1
|
Wang H, Yin X, Lou SH, Fang TY, Han BL, Gao JL, Wang YF, Zhang DX, Wang XB, Lu ZF, Wu JP, Zhang JQ, Wang YM, Zhang Y, Xue YW. Metastatic lymph nodes and prognosis assessed by the number of retrieved lymph nodes in gastric cancer. World J Gastrointest Surg 2022; 14:1230-1249. [PMID: 36504519 PMCID: PMC9727575 DOI: 10.4240/wjgs.v14.i11.1230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/17/2022] [Accepted: 10/20/2022] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The prognostic value of quantitative assessments of the number of retrieved lymph nodes (RLNs) in gastric cancer (GC) patients needs further study.
AIM To discuss how to obtain a more accurate count of metastatic lymph nodes (MLNs) based on RLNs in different pT stages and then to evaluate patient prognosis.
METHODS This study retrospectively analyzed patients who underwent GC radical surgery and D2/D2+ LN dissection at the Cancer Hospital of Harbin Medical University from January 2011 to May 2017. Locally weighted smoothing was used to analyze the relationship between RLNs and the number of MLNs. Restricted cubic splines were used to analyze the relationship between RLNs and hazard ratios (HRs), and X-tile was used to determine the optimal cutoff value for RLNs. Patient survival was analyzed with the Kaplan-Meier method and log-rank test. Finally, HRs and 95% confidence intervals were calculated using Cox proportional hazards models to analyze independent risk factors associated with patient outcomes.
RESULTS A total of 4968 patients were included in the training cohort, and 11154 patients were included in the validation cohort. The smooth curve showed that the number of MLNs increased with an increasing number of RLNs, and a nonlinear relationship between RLNs and HRs was observed. X-tile analysis showed that the optimal number of RLNs for pT1-pT4 stage GC patients was 26, 31, 39, and 45, respectively. A greater number of RLNs can reduce the risk of death in patients with pT1, pT2, and pT4 stage cancers but may not reduce the risk of death in patients with pT3 stage cancer. Multivariate analysis showed that RLNs were an independent risk factor associated with the prognosis of patients with pT1-pT4 stage cancer (P = 0.044, P = 0.037, P = 0.003, P < 0.001).
CONCLUSION A greater number of RLNs may not benefit the survival of patients with pT3 stage disease but can benefit the survival of patients with pT1, pT2, and pT4 stage disease. For the pT1, pT2, and pT4 stages, it is recommended to retrieve 26, 31 and 45 LNs, respectively.
Collapse
Affiliation(s)
- Hao Wang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Xin Yin
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Sheng-Han Lou
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Tian-Yi Fang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Bang-Ling Han
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Jia-Liang Gao
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Yu-Fei Wang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Dao-Xu Zhang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Xi-Bo Wang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Zhan-Fei Lu
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Jun-Peng Wu
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Jia-Qi Zhang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Yi-Min Wang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Yao Zhang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Ying-Wei Xue
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| |
Collapse
|
2
|
Zhang Z, Guo F, Roy A, Yang J, Luo W, Shen X, Irwin DM, Chen RA, Shen Y. Evolutionary perspectives and adaptation dynamics of human seasonal influenza viruses from 2009 to 2019: An insight from codon usage. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2021; 96:105067. [PMID: 34487866 DOI: 10.1016/j.meegid.2021.105067] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/28/2021] [Accepted: 09/01/2021] [Indexed: 06/13/2023]
Abstract
The annually recurrent seasonal influenza viruses, namely, influenza A viruses (H1N1/pdm2009 and H3N2) and influenza B viruses, contribute substantially to human disease burden. Elucidation of host adaptation, population dynamics and evolutionary patterns of these viruses contribute to better control of current epidemic situation and bolster efforts towards pandemic preparedness. Present study has been addressed at unraveling the signatures of codon usage and dinucleotide distribution of these seasonal influenza viruses associating with their fitness and ongoing adaptive evolution in human population. Thorough analysis of codon usage adaptation revealed that H3N2 has been exhibited best adapted to human cellular system, which correlate with its highest epidemic intensity as compared with the other seasonal influenza viruses. CpG dinucleotide was found to be strongly avoided among the seasonal influenza viruses with more restraint among influenza B viruses than influenza A viruses, and might be accounted to the strategy of the viral pathogens in evading human immune signals. Dynamic scenes of ongoing evolution in codon usage and elimination of CpG motif among the viruses, which correlate with their distinct host adaption state, signifying the marked impact of selective force operational on the viral genomes, aimed at proficient circulation, enhanced fitness and successful infective manifestations in humans.
Collapse
Affiliation(s)
- Zhipeng Zhang
- Zhaoqing Branch Center of Guangdong Laboratory for Lingnan Modern Agricultural Science and Technology, Zhaoqing 526238, China; Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China
| | - Fucheng Guo
- Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
| | - Ayan Roy
- Department of Biotechnology, Lovely Professional University, Punjab, India
| | - Jinjin Yang
- Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China
| | - Wen Luo
- Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China
| | - Xuejuan Shen
- Zhaoqing Branch Center of Guangdong Laboratory for Lingnan Modern Agricultural Science and Technology, Zhaoqing 526238, China; Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China
| | - David M Irwin
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto M5S 1A8, Canada; Banting and Best Diabetes Centre, University of Toronto, Toronto M5S 1A8, Canada
| | - Rui-Ai Chen
- Zhaoqing Branch Center of Guangdong Laboratory for Lingnan Modern Agricultural Science and Technology, Zhaoqing 526238, China; Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China; Zhaoqing Institute of Biotechnology, Zhaoqing 526238, China.
| | - Yongyi Shen
- Zhaoqing Branch Center of Guangdong Laboratory for Lingnan Modern Agricultural Science and Technology, Zhaoqing 526238, China; Center for Emerging and Zoonotic Diseases, College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China; Zhaoqing Institute of Biotechnology, Zhaoqing 526238, China; Key Laboratory of Zoonosis Prevention and Control of Guangdong Province, Guangzhou 510642, China.
| |
Collapse
|
3
|
Chen W, Guo X, Guo Q, Tan X, Wang Z. Long-Term Chili Monoculture Alters Environmental Variables Affecting the Dominant Microbial Community in Rhizosphere Soil. Front Microbiol 2021; 12:681953. [PMID: 34276615 PMCID: PMC8281244 DOI: 10.3389/fmicb.2021.681953] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 05/31/2021] [Indexed: 11/13/2022] Open
Abstract
Continuous cropping negatively affects soil fertility, physicochemical properties and the microbial community structure. However, the effects of long-term chili monoculture on the dominant microbial community assembly are not known. In this study, the impact of long-term chili monoculture on the correlation between the dominant microbial community and soil environmental variables was assessed. The results indicated that increasing duration of chili monoculture generated significant changes in soil nutrients, soil aggregates and soil enzymes: nutrient contents increased overall, mechanically stable macroaggregates increased and microaggregates decreased, water-stable macroaggregates and microaggregates decreased, β-glucosidase decreased nonlinearly, and nitrate reductase and alkaline phosphatase activities showed a nonlinear increase. Moreover, an increasing number of years of chili monoculture also affected the structure of the dominant microbiota, with substantial changes in the relative abundances of 11 bacterial and fungal genera. The drivers of the dominant microbial community assembly in rhizosphere soil were soil moisture, abiotic nitrogen, pH and salt.
Collapse
Affiliation(s)
- Wenjing Chen
- Institute of Soil, Fertilizer and Water-Saving Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou, China.,College of Life Sciences, Agriculture and Forestry, Qiqihar University, Qiqihar, China.,Heilongjiang Provincial Technology Innovation Center of Agromicrobial Preparation Industrialization, Qiqihar, China
| | - Xiaodong Guo
- Institute of Soil, Fertilizer and Water-Saving Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou, China
| | - Quanen Guo
- Institute of Soil, Fertilizer and Water-Saving Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou, China
| | - Xuelian Tan
- Institute of Soil, Fertilizer and Water-Saving Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou, China.,Key Laboratory of Efficient Utilization of Water in Dry Farming, Lanzhou, China
| | - Zhigang Wang
- College of Life Sciences, Agriculture and Forestry, Qiqihar University, Qiqihar, China.,Heilongjiang Provincial Technology Innovation Center of Agromicrobial Preparation Industrialization, Qiqihar, China
| |
Collapse
|
4
|
Fox-Lewis A, Fox-Lewis S, Beaumont J, Drinković D, Harrower J, Howe K, Jackson C, Rahnama F, Shilton B, Qiao H, Smith KK, Morpeth SC, Taylor S, Blakiston M, Roberts S, McAuliffe G. SARS-CoV-2 viral load dynamics and real-time RT-PCR cycle threshold interpretation in symptomatic non-hospitalised individuals in New Zealand: a multicentre cross sectional observational study. Pathology 2021; 53:530-535. [PMID: 33838922 PMCID: PMC7980174 DOI: 10.1016/j.pathol.2021.01.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 12/14/2020] [Accepted: 01/15/2021] [Indexed: 12/27/2022]
Abstract
We conducted a multicentre cross sectional observational study of laboratory, public health and hospitalisation data for PCR-confirmed COVID-19 cases within the New Zealand Northern Region, between 12 February and 8 June 2020. The aim of this study was to describe population level SARS-CoV-2 upper respiratory tract (URT) viral load dynamics by stratifying positivity rates and polymerase chain reaction (PCR) cycle threshold (Ct) values of URT samples from COVID-19 cases by days since symptom onset, and to explore utility of Ct values in determining length of time post-infection and thus potential infectivity. Of 123,124 samples tested for SARS-CoV-2 by PCR, 579 samples (407 positive and 172 negative) from 368 symptomatic non-hospitalised individuals with PCR-confirmed infection were included. Sample positivity rate was 61.5% (8/13) for pre-symptomatic samples, rising to 93.2% (317/340) for samples collected during the purported symptomatic infectious period (days 0–10 post-symptom onset), and dropping to 36.3% (82/226) for post-infectious period samples (day 11 onwards). URT viral load peaked shortly after symptom onset, with median Ct values ranging 20.00–29.99 until 15 days post-symptom onset, and >30.00 after this time. Of samples with a Ct value of <20.00, 96.1% were collected during the symptomatic infectious period. However, of samples with a Ct value ≥30.00 and ≥35.00, 46.9% and 18.5%, respectively, were also collected during the symptomatic infectious period. The findings of this study indicate that at or soon after symptom onset represents the optimum time to test for SARS-CoV-2 in the URT, with median Ct values suggesting the useful testing window extends until around 15 days post-symptom onset. In asymptomatic individuals or those with unknown dates of symptom onset, Ct values <20.00 imply recent onset/potential infectivity, but Ct values ≥30.00 or ≥35.00 do not exclude recent onset/potential infectivity. Individual sample Ct values should not be used as an absolute marker of length of time post-infection or to exclude infectivity where date of symptom onset is unavailable.
Collapse
Affiliation(s)
- Andrew Fox-Lewis
- Microbiology Department, LabPLUS, Auckland City Hospital, Auckland District Health Board, Auckland, New Zealand
| | - Shivani Fox-Lewis
- Virology-Immunology Department, LabPLUS, Auckland City Hospital, Auckland District Health Board, Auckland, New Zealand.
| | - Jenna Beaumont
- Microbiology Department, Middlemore Hospital, Counties Manukau District Health Board, Auckland, New Zealand
| | - Dragana Drinković
- Microbiology Department, North Shore Hospital, Waitematā District Health Board, Auckland, New Zealand
| | - Jay Harrower
- Auckland Regional Public Health Service, Auckland District Health Board, Auckland, New Zealand
| | - Kevin Howe
- Auckland Regional Public Health Service, Auckland District Health Board, Auckland, New Zealand
| | - Catherine Jackson
- Nga Tai Ora Public Health Northland, Northland District Health Board, Whangarei, New Zealand
| | - Fahimeh Rahnama
- Virology-Immunology Department, LabPLUS, Auckland City Hospital, Auckland District Health Board, Auckland, New Zealand
| | | | - Helen Qiao
- Microbiology Department, Middlemore Hospital, Counties Manukau District Health Board, Auckland, New Zealand
| | - Kevin K Smith
- Microbiology Department, North Shore Hospital, Waitematā District Health Board, Auckland, New Zealand
| | - Susan C Morpeth
- Microbiology Department, Middlemore Hospital, Counties Manukau District Health Board, Auckland, New Zealand
| | - Susan Taylor
- Microbiology Department, Middlemore Hospital, Counties Manukau District Health Board, Auckland, New Zealand
| | - Matthew Blakiston
- Microbiology Department, LabPLUS, Auckland City Hospital, Auckland District Health Board, Auckland, New Zealand; Labtests, Auckland, New Zealand
| | - Sally Roberts
- Microbiology Department, LabPLUS, Auckland City Hospital, Auckland District Health Board, Auckland, New Zealand
| | - Gary McAuliffe
- Virology-Immunology Department, LabPLUS, Auckland City Hospital, Auckland District Health Board, Auckland, New Zealand; Labtests, Auckland, New Zealand
| |
Collapse
|
5
|
Delgado-Sanz C, Mazagatos-Ateca C, Oliva J, Gherasim A, Larrauri A. Illness Severity in Hospitalized Influenza Patients by Virus Type and Subtype, Spain, 2010-2017. Emerg Infect Dis 2021; 26:220-228. [PMID: 31961295 PMCID: PMC6986827 DOI: 10.3201/eid2602.181732] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Influenza A(H1N1)pdm09 caused more hospitalizations, intensive care unit admissions, and deaths than influenza A(H3N2) or B. We conducted a retrospective cohort study to assess the effect of influenza virus type and subtype on disease severity among hospitalized influenza patients in Spain. We analyzed the cases of 8,985 laboratory-confirmed case-patients hospitalized for severe influenza by using data from a national surveillance system for the period 2010–2017. Hospitalized patients with influenza A(H1N1)pdm09 virus were significantly younger, more frequently had class III obesity, and had a higher risk for pneumonia or acute respiratory distress syndrome than patients infected with influenza A(H3N2) or B (p<0.05). Hospitalized patients with influenza A(H1N1)pdm09 also had a higher risk for intensive care unit admission, death, or both than patients with influenza A(H3N2) or B, independent of other factors. Determining the patterns of influenza-associated severity and how they might differ by virus type and subtype can help guide planning and implementation of adequate control and preventive measures during influenza epidemics.
Collapse
|
6
|
Liu R, Yi S, Zhang J, Lv Z, Zhu C, Zhang Y. Viral Load Dynamics in Sputum and Nasopharyngeal Swab in Patients with COVID-19. J Dent Res 2020; 99:1239-1244. [PMID: 32744907 PMCID: PMC7399563 DOI: 10.1177/0022034520946251] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) has caused a global pandemic associated with substantial morbidity and mortality. Nasopharyngeal swabs and sputum samples are generally collected for serial viral load screening of respiratory contagions, but temporal profiles of these samples are not completely clear in patients with COVID-19. We performed an observational cohort study at Renmin Hospital of Wuhan University, which involved 31 patients with confirmed COVID-19 with or without underlying diseases. We obtained samples from each patient, and serial viral load was measured by real-time quantitative polymerase chain reaction. We found that the viral load in the sputum was inclined to be higher than samples obtained from the nasopharyngeal swab at disease presentation. Moreover, the viral load in the sputum decreased more slowly over time than in the nasopharyngeal group as the disease progressed. Interestingly, even when samples in the nasopharyngeal swab turned negative, it was commonly observed that patients with underlying diseases, especially hypertension and diabetes, remained positive for COVID-19 and required a longer period for the sputum samples to turn negative. These combined findings emphasize the importance of tracking sputum samples even in patients with negative tests from nasopharyngeal swabs, especially for those with underlying conditions. In conclusion, this work reinforces the importance of sputum samples for SARS-CoV-2 detection to minimize transmission of COVID-19 within the community.
Collapse
Affiliation(s)
- R Liu
- Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, China
| | - S Yi
- The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei-MOST) and Key Laboratory of Oral Biomedicine Ministry of Education, School and Hospital of Stomatology, Wuhan University, Wuhan, China
| | - J Zhang
- The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei-MOST) and Key Laboratory of Oral Biomedicine Ministry of Education, School and Hospital of Stomatology, Wuhan University, Wuhan, China
| | - Z Lv
- Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, China
| | - C Zhu
- Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, China.,State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China
| | - Y Zhang
- The State Key Laboratory Breeding Base of Basic Science of Stomatology (Hubei-MOST) and Key Laboratory of Oral Biomedicine Ministry of Education, School and Hospital of Stomatology, Wuhan University, Wuhan, China
| |
Collapse
|
7
|
Zheng S, Fan J, Yu F, Feng B, Lou B, Zou Q, Xie G, Lin S, Wang R, Yang X, Chen W, Wang Q, Zhang D, Liu Y, Gong R, Ma Z, Lu S, Xiao Y, Gu Y, Zhang J, Yao H, Xu K, Lu X, Wei G, Zhou J, Fang Q, Cai H, Qiu Y, Sheng J, Chen Y, Liang T. Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang province, China, January-March 2020: retrospective cohort study. BMJ 2020; 369:m1443. [PMID: 32317267 PMCID: PMC7190077 DOI: 10.1136/bmj.m1443] [Citation(s) in RCA: 982] [Impact Index Per Article: 245.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/06/2020] [Indexed: 02/07/2023]
Abstract
OBJECTIVE To evaluate viral loads at different stages of disease progression in patients infected with the 2019 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the first four months of the epidemic in Zhejiang province, China. DESIGN Retrospective cohort study. SETTING A designated hospital for patients with covid-19 in Zhejiang province, China. PARTICIPANTS 96 consecutively admitted patients with laboratory confirmed SARS-CoV-2 infection: 22 with mild disease and 74 with severe disease. Data were collected from 19 January 2020 to 20 March 2020. MAIN OUTCOME MEASURES Ribonucleic acid (RNA) viral load measured in respiratory, stool, serum, and urine samples. Cycle threshold values, a measure of nucleic acid concentration, were plotted onto the standard curve constructed on the basis of the standard product. Epidemiological, clinical, and laboratory characteristics and treatment and outcomes data were obtained through data collection forms from electronic medical records, and the relation between clinical data and disease severity was analysed. RESULTS 3497 respiratory, stool, serum, and urine samples were collected from patients after admission and evaluated for SARS-CoV-2 RNA viral load. Infection was confirmed in all patients by testing sputum and saliva samples. RNA was detected in the stool of 55 (59%) patients and in the serum of 39 (41%) patients. The urine sample from one patient was positive for SARS-CoV-2. The median duration of virus in stool (22 days, interquartile range 17-31 days) was significantly longer than in respiratory (18 days, 13-29 days; P=0.02) and serum samples (16 days, 11-21 days; P<0.001). The median duration of virus in the respiratory samples of patients with severe disease (21 days, 14-30 days) was significantly longer than in patients with mild disease (14 days, 10-21 days; P=0.04). In the mild group, the viral loads peaked in respiratory samples in the second week from disease onset, whereas viral load continued to be high during the third week in the severe group. Virus duration was longer in patients older than 60 years and in male patients. CONCLUSION The duration of SARS-CoV-2 is significantly longer in stool samples than in respiratory and serum samples, highlighting the need to strengthen the management of stool samples in the prevention and control of the epidemic, and the virus persists longer with higher load and peaks later in the respiratory tissue of patients with severe disease.
Collapse
Affiliation(s)
- Shufa Zheng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Jian Fan
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Fei Yu
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Baihuan Feng
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Bin Lou
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Qianda Zou
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Guoliang Xie
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Sha Lin
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Ruonan Wang
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Xianzhi Yang
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Weizhen Chen
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Qi Wang
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Dan Zhang
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Yanchao Liu
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Renjie Gong
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Zhaohui Ma
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Siming Lu
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yanyan Xiao
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yaxi Gu
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jinming Zhang
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Hangping Yao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Kaijin Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Xiaoyang Lu
- Department of Pharmacy, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Guoqing Wei
- Bone Marrow Transplantation Centre, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jianying Zhou
- Department of Respiratory Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Qiang Fang
- Department of Critical Care Medicine, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Hongliu Cai
- Department of Critical Care Medicine, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yunqing Qiu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jifang Sheng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yu Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, Collaborative Innovation Centre for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China
- Centre of Clinical Laboratory, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Institute of Laboratory Medicine, Zhejiang University, Hangzhou, China
| | - Tingbo Liang
- Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Zhejiang Provincial Key Laboratory of Pancreatic Disease, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- The Innovation Centre for the Study of Pancreatic Diseases of Zhejiang Province, Hangzhou, China
| |
Collapse
|
8
|
Hayward AC, Beale S, Johnson AM, Fragaszy EB. Public activities preceding the onset of acute respiratory infection syndromes in adults in England - implications for the use of social distancing to control pandemic respiratory infections. Wellcome Open Res 2020; 5:54. [PMID: 32399501 PMCID: PMC7194223 DOI: 10.12688/wellcomeopenres.15795.1] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/23/2020] [Indexed: 01/08/2023] Open
Abstract
Background: Social distancing measures may reduce the spread of emerging respiratory infections however, there is little empirical data on how exposure to crowded places affects risk of acute respiratory infection. Methods: We used a case-crossover design nested in a community cohort to compare self-reported measures of activities during the week before infection onset and baseline periods. The design eliminates the effect of non-time-varying confounders. Time-varying confounders were addressed by exclusion of illnesses around the Christmas period and seasonal adjustment. Results: 626 participants had paired data from the week before 1005 illnesses and the week before baseline. Each additional day of undertaking the following activities in the prior week was associated with illness onset: Spending more than five minutes in a room with someone (other than a household member) who has a cold (Seasonally adjusted OR 1·15, p=0·003); use of underground trains (1·31, p=0·036); use of supermarkets (1·32, p<0·001); attending a theatre, cinema or concert (1·26, p=0·032); eating out at a café, restaurant or canteen (1·25, p=0·003); and attending parties (1·47, p<0·001). Undertaking the following activities at least once in the previous week was associated with illness onset: using a bus, (aOR 1.48, p=0.049), shopping at small shops (1.9, p<0.002) attending a place of worship (1.81, p=0.005). Conclusions: Exposure to potentially crowded places, public transport and to individuals with a cold increases risk of acquiring circulating acute respiratory infections. This suggests social distancing measures can have an important impact on slowing transmission of emerging respiratory infections.
Collapse
Affiliation(s)
- Andrew C. Hayward
- UCL Research Department of Epidemiology & Public Health, UCL, London, WC1E 7HB, UK
| | - Sarah Beale
- UCL Public Health Data Science Research Group, Institute of Health Informatics, UCL, London, NW1 2DA, UK
| | | | - Ellen B. Fragaszy
- UCL Public Health Data Science Research Group, Institute of Health Informatics, UCL, London, NW1 2DA, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
| | - Flu Watch Group
- UCL Research Department of Epidemiology & Public Health, UCL, London, WC1E 7HB, UK
- UCL Public Health Data Science Research Group, Institute of Health Informatics, UCL, London, NW1 2DA, UK
- UCL Institute of Global Health, UCL, London, WC1E 6JB, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
| |
Collapse
|
9
|
Chen ICM, Loh JP, Chuah CXP, Gao QHC, Sun Y, Ng SH, Koh WHV, Goh EH, Zhao X, Tambyah PA, Cook AR, Chng J, Pang J, Tan BH, Lee VJ. Evidence for Cross-Protection Against Subsequent Febrile Respiratory Illness Episodes From Prior Infections by Different Viruses Among Singapore Military Recruits 2009-2014. J Infect Dis 2020; 219:1913-1923. [PMID: 30722024 PMCID: PMC6534195 DOI: 10.1093/infdis/jiz046] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 01/27/2019] [Indexed: 12/22/2022] Open
Abstract
Background Few studies have evaluated the relative cross-protection conferred by infection with different groups of viruses through studies of sequential infections in humans. We investigated the presence of short-lived relative cross-protection conferred by specific prior viral infections against subsequent febrile respiratory illness (FRI). Methods Men enlisted in basic military training between December 2009 and December 2014 were recruited, with the first FRI as the study entry point. ResPlex II assays and real-time polymerase chain reaction assays were used to detect viral pathogens in nasal wash samples, and survival analyses were performed to determine whether infection with particular viruses conferred short-lived relative cross-protection against FRI. Results Prior infection with adenovirus (hazard ratio [HR], 0.24; 95% confidence interval [CI], .14–.44) or influenza virus (HR, 0.52; 95% CI, .38–.73) conferred relative protection against subsequent FRI episode. Results were statistically significant even after adjustment for the interval between enlistment and FRI (P < .001). Adenovirus-positive participants with FRI episodes tended to be protected against subsequent infection with adenovirus, coronavirus, enterovirus/rhinovirus, and influenza virus (P = .062–.093), while men with influenza virus–positive FRI episodes tended be protected against subsequent infection with adenovirus (P = .044) and influenza virus (P = .081). Conclusion Prior adenovirus or influenza virus infection conferred cross-protection against subsequent FRI episodes relative to prior infection due to other circulating viruses.
Collapse
Affiliation(s)
- I-Cheng Mark Chen
- Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore.,Infectious Disease Research and Training Office, National Centre for Infectious Diseases, Singapore
| | | | - Cheryl X P Chuah
- Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore
| | | | - Yinxiaohe Sun
- Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore.,Centre for Infectious Disease Epidemiology and Research, Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore
| | | | | | - Ee Hui Goh
- Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore
| | - Xiahong Zhao
- Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore
| | - Paul Anantharajah Tambyah
- Yong Loo Lin School of Medicine, National University of Singapore and National University Hospital System, Singapore
| | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore
| | - Jeremiah Chng
- Biodefence Centre, Headquarters Medical Corps, Singapore Armed Forces, Singapore
| | - Junxiong Pang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore.,Centre for Infectious Disease Epidemiology and Research, Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore
| | - Boon-Huan Tan
- DSO National Laboratories, Singapore.,Infection and Immunity, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Vernon J Lee
- Saw Swee Hock School of Public Health, National University of Singapore and National University Hospital System, Singapore.,Biodefence Centre, Headquarters Medical Corps, Singapore Armed Forces, Singapore
| |
Collapse
|
10
|
Ho HJ, Tan YR, Cook AR, Koh G, Tham TY, Anwar E, Hui Chiang GS, Lwin MO, Chen MI. Increasing Influenza and Pneumococcal Vaccination Uptake in Seniors Using Point-of-Care Informational Interventions in Primary Care in Singapore: A Pragmatic, Cluster-Randomized Crossover Trial. Am J Public Health 2019; 109:1776-1783. [PMID: 31622142 PMCID: PMC6836784 DOI: 10.2105/ajph.2019.305328] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/03/2019] [Indexed: 12/31/2022]
Abstract
Objectives. To evaluate the effectiveness of point-of-care informational interventions in general practitioner clinics to improve influenza and pneumococcal vaccination uptake among elderly patients.Methods. We conducted a pragmatic, cluster-randomized crossover trial in 22 private general practitioner clinics in Singapore, from November 2017 to July 2018. We included all patients aged 65 years or older. Clinics were assigned to a 3-month intervention (flyers and posters encouraging vaccination) plus 1-month washout period, and a 4-month control period (usual care). Primary outcomes were differences in vaccination uptake rates between periods. Secondary outcomes were identification of other factors associated with vaccination uptake.Results. A total of 4378 and 4459 patients were included in the intervention and control periods, respectively. Both influenza (5.9% vs 4.8%; P = .047) and pneumococcal (5.7% vs 3.7%; P = .001) vaccination uptake rates were higher during the intervention period compared with the control period. On multilevel logistic regression analysis, follow-up for hypertension, diabetes mellitus, hyperlipidemia, or any combination of the 3 was associated with uptake of both vaccines.Conclusions. Point-of-care informational interventions likely contributed to increased influenza and pneumococcal vaccination uptake. Patients on follow-up for hypertension, diabetes mellitus, hyperlipidemia, or any combination of the 3 were more likely to receive influenza and pneumococcal vaccination and should be actively engaged by physicians.Trial Registration. ClinicalTrials.gov Identifier: NCT03445117.
Collapse
Affiliation(s)
- Hanley J Ho
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| | - Yi-Roe Tan
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| | - Alex R Cook
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| | - Gerald Koh
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| | - Tat Yean Tham
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| | - Eve Anwar
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| | - Grace Shu Hui Chiang
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| | - May O Lwin
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| | - Mark I Chen
- Hanley J. Ho is with the Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore. Yi-Roe Tan and Mark I. Chen are with the National Centre for Infectious Diseases, Singapore. Alex R. Cook and Gerald Koh are with the Saw Swee Hock School of Public Health, National University of Singapore, Singapore. Tat Yean Tham is with Frontier Healthcare Group, Singapore. Eve Anwar is with OneCare Medical Group Pte Ltd, Singapore. Grace Shu Hui Chiang is with the Department of Medicine, St Luke's Hospital, Singapore. May O. Lwin is with the Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore
| |
Collapse
|
11
|
Post-pandemic influenza A/H1N1pdm09 is associated with more severe outcomes than A/H3N2 and other respiratory viruses in adult hospitalisations. Epidemiol Infect 2019; 147:e310. [PMID: 31775940 PMCID: PMC7003621 DOI: 10.1017/s095026881900195x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
This study compares the frequency and severity of influenza A/H1N1pdm09 (A/H1), influenza A/H3N2 (A/H3) and other respiratory virus infections in hospitalised patients. Data from 17 332 adult hospitalised patients admitted to Sir Charles Gairdner Hospital, Perth, Western Australia, with a respiratory illness between 2012 and 2015 were linked with data containing reverse transcription polymerase chain reaction results for respiratory viruses including A/H1, A/H3, influenza B, human metapneumovirus, respiratory syncytial virus and parainfluenza. Of these, 1753 (10.1%) had test results. Multivariable regression analyses were conducted to compare the viruses for clinical outcomes including ICU admission, ventilation, pneumonia, length of stay and death. Patients with A/H1 were more likely to experience severe outcomes such as ICU admission (OR 2.5, 95% CI 1.2–5.5, P = 0.016), pneumonia (OR 3.0, 95% CI 1.6–5.7, P < 0.001) and lower risk of discharge from hospital (indicating longer lengths of hospitalisation; HR 0.64 95% CI 0.47–0.88, P = 0.005), than patients with A/H3. Patients with a non-influenza respiratory virus were less likely to experience severe clinical outcomes than patients with A/H1, however, had similar likelihood when compared to patients with A/H3. Patients hospitalised with A/H1 had higher odds of severe outcomes than patients with A/H3 or other respiratory viruses. Knowledge of circulating influenza strains is important for healthcare preparedness.
Collapse
|
12
|
Czaja CA, Miller L, Colborn K, Cockburn MG, Alden N, Herlihy RK, Simões EAF. State-level estimates of excess hospitalizations and deaths associated with influenza. Influenza Other Respir Viruses 2019; 14:111-121. [PMID: 31702114 PMCID: PMC7040963 DOI: 10.1111/irv.12700] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2019] [Revised: 10/04/2019] [Accepted: 10/11/2019] [Indexed: 11/30/2022] Open
Abstract
Background National estimates of influenza burden may not reflect state‐level influenza activity, and local surveillance may not capture the full burden of influenza. Methods To provide state‐level information about influenza burden, we estimated excess pneumonia and influenza (P&I) and respiratory and circulatory (R&C) hospitalizations and deaths in Colorado from local hospital discharge records, death certificates, and influenza virus surveillance using negative binomial models. Results From July 2007 to June 2016, influenza was associated with an excess of 17 911 P&I hospitalizations (95%CI: 15 227, 20 354), 30 811 R&C hospitalizations (95%CI: 24 344, 37 176), 1,064 P&I deaths (95%CI: 757, 1298), and 3828 R&C deaths (95%CI: 2060, 5433). There was a large burden of influenza A(H1N1) among persons aged 0‐64 years, with high median seasonal rates of excess hospitalization among persons aged 0‐4 years. Persons aged ≥65 years experienced the largest numbers and highest median seasonal rates of excess hospitalization and death associated with influenza A (H3N2). The burden of influenza B was generally lower, with elevated median seasonal rates of excess hospitalization among persons aged 0‐4 years and ≥65 years. Conclusions These findings complement existing influenza surveillance. Periodic state‐level estimates of influenza disease burden may be useful for setting state public health priorities and planning prevention and control initiatives.
Collapse
Affiliation(s)
- Christopher A Czaja
- Colorado Department of Public Health and Environment, Denver, CO, USA.,Colorado School of Public Health, Aurora, CO, USA.,University of Colorado School of Medicine, Aurora, CO, USA
| | - Lisa Miller
- Colorado School of Public Health, Aurora, CO, USA
| | | | | | - Nisha Alden
- Colorado Department of Public Health and Environment, Denver, CO, USA
| | - Rachel K Herlihy
- Colorado Department of Public Health and Environment, Denver, CO, USA
| | - Eric A F Simões
- Colorado School of Public Health, Aurora, CO, USA.,University of Colorado School of Medicine, Aurora, CO, USA
| |
Collapse
|
13
|
Möst J, Redlberger-Fritz M, Weiss G. Multiple Influenza Virus Infections in 4 Consecutive Epidemiological Seasons: A Retrospective Study in Children and Adolescents. Open Forum Infect Dis 2019; 6:ofz195. [PMID: 31223630 PMCID: PMC6579483 DOI: 10.1093/ofid/ofz195] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 04/17/2019] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Recent observations provide evidence for group-specific immunity toward influenza A infections and raise the question of how often we can get the flu. METHODS We retrospectively analyzed 2308 cases of children and adolescents with clinically manifested influenza and a positive PCR-test during the last 4 epidemiological seasons (2014-15 through 2017-18). RESULTS In the 2015-16 epidemiological season, almost 12% of patients had experienced an influenza infection during the previous season; in the 2016-17 season, more than 14% had at least 1 infection during the previous 2 seasons, and in 2017-18 season, over 18% had 1 or more infections during the previous 3 seasons. The majority of these repetitive infections occurred in children between 3-8 years of age. 29 patients experienced 3 or 4 infections during these seasons, whereas 38 children had 2 influenza episodes within the same season. Epidemiological pattern of circulating viral strains changed yearly; however, we identified 5 patients with confirmed influenza B infections during the 2014-15 and 2017-18 seasons, when only subtype Yamagata was circulating in Austria. CONCLUSIONS Repetitive influenza infections in consecutive epidemiological seasons occurred quite frequently in children and adolescents. Observations like ours contribute to a better understanding of the immunity against influenza virus infections and could have implications for future vaccination strategies.
Collapse
Affiliation(s)
- Johannes Möst
- MB-LAB—Clinical Microbiology Laboratory, Innsbruck, Austria
| | | | - Günter Weiss
- Department of Internal Medicine II (Infectious Diseases, Immunology, Rheumatology, and Pneumology), Medical University of Innsbruck, Innsbruck, Austria
| |
Collapse
|
14
|
Chuah CXP, Lim RL, Chen MIC. Investigating the Legacy of the 1918 Influenza Pandemic in Age-Related Seroepidemiology and Immune Responses to Subsequent Influenza A(H1N1) Viruses Through a Structural Equation Model. Am J Epidemiol 2018; 187:2530-2540. [PMID: 30165573 PMCID: PMC6269251 DOI: 10.1093/aje/kwy192] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 08/21/2018] [Indexed: 01/08/2023] Open
Abstract
A(H1N1) strains of Influenzavirus were responsible for 2 pandemics in the last 100 years. Because infections experienced early in life may have a long-lasting influence on future immune response against other influenza strains, we drew on previously collected seroincidence data from Singapore (n = 2,554; June-October 2009) to investigate whether the 1918 pandemic influenza virus and its early descendants produced an age-related signature in immune responses against the A/California/7/2009(H1N1)pdm09 virus of 2009. Hemagglutination inhibition assays revealed a J-shaped relationship; the oldest birth cohort (born in 1911-1926) had the highest titers, followed by the youngest (born in 1987-1992). Differential response by vaccination history was also observed, with seasonal influenza vaccine being associated with higher titers mainly in the oldest birth cohort. On the assumption that antibody titers are a correlate of protection, structural equation modeling predicted that a titer-mediated effect by the vaccine could, on its own, account for a negative association with seroconversion equivalent to a risk reduction of 23% (relative risk = 0.77, 95% confidence interval: 0.60, 0.99) in the oldest birth cohort. A subset of 503 samples tested against the A/Brisbane/59/2007(H1N1) and A/Puerto Rico/8/1934(H1N1) strains also revealed different age-related antibody profiles. The effectiveness of seasonal influenza vaccines against future pandemic strains could thus be age-dependent and related to early-life exposures.
Collapse
Affiliation(s)
- Cheryl X P Chuah
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
| | - Rachel L Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
| | - Mark I C Chen
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
| |
Collapse
|
15
|
Hardjojo A, Gunachandran A, Pang L, Abdullah MRB, Wah W, Chong JWC, Goh EH, Teo SH, Lim G, Lee ML, Hsu W, Lee V, Chen MIC, Wong F, Phang JSK. Validation of a Natural Language Processing Algorithm for Detecting Infectious Disease Symptoms in Primary Care Electronic Medical Records in Singapore. JMIR Med Inform 2018; 6:e36. [PMID: 29907560 PMCID: PMC6026305 DOI: 10.2196/medinform.8204] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Revised: 02/14/2018] [Accepted: 03/19/2018] [Indexed: 02/04/2023] Open
Abstract
Background Free-text clinical records provide a source of information that complements traditional disease surveillance. To electronically harness these records, they need to be transformed into codified fields by natural language processing algorithms. Objective The aim of this study was to develop, train, and validate Clinical History Extractor for Syndromic Surveillance (CHESS), an natural language processing algorithm to extract clinical information from free-text primary care records. Methods CHESS is a keyword-based natural language processing algorithm to extract 48 signs and symptoms suggesting respiratory infections, gastrointestinal infections, constitutional, as well as other signs and symptoms potentially associated with infectious diseases. The algorithm also captured the assertion status (affirmed, negated, or suspected) and symptom duration. Electronic medical records from the National Healthcare Group Polyclinics, a major public sector primary care provider in Singapore, were randomly extracted and manually reviewed by 2 human reviewers, with a third reviewer as the adjudicator. The algorithm was evaluated based on 1680 notes against the human-coded result as the reference standard, with half of the data used for training and the other half for validation. Results The symptoms most commonly present within the 1680 clinical records at the episode level were those typically present in respiratory infections such as cough (744/7703, 9.66%), sore throat (591/7703, 7.67%), rhinorrhea (552/7703, 7.17%), and fever (928/7703, 12.04%). At the episode level, CHESS had an overall performance of 96.7% precision and 97.6% recall on the training dataset and 96.0% precision and 93.1% recall on the validation dataset. Symptoms suggesting respiratory and gastrointestinal infections were all detected with more than 90% precision and recall. CHESS correctly assigned the assertion status in 97.3%, 97.9%, and 89.8% of affirmed, negated, and suspected signs and symptoms, respectively (97.6% overall accuracy). Symptom episode duration was correctly identified in 81.2% of records with known duration status. Conclusions We have developed an natural language processing algorithm dubbed CHESS that achieves good performance in extracting signs and symptoms from primary care free-text clinical records. In addition to the presence of symptoms, our algorithm can also accurately distinguish affirmed, negated, and suspected assertion statuses and extract symptom durations.
Collapse
Affiliation(s)
- Antony Hardjojo
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Arunan Gunachandran
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Long Pang
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Mohammed Ridzwan Bin Abdullah
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Win Wah
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Joash Wen Chen Chong
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Ee Hui Goh
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Sok Huang Teo
- National Healthcare Group Polyclinics, Singapore, Singapore
| | - Gilbert Lim
- School of Computing, National University of Singapore, Singapore, Singapore
| | - Mong Li Lee
- School of Computing, National University of Singapore, Singapore, Singapore
| | - Wynne Hsu
- School of Computing, National University of Singapore, Singapore, Singapore
| | - Vernon Lee
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore
| | - Mark I-Cheng Chen
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore, Singapore.,National Centre for Infectious Diseases, Singapore, Singapore
| | - Franco Wong
- National Healthcare Group Polyclinics, Singapore, Singapore.,National University Polyclinics, Singapore, Singapore
| | - Jonathan Siung King Phang
- National Healthcare Group Polyclinics, Singapore, Singapore.,National University Polyclinics, Singapore, Singapore
| |
Collapse
|