Melissa R. Pfeiffer

Causes of Death among Persons with AIDS in the Era of Highly Active Antiretroviral Therapy: New York City

Context As HIV treatment becomes more effective, AIDS-related deaths are decreasing and HIV-infected patients are dying of other causes. Better information about these other causes will help to determine appropriate health care for this population. Contribution The authors used death certificates to identify the causes of death in 68669 residents of New York City reported with AIDS. The percentage of deaths from nonHIV-related causes increased from 19.8% to 26.3% between 1999 and 2004. The principal causes of nonHIV-related deaths were cardiovascular disease, substance abuse, and nonAIDS-defining cancer. Cautions Death certificates are an imperfect way to identify cause of death. Implications Health care for HIV-infected patients must include prevention and management of common diseases as well as HIV-focused care. The Editors Over the past 20 years, AIDS has been transformed from a disease that was almost inevitably fatal to a chronic condition that is manageable for many people in the United States (1). The evolution began modestly in the early 1990s with prophylaxis against common opportunistic illnesses and accelerated in the mid-1990s with the introduction of protease inhibitors and highly active antiretroviral therapy (HAART). Between 1996 and 1998, HIV-related morbidity and mortality decreased by 60% in the United States (24). Along with increases in survival, the spectrum of underlying causes of death among persons with AIDS has gradually shifted. Between 1987 and 1999, the proportion of deaths due to nonHIV-related causes increased from 10.6% to 22.9% in 2 U.S. metropolitan areas (5). The most common nonHIV-related causes of death reported in the literature are alcohol and drug dependence, cardiovascular disease, and nonHIV-related cancer (69). The distribution of these causes varies with the sociodemographic characteristics of the persons studied, notably the prevalence of injection drug use (1012). In recognition of the increasing importance of nonHIV-related causes of death, the Infectious Diseases Society of America (IDSA) has argued that health care for people with HIV infection should expand from a primary focus on HIV-related illnesses to include preventable conditions that account for an increasing proportion of deaths (13). Thus, analyses that contribute to a fuller understanding of the underlying causes of death in subpopulations of persons with AIDS are needed. Many previous analyses are limited by small sample size, lack of generalizability, a focus on specific causes of death, and a failure to distinguish between deaths of persons with AIDS and deaths of persons with HIV infection (non-AIDS) (8, 1419). New York City is the single largest HIV/AIDS-reporting jurisdiction in the United States, accounting for 15.3% of AIDS cases and 16.4% of deaths among persons with AIDS (20). Thus, we had a unique opportunity to conduct a population-based analysis of the spectrum of underlying causes of death in a large and heterogeneous population. The data are drawn from 2 population-based registries, the New York City HIV/AIDS Reporting System and Vital Statistics Registry, and cover the period of 1999 through 2004. Methods Population The population was made up of persons 13 years of age or older who received; a diagnosis of AIDS; were alive at any time between 1999 and 2004; were reported to the New York City HIV/AIDS Reporting System as of 30 September 2005; were residents of New York City at the time of diagnosis; and, among those who died, had a known underlying cause of death (98.2% of all deaths). Data Sources The New York City HIV/AIDS Reporting System is a population-based registry of persons who received a diagnosis of AIDS (beginning in 1981), as defined by the Centers for Disease Control and Prevention (CDC), or HIV infection (non-AIDS) (beginning in 2000) (21). The current AIDS case definition includes a positive test result for HIV plus 1 or more of 26 opportunistic illnesses or a CD4+ lymphocyte count less than 0.200109 cells/L or less than 14% of total lymphocytes. The New York City HIV/AIDS Reporting System receives reports of possible AIDS diagnoses through an electronic laboratory reporting system or physician reports and investigates them by chart review. Reporting of AIDS in New York City is estimated to be 95% complete (22). The vital status of persons with AIDS is ascertained by semiannual matches between the HIV/AIDS Reporting System and the Vital Statistics Registry. The underlying cause of death is coded at the New York City Department of Health and Mental Hygiene (DOHMH) Office of Vital Statistics by a nosologist who is certified by the National Center for Health Statistics. The nosologist codes the cause of death using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) (23). We classified persons as living in an area of poverty if they lived in a ZIP codetabulation area with more than 20% of the population below the 1999 federal poverty level or if they were homeless (24). All other variables were patient-level and were collected as part of routine surveillance. We derived demographic data from medical record reviews and provider reports and computed age at the end of 2004 or at the time of death for persons who died. We classified race or ethnicity as Hispanic, black (non-Hispanic), white (non-Hispanic), or other or unknown. The HIV transmission categories were injection drug use, men who have sex with men, and high-risk heterosexual sex. The high-risk heterosexual category included heterosexual sex with a partner who had HIV infection, with an injection drug user, or with a bisexual man. We classified men who were injection drug users and who had sex with men as injection drug users. Otherwise, when more than 1 risk factor was reported, we classified persons on the basis of the CDC hierarchy of transmission categories (25). We defined borough as the borough of residence at the time of AIDS diagnosis. We grouped the year of the AIDS diagnosis into 3 periods: pre-HAART (before 1996), early HAART (19961998), and late HAART (19992004). We obtained CD4+ lymphocyte counts primarily through an electronic laboratory reporting system. The CD4+ lymphocyte count used in the analysis was the lowest count in the second half of 2004 or within 6 months of death. Outcome The outcome was the underlying cause of death. Persons with an unknown underlying cause of death (n= 233 [1.8%]) were excluded from cause-specific analyses. HIV-Related Underlying Causes of Death We classified deaths as HIV-related if the ICD-10 code for the underlying cause of death was between B20 and B24 (HIV disease) or if the ICD-10 code was for an opportunistic illness in the CDC case definition. The latter criterion ensured that we did not misclassify deaths of people with AIDS as nonHIV-related because HIV was not mentioned on the death certificate (26). We did not further categorize these deaths in the main analysis because 70.9% of deaths were assigned a nonspecific underlying cause, for example, HIV disease resulting in other specified conditions (ICD-10 code B23.8) (Appendix Table 1). Appendix Table 1. Categories of Underlying Causes of HIV-Related Deaths in Persons with AIDS in New York City, 19992004* NonHIV-Related Underlying Causes of Death We classified deaths with a known underlying cause that did not meet the criteria described earlier as nonHIV-related. We further classified underlying causes into 9 major categories based on those used by the New York City DOHMH Office of Vital Statistics (27). Appendix Table 2 shows these categories and their associated ICD-10 codes. The substance abuse category included heterogeneous conditions that were associated with alcohol and drug abuse, including drug dependence (that is, overdose), alcoholic liver disease, cirrhosis, hepatitis C, and liver cancer (2732). The cardiovascular disease category comprised all ICD-10 codes between I00 and I78, except cardiac arrest codes. The cancer category comprised malignant types of cancer, except liver cancer and neoplasms that are part of the CDC case definition. We further classified nonHIV-related causes into 16 specific subcategories to better characterize the cause of death. Appendix Table 2. Codes for Major Categories of NonHIV-Related Causes of Death and Selected Specific Causes within Categories* Statistical Analysis We calculated the age-adjusted mortality rates per 10000 persons with AIDS for each year from 1999 to 2004 and for the entire time period. Mortality rates were age-standardized to the U.S. Census population in New York City in 2000 (33). We tested trends in rates of HIV-related deaths, nonHIV-related deaths, and specific nonHIV-related causes by using linear regression models. The model that tested trends in HIV-related and nonHIV-related deaths pooled all deaths to allow for differential trends and an explicit statistical test of whether they differed. We compared crude and age-standardized mortality rates by using methods developed for mortality vital statistics (34). We tested the association between time to death and patient characteristics in separate Cox proportional hazards regression models for HIV-related and nonHIV-related deaths. Independent variables in the model were age, sex, race or ethnicity, HIV transmission category, borough, residence in an area of poverty, year of AIDS diagnosis, and lowest CD4+ lymphocyte count. Date of cohort entry was 1 January 1999 or the date of AIDS diagnosis if diagnosis was after this date. We followed cases until death or we censored cases on 31 December 2004 if patients were still alive on that date. Those who died of a nonHIV-related cause were censored on the date of death in the model that assessed time to HIV-related death. Similarly, those who died of an HIV-related cause were censored at death in the model that assessed time to nonHIV-related death. We verified the proportional hazards assumption by

School-age outcomes of late preterm infants in New York City

OBJECTIVEnThis study compares school-age outcomes among preterm (PT) (32 0/7-<34 weeks), late PT (LP) (34 0/7-<37 weeks), and full-term (FT) infants to assess cognitive sequelae of LP births.nnnSTUDY DESIGNnWe obtained linked birth and educational data for all nonanomalous singleton infants born 1994 through 1998 in New York City who had a third-grade standardized test score (n = 215,138).nnnRESULTSnChildren delivered LP and PT had 30% and 50% higher adjusted odds of needing special education than those delivered FT (adjusted odds ratio, 1.34; 95% confidence interval, 1.29-1.40; and adjusted odds ratio, 1.53; 95% confidence interval, 1.30-1.69). They also had lower adjusted math and English scores than those delivered FT (math: 7% and 10% of SD, respectively; English: 4% and 6% of SD). A linear association between gestational age and test scores was seen through 39 weeks gestation.nnnCONCLUSIONnThere is a significant risk of developmental differences in PT and LP infants compared with FT infants.

Estimation of HIV Prevalence, Risk Factors, and Testing Frequency among Sexually Active Men Who Have Sex with Men, Aged 18–64 Years—New York City, 2002

Population-based estimates of human immunodeficiency virus (HIV) prevalence and risk behaviors among men who have sex with men (MSM) are valuable for HIV prevention planning but not widely available, especially at the local level. We combined two population-based data sources to estimate prevalence of diagnosed HIV infection, HIV-associated risk-behaviors, and HIV testing patterns among sexually active MSM in New York City (NYC). HIV/AIDS surveillance data were used to determine the number of living males reporting a history of sex with men who had been diagnosed in NYC with HIV infection through 2002 (23% of HIV-infected males did not have HIV transmission risk information available). Sexual behavior data from a cross-sectional telephone survey were used to estimate the number of sexually active MSM in NYC in 2002. Prevalence of diagnosed HIV infection was estimated using the ratio of HIV-infected MSM to sexually active MSM. The estimated base prevalence of diagnosed HIV infection was 8.4% overall (95% confidence interval [CI] = 7.5–9.6). Diagnosed HIV prevalence was highest among MSM who were non-Hispanic black (12.6%, 95% CI = 9.8–17.6), aged 35–44 (12.6%, 95% CI = 10.4–15.9), or 45–54 years (13.1%, 95% CI = 10.2–18.3), and residents of Manhattan (17.7%, 95% CI = 14.5–22.8). Overall, 37% (95% CI = 32–43%) of MSM reported using a condom at last sex, and 34% (95% CI = 28–39%) reported being tested for HIV in the past year. Estimates derived through sensitivity analyses (assigning a range of HIV-infected males with no reported risk information as MSM) yielded higher diagnosed HIV prevalence estimates (11.0–13.2%). Accounting for additional undiagnosed HIV-infected MSM yielded even higher prevalence estimates. The high prevalence of diagnosed HIV among sexually active MSM in NYC is likely due to a combination of high incidence over the course of the epidemic and prolonged survival in the era of highly active antiretroviral therapy. Despite high HIV prevalence in this population, condom use and HIV testing are low. Combining complementary population-based data sources can provide critical HIV-related information to guide prevention efforts. Individual counseling and education interventions should focus on increasing condom use and encouraging safer sex practices among all sexually active MSM, particularly those groups with low levels of condom use and multiple sex partners

Comparing the National Death Index and the Social Security Administration's Death Master File to Ascertain Death in HIV Surveillance

Objectives. New York City (NYC) maintains a population-based registry of people with human immunodeficiency virus (HIV) infection to monitor the epidemic and inform resource allocation. We evaluated record linkages with the National Death Index (NDI) and the Social Security Administrations Death Master File (SSDMF) to find deaths occurring from 2000 through 2004. Methods. We linked records from 32,837 people reported with HIV and not previously known to be dead with deaths reported in the NDI and the SSDMF. We calculated the kappa statistic to assess agreement between data sources. We performed subgroup analyses to assess differences within demographic and transmission risk subpopulations. We quantified the benefit of linkages with each data source beyond prior death ascertainment from local vital statistics data. Results. We discovered 1,926 (5.87%) deaths, which reduced the HIV prevalence estimate in NYC by 2.03%, from 1.19% to 1.16%. Of these, 458 (23.78%) were identified only from NDI, and 305 (15.84%) only from SSDMF. Agreement in ascertainment between sources was substantial (kappa = [K] 0.74, 95% confidence interval [CI] 0.72, 0.76); agreement was lower among Hispanic people (K=0.65, 95% CI 0.62, 0.69) and people born outside the U.S. (K=0.60, 95% CI 0.52, 0.68). We identified an additional 13.62% of deaths to people reported with HIV in NYC; white people and men who have sex with men were disproportionately likely to be underascertained without these linkages (p<0.0001). Conclusion. Record linkages with national databases are essential for accurate prevalence estimates from disease registries, and the SSDMF is an inexpensive means to supplement linkages with the NDI to maximize death ascertainment.

Rates of Early Intervention Referral and Significant Developmental Delay, by Birthweight and Gestational Age

Though correlated, birthweight (BW) and gestational age (GA) have independent effects on cognitive and neurological outcomes. Jurisdictions vary in their inclusion of these two characteristics in their list of established conditions for automatic eligibility for Early Intervention (EI) services, which may lead them to miss important high-risk groups. We evaluated the relationship between BW–GA combinations and both EI referral rates and risk of EI-diagnosed significant developmental delay in a population of New York City (NYC) births. We linked birth certificates of children born in NYC to resident mothers during 1999–2001 and surviving the first 28xa0days of life (nxa0=xa0339,522) to EI administrative data. We calculated EI referral rates for various BW–GA categories, and used a logistic model to directly estimate the predicted risk of delay. EI referral rates of over 50% were observed in children born <1,250xa0g and those born <30xa0weeks and 1,250–1,499xa0g. Additionally, more than one in two children born either less than 1,250xa0g or <30xa0weeks and 1,250–1,499xa0g were predicted to be diagnosed with a developmental delay, compared with almost one-tenth among those born >2,500xa0g and 39+ weeks. A BW threshold of <1,250xa0g would identify children with the highest risk of delay; GA as an additional criterion would prevent overlooking high-risk children born <30xa0weeks but at higher birthweights. Physicians should monitor children with high-risk birth characteristics and refer them, if appropriate, for formal evaluation. EI programs may use these findings to guide determination of automatic eligibility criteria.

Effects of individual and neighborhood characteristics on the timeliness of provider designation for early intervention services in New York City.

Background: The Early Intervention (EI) Program of the New York City (NYC) Department of Health and Mental Hygiene provides therapeutic services to children under 3 years of age with developmental delays or disabilities. Although the EI Program targets delivery of services within 21 days of the meeting at which the Individualized Family Service Plan (IFSP) is developed, the designation of a service provider alone often takes longer than that. Objective: This study examined associations between individual and neighborhood characteristics and timeliness of provider designation in NYC. Methods: Multivariable logistic regression analyses were performed for 14,623 children who had their initial IFSPs developed in Fiscal Year 2004. Results: Provider designation was delayed 13.4% of the time for speech therapy, 10.0% of the time for special instruction, 8.2% of the time for occupational therapy, and 4.2% of the time for physical therapy. Individual characteristics independently associated with provider designation delay were: being older than 24 months, having the IFSP meeting between July and December, having an adaptive delay, and having speech therapy or special instruction in the IFSP. Neighborhood characteristics independently associated with provider designation delay included living in a low-income neighborhood and living in a heavily Spanish-speaking neighborhood. Conclusion: Delayed provider designation occurs because of both individual and neighborhood factors. Interventions are needed to address shortages of providers in certain neighborhoods or with specific skills, and to address surges in administrative program functions at certain times of the year.

Excess Mortality Among Injection Drug Users With AIDS, New York City (1999–2004)

We calculated proportions and trends in contributing causes of death among persons with AIDS (PWA) and a history of injection drug use (IDU) in New York City and compared the proportions with those among PWA with a transmission risk of high-risk heterosexual sex (HRH) and men who have sex with men (MSM). We included all 10,575 injection drug user, HRH, and MSM residents aged 13+ years with AIDS reported by September 30, , who died from 1999 through 2004. Accidental drug overdose was the most frequent contributing cause of death among IDUs (20.5%). Overdose prevention initiatives may greatly and immediately reduce deaths among PWA.