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6 results on '"Kung-Ping Lin"'

1. Genetic Differentiation and Demographic Trajectory of the Insular Formosan and Orii’s Flying Foxes

Author

Hsi Chi Cheng, Kung Ping Lin, Shiang Fan Chen, Wen Ya Ko, Yoko Satta, Quintin Liu, Shu-Miaw Chaw, Chien Yi Tung, Teruo Kinjo, Yun Hwa Lo, and Masako Izawa

Subjects
0106 biological sciences, 0301 basic medicine, Conservation genetics, AcademicSubjects/SCI01140, Demographic history, Pteropus dasymallus, Population, Taiwan, Zoology, Jhered/1, RADSeq, 010603 evolutionary biology, 01 natural sciences, 03 medical and health sciences, Genetics, Flying fox (fish), Ryukyu Islands, education, Molecular Biology, Genetics (clinical), education.field_of_study, biology, Small population size, Original Articles, biology.organism_classification, Pteropodidae, Population decline, 030104 developmental biology, conservation genetics, Genetic structure, Biotechnology
Abstract

Insular flying foxes are keystone species in island ecosystems due to their critical roles in plant pollination and seed dispersal. These species are vulnerable to population decline because of their small populations and low reproductive rates. The Formosan flying fox (Pteropus dasymallus formosus) is one of the 5 subspecies of the Ryukyu flying fox. Pteropus dasymallus formosus has suffered from a severe decline and is currently recognized as a critically endangered population in Taiwan. On the contrary, the Orii’s flying fox (Pteropus dasymallus inopinatus) is a relatively stable population inhabiting Okinawa Island. Here, we applied a genomic approach called double digest restriction-site associated DNA sequencing to study these 2 subspecies for a total of 7 individuals. We detected significant genetic structure between the 2 populations. Despite their contrasting contemporary population sizes, both populations harbor very low degrees of genetic diversity. We further inferred their demographic history based on the joint folded site frequency spectrum and revealed that both P. d. formosus and P. d. inopinatus had maintained small population sizes for a long period of time after their divergence. Recently, these populations experienced distinct trajectories of demographic changes. While P. d. formosus suffered from a drastic ~10-fold population decline not long ago, P. d. inopinatus underwent a ~4.5-fold population expansion. Our results suggest separate conservation management for the 2 populations—population recovery is urgently needed for P. d. formosus while long-term monitoring for adverse genetic effects should be considered for P. d. inopinatus.

Published
2021

2. Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People

Author

Chen-Yang Shen, Mei-Ling Kang, Shu-Miaw Chaw, Chia-Ni Hsiung, Chun-Yu Chen, Yun-Hua Lo, Hou-Wei Chu, Chien-Hsiun Chen, Yoko Satta, Chiao-Feng Lin, Jun-Hun Loo, Mei Hsuan Lee, Chia-Wei Peng, Han-Yu Wang, Marie Lin, Cheng-Jui Lin, Kung-Ping Lin, Show-Ling Yang, Quintin Liu, Wen Ya Ko, and Hsueh-Chien Cheng

Subjects
Candidate gene, Genetic genealogy, Population, adaptation, Biology, Southeast asian, AcademicSubjects/SCI01180, 03 medical and health sciences, 0302 clinical medicine, Genetics, education, Molecular Biology, Genotyping, Ecology, Evolution, Behavior and Systematics, Discoveries, 030304 developmental biology, 0303 health sciences, education.field_of_study, Natural selection, ancestry, Taiwanese Han, Haplotype, AcademicSubjects/SCI01130, natural selection, Evolutionary biology, admixture, Adaptation, 030217 neurology & neurosurgery
Abstract

The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.

Published
2020

3. Renal function is associated with 1-month and 1-year mortality in patients with ischemic stroke

Author

I-Kuan Wang, Chung-Hsiang Liu, Tzung-Hai Yen, Jiann-Shing Jeng, Sheng-Feng Sung, Pai-Hao Huang, Jie-Yuan Li, Yu Sun, Cheng-Yu Wei, Li-Ming Lien, I-Ju Tsai, Fung-Chang Sung, Chung Y. Hsu, Chon-Haw Tsai, Wei-Shih Huang, Chung-Ta Lu, Tzung-Chang Tsai, Chun-Hung Tseng, Kang-Hsu Lin, Woei-Cherng Shyu, Yu-Wan Yang, Yen-Liang Liu, Der-Yang Cho, Chun-Chung Chen, Sung-Chun Tang, Li-Kai Tsai, Shin-Joe Yeh, Chih-Hao Chen, Hsin-Hsi Tsai, Han-Jung Chen, Kan Lu, Shih-Pin Hsu, Hung-Chang Kuo, Jung-Chi Tsou, Yan-Tang Wang, Yi-Cheng Tai, Meng-Tsang Hsieh, Po-Chao Liliang, Cheng-Loong Liang, Hao-Kuang Wang, Yu-Tun Tsai, Kuo-Wei Wang, Jui-Sheng Chen, Po-Yuan Chen, Yi-Ching Wang, Chih-Hung Chen, Pi-Shan Sung, Han-Chieh Hsieh, Hui-Chen Su, Hou-Chang Chiu, Wei-Hung Chen, Chyi-Huey Bai, Tzu-Hsuan Huang, Chi-Ieong Lau, Ya-Ying Wu, Hsu-Ling Yeh, Anna Chang, Ching-Huang Lin, Cheng-Chang Yen, Ruey-Tay Lin, Chun-Hung Chen, Gim-Thean Khor, A-Ching Chao, Hsiu-Fen Lin, Poyin Huang, Huey-Juan Lin, Der-Shin Ke, Chia-Yu Chang, Poh-Shiow Yeh, Kao-Chang Lin, Tain-Junn Cheng, Chih-Ho Chou, Chun-Ming Yang, Hsiu-Chu Shen, An-Chih Chen, Shih-Jei Tsai, Tsong-Ming Lu, Sheng-Ling Kung, Mei-Ju Lee, Hsi-Hsien Chou, Wei-Lun Chang, Pai-Yi Chiu, Min-Hsien Hsu, Po-Chi Chan, Chau-Hsiung Pan, Hai-Ming Shoung, Yi-Chen Lo, Fu-Hwa Wang, Wei-Chieh Chang, Ta-Chang Lai, Jiu-Haw Yin, Chung-Jen Wang, Kai-Chen Wang, Li-Mei Chen, Jong-Chyou Denq, Chien-Jung Lu, Cheng-Huai Lin, Chieh-Cheng Huang, Chang-Hsiu Liu, Hoi-Fong Chan, Siu-Pak Lee, Ming-Hui Sun, Li-Ying Ke, Po-Lin Chen, Yu-Shan Lee, Cheung-Ter Ong, Chi-Shun Wu, Yung-Chu Hsu, Yu-Hsiang Su, Ling-Chien Hung, Jiunn-Tay Lee, Jiann-Chyun Lin, Yaw-Don Hsu, Giia-Sheun Peng, Chang-Hung Hsu, Chun-Chieh Lin, Che-Hung Yen, Chun-An Cheng, Yueh-Feng Sung, Yuan-Liang Chen, Ming-Tung Lien, Chung-Hsing Chou, Chia-Chen Liu, Fu-Chi Yang, Yi-Chung Wu, An-Chen Tso, Yu- Hua Lai, Chun-I. Chiang, Chia-Kuang Tsai, Meng-Ta Liu, Ying-Che Lin, Yu-Chuan Hsu, Tsuey-Ru Chiang, Pin-Wen Liao, Mei-Ching Lee, Jen-Tse Chen, Sian-King Lie, Mu-Chien Sun, Pi-Ju Hsiao, Wei-Liang Chen, Ta-Cheng Chen, Chen-Shu Chang, Chien-Hsu Lai, Chieh-Sen Chuang, Yen-Yu Chen, Shinn-Kuang Lin, Yu-Chin Su, Jen-Lun Shiao, Fu-Yi Yang, Chih-Yang Liu, Han-Lin Chiang, Guei-Chiuan Chen, Po-Jen Hsu, Chun-Yuan Chang, I.-sheng Lin, Chung-Hsien Chien, Yang-Chuang Chang, Ping-Kun Chen, Yu-Jen Hsiao, Chen-Wen Fang, Yu-Wei Chen, Kuo-Ying Lee, Yun-Yu Lin, Chen-Hua Li, Hui-Fen Tsai, Chuan-Fa Hsieh, Chih-Dong Yang, Shiumn-Jen Liaw, How-Chin Liao, Shoou-Jeng Yeh, Ling-Li Wu, Liang-Po Hsieh, Yong-Hui Lee, Chung-Wen Chen, Chih-Shan Hsu, Ye-Jian Jhih, Hao-Yu Zhuang, Yan-Hong Pan, Shin-An Shih, Chin-I. Chen, Jia-Ying Sung, Hsing-Yu Weng, Hao-Wen Teng, Jing-Er Lee, Chih-Shan Huang, Shu-Ping Chao, Rey-Yue Yuan, Jau-Jiuan Sheu, Jia-Ming Yu, Chun-Sum Ho, Ting-Chun Lin, Shih-Chieh Yu, Jiunn-Rong Chen, Song-Yen Tsai, Chao-Hsien Hung, Chia Fang Lee, Sheng-Kung Yang, Chih-Lin Chen, Wei Lin, Hung-Pin Tseng, Chin-Hsiung Liu, Chun-Liang Lin, Hung-Chih Lin, Pi-Tzu Chen, Chaur-Jong Hu, Lung Chan, Nai-Fang Chi, Chang-Ming Chern, Chun-Jen Lin, Shuu-Jiun Wang, Li-Chi Hsu, Wen-Jang Wong, I-Hui Lee, Der-Jen Yen, Ching-Piao Tsai, Shang-Yeong Kwan, Bing-Wen Soong, Shih-Pin Chen, Kwong-Kum Liao, Kung-Ping Lin, Chien Chen, Din-E. Shan, Jong-Ling Fuh, Pei-Ning Wang, Yi-Chung Lee, Yu-Hsiang Yu, Hui-Chi Huang, Jui-Yao Tsai, Ming-Hsiu Wu, Szu-Yi Chiang, Chiung-Yao Wang, Ming-Chin Hsu, Chien-Chung Chen, Po-Yen Yeh, Yu-Tai Tsai, Ko-Yi Wang, Tsang-Shan Chen, Cheng-Yang Hsieh, Wei-Fen Chen, Ping-Keung Yip, Vinchi Wang, Kaw-Chen Wang, Chung-Fen Tsai, Chao-Ching Chen, Yi-Chien Liu, Shao-Yuan Chen, Zi-Hao Zhao, Zhi-Peng Wei, Shey-Lin Wu, Ching-Kuan Liu, Ryh-Huei Lin, Ching-Hua Chu, Sui-Hing Yan, Yi-Chun Lin, Pei-Yun Chen, Sheng-Huang Hsiao, Bak-Sau Yip, Pei-Chun Tsai, Ping-Chen Chou, Tsam-Ming Kuo, Yi-Chen Lee, Yi-Pin Chiu, Kun-Chang Tsai, Yi-Sheng Liao, Ming-Jun Tsai, and Hsin-Yi Kao

Subjects
Adult, Male, Stroke registry, medicine.medical_specialty, Time Factors, Adolescent, Taiwan, Renal function, 030204 cardiovascular system & hematology, Kidney, Risk Assessment, Brain Ischemia, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Humans, Medicine, In patient, Registries, Risk factor, Stroke, Aged, Retrospective Studies, Aged, 80 and over, business.industry, Mortality rate, Middle Aged, Prognosis, medicine.disease, Ischemic stroke, Cardiology, Female, Kidney Diseases, Cardiology and Cardiovascular Medicine, business, 1 year mortality, 030217 neurology & neurosurgery, Glomerular Filtration Rate
Abstract

Background and aims Renal dysfunction is a potent risk factor for cardiovascular diseases, including stroke. This study aimed to evaluate the impact of admission estimated glomerular filtration rate (eGFR) levels on short-term (1-month) and long-term (1-year) mortality in patients with acute ischemic stroke. Methods From the Taiwan Stroke Registry data, we classified ischemic stroke patients, identified from April 2006 to December 2015, into 5 groups by eGFR at admission: ≥ 90, 60–89, 30–59, 15–29, and Results Among 52,732 ischemic stroke patients, 1480 died within one month. The 1-month mortality rate was over 5-fold greater in patients with eGFR Conclusions After acute ischemic stroke, patients with reduced eGFR are at elevated risks of short-term and long-term deaths in a graded relationship.

Published
2018
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4. Corrigendum to: Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People

Author

Kung-Ping Lin, Chen-Yang Shen, Mei-Ling Kang, Wen Ya Ko, Chia-Wei Peng, Show-Ling Yang, Quintin Liu, Chia-Ni Hsiung, Chiao-Feng Lin, Hsueh-Chien Cheng, Mei Hsuan Lee, Yun-Hua Lo, Han-Yu Wang, Chien-Hsiun Chen, Chun-Yu Chen, Cheng-Jui Lin, Yoko Satta, Jun-Hun Loo, Hou-Wei Chu, Shu-Miaw Chaw, and Marie Lin

Subjects
2019-20 coronavirus outbreak, Genome, Coronavirus disease 2019 (COVID-19), Genetic genealogy, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), AcademicSubjects/SCI01130, MEDLINE, Biology, AcademicSubjects/SCI01180, Corrigenda, Polymorphism, Single Nucleotide, Asian People, Haplotypes, Evolutionary biology, Genetics, Humans, Adaptation, Molecular Biology, Ecology, Evolution, Behavior and Systematics, Genome-Wide Association Study
Abstract

The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.

Published
2021
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5. Cholesterol Levels Are Associated with 30-day Mortality from Ischemic Stroke in Dialysis Patients

Author

I.-Kuan Wang, Chung-Hsiang Liu, Tzung-Hai Yen, Jiann-Shing Jeng, Shih-Pin Hsu, Chih-Hung Chen, Li-Ming Lien, Ruey-Tay Lin, An-Chih Chen, Huey-Juan Lin, Hsin-Yi Chi, Ta-Chang Lai, Yu Sun, Siu-Pak Lee, Sheng-Feng Sung, Po-Lin Chen, Jiunn-Tay Lee, Tsuey-Ru Chiang, Shinn-Kuang Lin, Chih-Hsin Muo, Henry Ma, Chi-Pang Wen, Fung-Chang Sung, Chung Y. Hsu, Chon-Haw Tsai, Wei-Shih Huang, Chung-Ta Lu, Tzung-Chang Tsai, Chun-Hung Tseng, Kang-Hsu Lin, Woei-Cherng Shyn, Yu-Wan Yang, Yen-Liang Liu, Der-Yang Cho, Chun-Chung Chen, Sung-Chun Tang, Li-Kai Tsai, Shin-Joe Yeh, Han-Jung Chen, Cheng-Sen Chang, Hung-Chang Kuo, Lian-Hui Lee, Huan-Wen Tsui, Jung-Chi Tsou, Yan-Tang Wang, Yi-Cheng Tai, Kun-Chang Tsai, Yen-Wen Chen, Kan Lu, Po-Chao Liliang, Yu-Tun Tsai, Cheng-Loong Liang, Kuo-Wei Wang, Hao-Kuang Wang, Jui-Sheng Chen, Po-Yuan Chen, Cien-Leong Chye, Wei-Jie Tzeng, Pei-Hua Wu, Pi-Shan Sung, Han-Chieh Hsieh, Hui-Chen Su, Hou-Chang Chiu, Wei-Hung Chen, Chyi-Huey Bai, Tzu-Hsuan Huang, Chi-Ieong Lau, Ya-Ying Wu, Hsu-Ling Yeh, Anna Chang, Ching-Huang Lin, Cheng-Chang Yen, Chun-Hung Chen, Gim-Thean Khor, A-Ching Chao, Hsiu-Fen Lin, Poyin Huang, Der-Shin Ke, Chia-Yu Chang, Poh-Shiow Yeh, Kao-Chang Lin, Tain-Junn Cheng, Chih-Ho Chou, Chun-Ming Yang, Hsiu-Chu Shen, Shih-Jei Tsai, Tsong-Ming Lu, Sheng-Ling Kung, Mei-Ju Lee, Hsi-Hsien Chou, Chou-Hsiung Pan, Po-Chi Chan, Min-Hsien Hsu, Wei-Lun Chang, Zhi-Zang Huang, Hai-Ming Shoung, Yi-Chen Lo, Fu-Hwa Wang, Jiu-Haw Yin, Chung-Jen Wang, Kai-Chen Wang, Li-Mei Chen, Jong-Chyou Denq, Chien-Jung Lu, Cheng-Huai Lin, Chieh-Cheng Huang, Chang-Hsiu Liu, Hoi-Fong Chan, Ming-Hui Sun, Li-Ying Ke, Yu-Shan Lee, Cheung-Ter Ong, Chi-Shun Wu, Yung-Chu Hsu, Yu-Hsiang Su, Ling-Chien Hung, Jiann-Chyun Lin, Yaw-Don Hsu, Giia-Sheun Peng, Chang-Hung Hsu, Chun-Chieh Lin, Che-Hung Yen, Chun-An Cheng, Yueh-Feng Sung, Yuan-Liang Chen, Ming-Tung Lien, Chung-Hsing Chou, Chia-Chen Liu, Fu-Chi Yang, Yi-Chung Wu, An-Chen Tso, Yu-Hua Lai, Chun-I Chiang, Chia-Kuang Tsai, Meng-Ta Liu, Ying-Che Lin, Yu-Chuan Hsu, Mei-Ching Lee, Pai-Hao Huang, Sian-King Lie, Pin-Wen Liao, Jen-Tse Chen, Mu-Chien Sun, Tien-Pao Lai, Wei-Liang Chen, Yen-Chun Chen, Ta-Cheng Chen, Wen-Fu Wang, Kwo-Whei Lee, Chen-Shu Chang, Chien-Hsu Lai, Siao-Ya Shih, Chieh-Sen Chuang, Yen-Yu Chen, Chien-Min Chen, Yu-Chin Su, Cheng-Lun Hsiao, Fu-Yi Yang, Chih-Yang Liu, Han-Lin Chiang, Chun-Yuan Chang, I-sheng Lin, Chung-Hsien Chien, Yang-Chuang Chang, Ping-Kun Chen, Pai-Yi Chiu, Yu-Jen Hsiao, Chen-Wen Fang, Yu-Wei Chen, Kuo-Ying Lee, Yun-Yu Lin, Chen-Hua Li, Hui-Fen Tsai, Chuan-Fa Hsieh, Chih-Dong Yang, Shiumn-Jen Liaw, How-Chin Liao, Shoou-Jeng Yeh, Ling-Li Wu, Liang-Po Hsieh, Yong-Hui Lee, Chung-Wen Chen, Chih-Shan Hsu, Ye-Jian Jhih, Hao-Yu Zhuang, Yan-Hong Pan, Shin-An Shih, Chin-I Chen, Jia-Ying Sung, Hsing-Yu Weng, Hao-Wen Teng, Jing-Er Lee, Chih-Shan Huang, Shu-Ping Chao, Rey-Yue Yuan, Jau- Jiuan Sheu, Jia-Ming Yu, Chun-Sum Ho, Ting-Chun Lin, Shih-Chieh Yu, Jiunn-Rong Chen, Song-Yen Tsai, Cheng-Yu Wei, Chao-Nan Yang, Chao-Hsien Hung, Ian Shih, Hung-Pin Tseng, Chin-Hsiung Liu, Chun-Liang Lin, Hung-Chih Lin, Pi-Tzu Chen, Chaur-Jong Hu, Nai-Fang Chi, Lung Chan, Chang-Ming Chern, Chun-Jen Lin, Shuu-Jiun Wang, Li-Chi Hsu, Wen-Jang Wong, I-Hui Lee, Der-Jen Yen, Ching-Piao Tsai, Shang-Yeong Kwan, Bing-Wen Soong, Shih-Pin Chen, Kwong-Kum Liao, Kung-Ping Lin, Chien Chen, Din-E Shan, Jong-Ling Fuh, Pei-Ning Wang, Yi-Chung Lee, Yu-Hsiang Yu, Hui-Chi Huang, Jui-Yao Tsai, Ming-Hsiu Wu, Shi-Cheng Chen, Szu-Yi Chiang, Chiung-Yao Wang, Ming-Chin Hsu, Chien-Chung Chen, Po-Yen Yeh, Yu-Tai Tsai, Ko-Yi Wang, Tsang-Shan Chen, Ping-Keung Yip, Vinchi Wang, Kaw-Chen Wang, Chung-Fen Tsai, Chao-Ching Chen, Chih-Hao Chen, Yi-Chien Liu, Shao-Yuan Chen, Zi-Hao Zhao, Zhi-Peng Wei, Shey-Lin Wu, Ching-Kuan Liu, Ryh-Huei Lin, Ching-Hua Chu, Sui-Hing Yan, Yi-Chun Lin, Pei-Yun Chen, Sheng-Huang Hsiao, Bak-Sau Yip, Pei-Chun Tsai, Ping-Chen Chou, Tsam-Ming Kuo, Yi-Chen Lee, Yi-Pin Chiu, Yi-Sheng Liao, Ming-Jun Tsai, and Hsin-Yi Kao

Subjects
Male, Stroke registry, medicine.medical_specialty, Time Factors, medicine.medical_treatment, Taiwan, Kaplan-Meier Estimate, 030204 cardiovascular system & hematology, Dialysis patients, Brain Ischemia, 03 medical and health sciences, chemistry.chemical_compound, Patient Admission, 0302 clinical medicine, Renal Dialysis, Risk Factors, Internal medicine, medicine, Humans, Registries, Serum cholesterol, Dialysis, Aged, Proportional Hazards Models, Aged, 80 and over, Cholesterol, business.industry, Mortality rate, Rehabilitation, Middle Aged, Prognosis, Stroke, chemistry, 30 day mortality, Ischemic stroke, Cardiology, Kidney Failure, Chronic, Female, Surgery, Neurology (clinical), Cardiology and Cardiovascular Medicine, business, Biomarkers, 030217 neurology & neurosurgery
Abstract

We investigated the impact of serum cholesterol levels on 30-day mortality after ischemic stroke in dialysis patients.From the Taiwan Stroke Registry data, we identified 46,770 ischemic stroke cases, including 1101 dialysis patients and 45,669 nondialysis patients from 2006 to 2013.Overall, the 30-day mortality was 1.46-fold greater in the dialysis group than in the nondialysis group (1.75 versus 1.20 per 1000 person-days). The mortality rates were 1.64, .62, 2.82, and 2.23 per 1000 person-days in dialysis patients with serum total cholesterol levels of 120 mg/dL, 120-159 mg/dL, 160-199 mg/dL, and ≥200 mg/dL, respectively. Compared to dialysis patients with serum total cholesterol levels of 120-159 mg/dL, the corresponding adjusted hazard ratios of mortality were 4.20 (95% confidence interval [CI] = 1.01-17.4), 8.06 (95% CI = 2.02-32.2), and 6.89 (95% CI = 1.59-29.8) for those with cholesterol levels of 120 mg/dL, 160-199 mg/dL, and ≥200 mg/dL, respectively.Dialysis patients with serum total cholesterol levels of ≥160 mg/dL or 120 mg/dL on admission are at an elevated hazard of 30-day mortality after ischemic stroke.

Published
2017
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6. Measurement of the urinary lactate:creatinine ratio for the early identification of newborn infants at risk for hypoxic-ischemic encephalopathy

Author

Ying Chao Chang, Pei Lin Wu, Kung Ping Lin, Shan Tair Wang, and Chao Ching Huang

Subjects
medicine.medical_specialty, Urinary system, Developmental Disabilities, Encephalopathy, Urine, Fetal Hypoxia, Sensitivity and Specificity, Hypoxic Ischemic Encephalopathy, Brain Ischemia, Central nervous system disease, chemistry.chemical_compound, medicine, Humans, Lactic Acid, Hypoxia, Brain, Asphyxia, Lactate/Creatinine, Creatinine, Asphyxia Neonatorum, business.industry, Infant, Newborn, Obstetrics and Gynecology, General Medicine, medicine.disease, Perinatal asphyxia, Surgery, chemistry, Anesthesia, medicine.symptom, business, Biomarkers
Abstract

Newborn infants with perinatal asphyxia are prone to the development of hypoxic-ischemic encephalopathy. There are no reliable methods for identifying infants at risk for this disorder.We measured the ratio of lactate to creatinine in urine by proton nuclear magnetic resonance spectroscopy within 6 hours and again 48 to 72 hours after birth in 58 normal infants and 40 infants with asphyxia. The results were correlated with the subsequent presence or absence of hypoxic-ischemic encephalopathy.Hypoxic-ischemic encephalopathy did not develop in any of the normal newborns but did develop in 16 of the 40 newborns with asphyxia. Within six hours after birth, the mean (+/-SD) ratio of urinary lactate to creatinine was 16.75+/-27.38 in the infants who subsequently had hypoxic-ischemic encephalopathy, as compared with 0.09+/-0.02 in the normal infants (P0.001) and 0.19+/-0.12 in the infants with asphyxia in whom hypoxic-ischemic encephalopathy did not develop (P0.001). A ratio of 0.64 or higher within six hours after birth had a sensitivity of 94 percent and a specificity of 100 percent for predicting the development of hypoxic-ischemic encephalopathy. The sensitivity and specificity of measurements obtained 48 to 72 hours after birth were much lower. The mean ratio of urinary lactate to creatinine was significantly higher in the infants who had adverse outcomes at one year (25.36+/-32.02) than in the infants with favorable outcomes (0.63+/-1.50) (P0.001).Measurement of the urinary lactate: creatinine ratio soon after birth may help identify infants at high risk for hypoxic-ischemic encephalopathy.

Published
1999

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