Timothy M. Uyeki

Bio: Timothy M. Uyeki is an academic researcher from Centers for Disease Control and Prevention. The author has contributed to research in topics: Influenza A virus subtype H5N1 & Influenza A virus. The author has an hindex of 86, co-authored 309 publications receiving 42818 citations. Previous affiliations of Timothy M. Uyeki include National Center for Immunization and Respiratory Diseases & University of California, San Francisco.

Quality of life reported by survivors after hospitalization for Middle East respiratory syndrome (MERS)

Abstract: Data are lacking on impact of Middle East Respiratory Syndrome (MERS) on health-related quality of life (HRQoL) among survivors. We conducted a cross-sectional survey of MERS survivors who required hospitalization in Saudi Arabia during 2016–2017, approximately 1 year after diagnosis. The Short-Form General Health Survey 36 (SF-36) was administered by telephone interview to assess 8 quality of life domains for MERS survivors and a sample of survivors of severe acute respiratory infection (SARI) without MERS. We compared mean SF-36 scores of MERS and non-MERS SARI survivors using independent t-test, and compared categorical variables using chi-square test. Adjusted analyses were performed using multiple linear regression. Of 355 MERS survivors, 83 were eligible and 78 agreed to participate. MERS survivors were younger than non-MERS SARI survivors (mean ± SD): (44.9 years ±12.9) vs (50.0 years ±13.6), p = 0.031. Intensive care unit (ICU) admissions were similar for MERS and non-MERS SARI survivors (46.2% vs. 57.1%), p = 0.20. After adjusting for potential confounders, there were no significant differences between MERS and non-MERS SARI survivors in physical component or mental component summary scores. MERS ICU survivors scored lower than MERS survivors not admitted to an ICU for physical function (p = 0.05), general health (p = 0.01), vitality (p = 0.03), emotional role (p = 0.03) and physical component summary (p < 0.02). Functional scores were similar for MERS and non-MERS SARI survivors. However, MERS survivors of critical illness reported lower quality of life than survivors of less severe illness. Efforts are needed to address the long-term medical and psychological needs of MERS survivors.

Health benefits, risks, and cost-effectiveness of influenza vaccination of children.

Abstract: We estimated cost-effectiveness of annually vaccinating children not at high risk with inactivated influenza vaccine (IIV) to range from US $12,000 per quality-adjusted life year (QALY) saved for children ages 6-23 months to $119,000 per QALY saved for children ages 12-17 years. For children at high risk (preexisting medical conditions) ages 6-35 months, vaccination with IIV was cost saving. For children at high risk ages 3-17 years, vaccination cost $1,000-$10,000 per QALY. Among children notat high risk ages 5-17 years, live, attenuated influenza vaccine had a similar cost-effectiveness as IIV. Risk status was more important than age in determining the economic effects of annual vaccination, and vaccination was less cost-effective as the child's age increased. Thus, routine vaccination of all children is likely less cost-effective than vaccination of all children ages 6-23 months plus all other children at high risk.

Family clustering of avian influenza A (H5N1).

Abstract: To the Editor: The unprecedented epizootic of avian influenza A (H5N1) in Asia poses a serious threat of causing the next global influenza pandemic. H5N1 viruses, to which humans have little or no immunity, have demonstrated the capacity to infect humans and cause severe illness and death (1–4). Fortunately, these viruses have not yet demonstrated the capacity for efficient and sustained person-to-person transmission, although limited person-to-person transmission was the cause of at least 1 family cluster of cases (5). Since family clusters of H5N1 illness may be the first suggestion of a viral or epidemiologic change, we have been monitoring them with great interest. Through our regional contacts and public sources, we have monitored family clusters and other aspects of H5N1 in Southeast Asia. A cluster was defined as >2 family members with laboratory-confirmed H5N1 or >2 family members with severe pneumonia or respiratory death, at least one of which had confirmed H5N1. To determine if family cluster events had increased over time, we divided the number of cluster events by the total number of days in 2 discrete periods and calculated rate ratios (RR) and 95% confidence intervals (CI). To determine whether the increase in family clustering was attributable to an increase in the number of cases, we divided the number of family units with >2 laboratory-confirmed cases by the total number of family units in the period. Percentage of deaths was also compared. From January 2004 to July 2005, 109 cases of avian influenza A (H5N1) were officially reported to the World Health Organization (WHO) (6). During this time, 15 family clusters were identified (Table). Of the 11 (73%) clusters that occurred in Vietnam, 7 were in northern Vietnam. Cluster size ranged from 2 to 5 persons, and 9 (60%) had >2 persons with laboratory-confirmed H5N1. Cluster 6 in Thailand was well documented and was likely the result of limited person-to-person transmission (5). For the other clusters, epidemiologic information was insufficient to determine whether person-to-person transmission occurred. In at least 3 clusters in Vietnam (Table; clusters 5, 7, and 11), >7 days occurred between the onset of the first and the next case, suggesting that simultaneous acquisition from a common source was unlikely. In cluster 11, 2 nurses assisted in the care of the index case-patient and subsequently were hospitalized with severe pneumonia; 1 had laboratory-confirmed H5N1. Table Family clusters of influenza A (H5N1) in Southeast Asia, January 2004–July 2005* Family clusters were slightly more likely to have occurred between December 2004 and July 2005 than in the first year of the outbreak (9 clusters in 243 days or 3.7 per 100 days vs. 6 clusters in 365 days or 1.6 per 100 days, respectively; RR 2.3, 95% CI 0.8–6.3). The difference was similar when the periods were limited to the same 8 months, 1 year apart (RR 1.8, 95% CI 0.6–5.4). Twenty-five (61%) of the 41 patients in the 15 family clusters died; the 7 persons who recovered or were not ill experienced secondary cases. Family clusters are still occurring; however, they do not appear to be increasing as a proportion of total cases. The proportion of families that were part of a cluster was similar from December 2004 to July 2005 to the proportion in the first year (6/55, 11% vs. 3/41, 7%, respectively, p = 0.7). However, the proportion of deaths dropped significantly, from 32 of 44 (73%) during December 2003 to November 2004, to 23 of 65 (35%) during December 2004 to July 2005 (p<0.0001). Although reports of H5N1 family clusters slightly increased, the increase was not statistically significant. Nevertheless, we believe any cluster of cases is of great concern and should be promptly and thoroughly investigated because it might be the first indication of viral mutations resulting in more efficient person-to-person spread. Family clustering does not necessarily indicate person-to-person transmission, as it may also result from common household exposures to the same H5N1-infected poultry or from other exposures, such as to uncooked poultry products. The decrease in proportion of deaths during 2005 is another epidemiologic change that should be monitored closely because it may reflect viral adaptation to the human host. Surveillance for human cases of avian influenza has been intensified in recent months, perhaps resulting in the identification of less severe cases. Alternatively, more widespread laboratory testing may be associated with false-positive results. No evidence to date shows genetic reassortment between H5N1 and human influenza A viruses (7). Viruses isolated from case-patients need to be immediately sequenced and characterized in relation to previously circulating viruses to see whether they are evolving. Recent modeling studies suggest that containing a pandemic at its source may be possible because emergent pandemic viruses may be less transmissible than commonly assumed (8), and antiviral treatment and chemoprophylaxis may slow the spread (9). Although the logistics of an attempt to contain the beginning of a potential influenza pandemic are formidable, we believe it is not beyond the capability of the modern global public health system. As WHO (10) has called for, countries should intensify their pandemic preparedness plans and strengthen international collaborations.

Effects of Oseltamivir Treatment on Duration of Clinical Illness and Viral Shedding and Household Transmission of Influenza Virus

Abstract: Background Large clinical trials have demonstrated the therapeutic efficacy of oseltamivir against influenza. Here we assessed its indirect effectiveness in reducing household secondary transmission in an incident cohort of influenza index cases and their household members.

Clinical Characteristics of Coronavirus Disease 2019 in China.

Abstract: Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of...

Standards of Medical Care in Diabetes

Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.