hupensis, the snail intermediate host of Schistosoma japonicum in mainland China.

Oncomelania hupensis is the unique intermediate host of Schistosoma japonicum, which plays a key role during the transmission of schistosomiasis. It is mainly found in the Yangtze River valley and mountains or hills in southwest China. In this paper, we described 15 new microsatellite makers in O. hupensis. Polymorphism of each locus was assessed in 80 individuals from four wild populations (n = 20 per population). The number of alleles per locus ranged from 6 to 29, with an average of 15.8. The observed (H(O)) and expected (H(E)) heterozygosities varied from 0.397 to 0.851 and from 0.696 to 0.948, respectively. These microsatellite markers will be useful for population genetic studies and genome mapping in O. hupensis.