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Cadernos de Saúde Pública

ISSN 1678-4464

38 nº.1

Rio de Janeiro, Janeiro 2022


ARTIGO

Avaliação da subnotificação de óbitos em pessoas vivendo com HIV no Rio de Janeiro, Brasil, entre 2014 e 2019

Adelzon Assis de Paula, Pedro Chequer, Denise Ribeiro Franqueira Pires, Katia Regina Valente de Lemos, Luciana Garritano Barone, Valdiléa Gonçalves Veloso, Antonio Guilherme Pacheco

http://dx.doi.org/10.1590/0102-311X00081821


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RESUMO
Os autores avaliaram as proporções de subnotificação de óbitos e fatores associados em pessoas vivendo com HIV (PVHIV) no Rio de Janeiro, Brasil, entre 2014 e 2019. Variáveis demográficas, menção de tuberculose (TB) e contagem de células CD4 mais próxima ao óbito foram utilizadas para comparar indivíduos que tiveram códigos para HIV/aids mencionados na declaração de óbito (HMDO) àqueles que não apresentaram tal menção. Entre 10.698 certidões de óbito, 2.863 (26.8%) não citaram HIV/aids. Entre estes, 412 (14,4%) apresentaram causas externas como a causa subjacente. Depois de excluir as causas externas, 24% das certidões não mencionaram HIV/aids. Idade acima de 40 anos (OR = 1,75; IC95%: 1,52-2,01), raça/etnicidade não branca (OR = 1,16; IC95%: 1,02-1,31), sexo masculino (OR = 1,25; IC95%: 1,11-1,42), contagem de CD4 mais alta próximo ao óbito (OR = 1,14; IC95%: 1,12-1,16), não ter TB (OR = 4,86; IC95%: 3,76-6,29) e morte extra-hospitalar (OR = 2,61; IC95%: 2,31-2,95) mostraram associação com aumento de probabilidade de não apresentar HMDO. A proporção de certidões de óbito que não citavam HIV/aids aumentou de 18,7% para 35,1% entre 2014 e 2019. A alta proporção de óbitos subnotificados no Rio de Janeiro indica a possível subestimação dos coeficientes de mortalidade por HIV/aids no estado. A mudança nos padrões de mortalidade em PVHIV desafia tanto os médicos, no sentido de considerar o espectro clínico mais amplo na infecção pelo HIV, quanto os especialistas em vigilância, no sentido de aprimorar o monitoramento da mortalidade.

HIV; Síndrome de Imunodeficiência Adquirida; Mortalidade; Vigilância


 

Introduction

After combined antiretroviral therapy (cART) became widely available in the mid-1990s, mortality among people living with HIV (PLHIV) greatly decreased. However, evidence showed that the decline in death rates was paralleled with a change from AIDS-related causes of death to deathes from conditions initially unrelated to the clinical spectrum of HIV infection 1,2,3,4,5.

In 1996, Brazil became the first middle-income country to offer free access to both HIV diagnosis and cART to all eligible patients. Although the trends conceal important regional variations, cART substantially mitigated death rates among PLHIV in Brazil as a whole 6. Accordingly, the mortality profile of PLHIV shifted towards conditions usually unrelated to HIV/AIDS, which has been described locally 7,8, regionally 9, and nationwide 10,11.

Besides these undisputable initial achievements, AIDS death rates in Brazil have been virtually stable since 1999 6,10. While the scrutiny of this downfall of the Brazilian response to the HIV/AIDS epidemic is beyond the scope of this work, AIDS death rates for the whole country 10,12 and for at least some of its states 10,13,14 seem to be greater than officially depicted, considering the underreporting of cases 15,16,17 and deaths 18 among PLHIV.

A study conducted a descriptive analysis to find the major causes of AIDS deaths misclassification and to redistribute ill-defined causes of death. The authors found that, from 1985 to 2009, 27% of cases were underreported due to misclassification of AIDS-related causes in Brazil 12. In a recent study, the official mortality system of Santa Catarina State had an estimated 21% of underreported HIV/AIDS deaths; with other obstacles in the surveillance structure, a 37.1% underestimation was found from 2008 to 2017 14.

Pacheco et al. 13 have merged data from two large urban cohorts of PLHIV in Rio de Janeiro to the official state mortality database to recover vital status information from patients lost to follow-up; the authors described that 23.9% of deaths did not have mention of HIV/AIDS codes on the death certificate (HMDC). Moreover, about one out of four deaths of PLHIV in Rio de Janeiro had no HMDC even after the exclusion of registers having external causes as the underlying causes of death 19. Together, these findings emphasize how underreported deaths affect the quality of information on PLHIV mortality and hence the HIV/AIDS surveillance and control.

From 2014 to 2019, we assessed the proportions of underreported deaths among PLHIV in Rio de Janeiro and their associated factors after cross-referencing public HIV/AIDS surveillance databases to the official death registry.

Methods

Study site

Located in the Southeastern Brazil, the state of Rio de Janeiro is the third most populous Brazilian Federative Unit, with around 17.3 million inhabitants in 2020. Rio de Janeiro also has the second largest economy of the country, contributing to 9.2% of the Brazilian GDP. The state's latest official Human Development Index (HDI) was calculated in 0.761 20.

According to the Brazilian Ministry of Health 21, in 2019, the state of Rio de Janeiro ranked third in the national ranking of AIDS standardized mortality rates with 7.1 deaths per 100,000 inhabitants, largely outnumbering the country average, estimated in 4.1 deaths per 100,000 inhabitants.

Data sources and study population

Data from four official electronic databases were used: (i) Information System for Notifiable Diseases (SINAN) is the HIV/AIDS case reporting and investigation system; (ii) Laboratory Test Control System (SISCEL) monitors information on CD4 cells count and viral load determination tests; (iii) System for Logistic Control of Drugs (SICLOM) provides strategic support regarding cART dispensation; and (iv) Mortality Information System (SIM) gathers and stores information from death certificates.

Although SISCEL and SICLOM are independent systems, they share common fields regarding patient identification and sociodemographic information.

The study population included PLHIV in the state of Rio de Janeiro who either (i) were diagnosed with HIV/AIDS or (ii) had a CD4/viral load determination or (iii) received cART or (iv) died, at any point between 2014 and 2019. Only individuals aged 13 years or older at any endpoint were included in the analysis.

Data linkage strategy

Data deduplication and linkage were performed with a previously validated fully-automated deterministic algorithm, developed to retrieve vital status from patients lost to follow-up in a HIV/AIDS cohort 13. The algorithm was also validated to cross-reference PLHIV public databases 22, linking these data to tuberculosis 23,24 and to HIV cohorts 7. Patient's name, date of birth, and mother's name were used as matching fields.

Records from SINAN and SISCEL/SICLOM were linked to the SIM database to determine the patients' vital status. To maximize linkage accuracy, we cross-referenced registers from SINAN to SIM and from SISCEL/SICLOM to SIM; then, resulting databases were linked, replaced by the final one. SINAN data were deduplicated according to the hierarchical structure and tiebreakers adopted by the Brazilian Ministry of Health, which are based on both AIDS case notification criteria and HIV diagnosis date, as detailed elsewhere 21.

Labels (of residence and death) for municipalities and codes of different types of health institutions were obtained from the Brazilian Institute of Geography and Statistics (IBGE; https://www.ibge.gov.br/) and the Brazilian National Registry of Healthcare Establishment (CNES; http://cnes.datasus.gov.br/) websites, respectively.

Variables of interest

Demographic variables included age, gender, ethnicity, schooling, marital status, municipality of residence/death, and type of institution where death occurred. If demographic data in more than one database diverged, information was chosen preferentially from SIM, SISCEL/SICLOM, and lastly from SINAN. Laboratorial variables included CD4 cell counts and viral load (both closest to the date of death).

Causes of death mentioned in any field of the death certificate were retrieved and classified regarding presence or absence of HIV/AIDS codes (B20-B24), according to the International Classification of Diseases, 10th revision (ICD-10) 25. We considered two different datasets regarding the inclusion or not of deaths from external underlying causes.

ICD-10 codes of interest included A15-A19 and B200 for tuberculosis and V01-Y98 for external causes. Garbage codes included R00-R99, A40, A411, C26, C55, C76, C78-C80, I10, I26, I50, I51, I64, I674, I679, I694, I698, J159, J18, J96, J98, N17, N19, V89, X59, Y09, Y1, Y2 and Y30-Y34, as described elsewhere 26.

Statistical analysis

Pearson's chi-squared test compared categorical data (proportions of gender, race/ethnicity, schooling level, place of death, and mention of tuberculosis and garbage codes), whereas Wilcoxon rank-sum test compared count data (age and CD4 cell count) mean ranks. Logistic regression models 27 were fitted to estimate the odds ratios for no HMDC. To find the best-fit model, an automated procedure was implemented via a genetic algorithm including first-order interactions 28. Residual analysis was used to inspect the model's goodness of fit. Mann-Kendall trend test was used to check whether the proportion of deaths with no HMDC consistently varied overtime. All analyses were performed in the R computing environment version 4.0.2 (http://www.r-project.org).

Ethics

This project was approved by the Research Ethics Committee of the Sergio Arouca National School of Public Health, Oswaldo Cruz Foundation (ENSP/Fiocruz; number 1.172.797).

Results

According to the eligibility criteria, 109,636 individuals were included in our study, from which 36,429 (33.2%) were reported to SINAN, 101,496 (92.6%) were registered in SISCEL/SICLOM and 10,698 (9.7%) were found in the mortality database. Of those registered in SINAN and SISCEL/SICLOM, respectively 5,601 (15.4%) and 7,709 (7.6%) were found in SIM.

Around 2,863 (26.8%) of the PLHIV found in the mortality database had no HMDC, from which 412 (14.4%) had external causes and 1,074 (37.5%) had garbage codes as the underlying cause of death. After we excluded deaths from external causes, 24% of the registers still had no HMDC.

Individuals with no HMDC were older, had higher CD4 cell counts closest to death and were more likely to be male (p < 0.001 for all). On the other hand, they were less likely to have tuberculosis as the underlying or contributing causes of death (p < 0.001). Among those who had HMDC, 81.4% died within hospitals, whereas 58.9% did not (p < 0.001; Table 1. Overall, quite similar findings were seen after registers of external underlying causes of death were excluded Table 2. Multiple logistic regression outputs are shown in Table 3.

 

 

Tab.: 1
Table 1 General features of deceased people living with HIV (PLHIV) from Rio de Janeiro, Brazil, retrieved by linkage of the official HIV/AIDS databases to the mortality system. Complete dataset considered.

 

 

 

Tab.: 2
Table 2 General features of deceased people living with HIV (PLHIV) from Rio de Janeiro, Brazil, retrieved by linkage of the official HIV/AIDS databases to the mortality system. Dataset with no external causes.

 

 

 

Tab.: 3
Table 3 Odds ratios (OR) for no HIV/AIDS codes mentioned in the death certificate of people living with HIV (PLHIV) from Rio de Janeiro, Brazil, retrieved by linkage of the official HIV/AIDS databases to the mortality system.

 

Being older (OR = 1.40; 95%CI: 1.24-1.58; p < 0.001), non-white (OR = 1.19; 95%CI: 1.06-1.34; p = 0.004), male (OR = 1.42; 95%CI: 1.26-1.59; p < 0.001), having higher CD4 cell count closest to death (OR = 1.16; 95%CI: 1.14-1.18; p < 0.001), not having tuberculosis (OR = 5.80; 95%CI: 4.50-7.49; p < 0.001) and not dying within a hospital (OR = 2.91; 95%CI: 2.59-3.27; p < 0.001) were associated to increased probability of no HMDC.

After we excluded deaths from external causes, the association with male gender (OR = 1.25; 95%CI: 1.11-1.42; p < 0.001), not having tuberculosis (OR = 4.86; 95%CI: 3.76-6.29; p < 0.001) and not dying within a hospital (OR = 2.61; 95%CI: 2.31-2.95; p < 0.001) on HMDC likelihood weakened, whereas the association with older ages (OR = 1.75; 95%CI: 1.52-2.01; p < 0.001) strengthened. Odds ratios for both race/ethnicity (OR = 1.16; 95%CI: 1.02-1.31; p = 0.019) and CD4 cell counts closest to death (OR = 1.14; 95%CI: 1.12-1.16; p < 0.001) did not change. Proportions of deaths with no HMDC increased over time, ranging from 18.7% in 2014 to 35.1% in 2019 (p < 0.001). Garbage codes were not modelled since they represent a post hoc event and do not truly predict a patients' death.

Discussion

Our main result is that, after deaths from external causes were ruled out, we found that 23.9% of PLHIV who died between January 1, 2014, and December 31, 2019, in Rio de Janeiro, had no HMDC. Those people were, therefore, out of the state mortality system's scope, indicating that state HIV/AIDS mortality coefficients, which are based solely on state-level death information, may be biased towards lower estimates.

According to the World Health Organization's guideline for death certification, in case of accidents, injuries, or poisonings, the external cause should be reported as the underlying causes of death instead of HIV/AIDS codes 29. When such deaths were excluded of the analyses, proportions of no HMDC increased to 26.4%. This corroborates our previous work assessing the proportions of underreported deaths in cohorts of PLHIV in Rio de Janeiro 13,30.

We emphasize the conflict between proportions of deaths occurred in hospitals for those with HMDC (81.4%) and for those without such codes (58.9%). As previously reported, patients in the city of Rio de Janeiro are becoming increasingly aware of their HIV serostatus in emergency care systems, with a worrying proportion already presenting pronounced immunodeficiency signs and evolving to death with no prior testing 31.

Male gender and younger ages are associated with violent deaths; therefore, after deaths from external underlying causes were excluded, no HMDC became less associated to male gender and more associated to older ages. Excluding younger patients may also have weakened the association of no HMDC with tuberculosis and with death outside hospitals.

Characteristics associated with HIV/AIDS mortality underestimation, including being older, having higher CD4 cell counts closest to death, and not having tuberculosis, suggest that the mortality profile of PLHIV is getting closer to that of the general population 32,33,34. This is likely a consequence of large-scale and early use of cART, which tends to gradually shift the morbidity profile among PLHIV from AIDS-related diseases to manageable chronic conditions 8,11,32. Moreover, occurrences of no HMDC have increased over time.

Our results point to a high proportion of garbage codes as the underlying cause of death among those not having HMDC, irrespective of whether external causes were considered or not. Notwithstanding, those numbers are very akin to the proportions of garbage codes verified for the overall state's population 26. It seems, therefore, that upon scale up use of cART PLHIV are progressively resembling the general population in clinical and epidemiological aspects, both beneficial and detrimental.

There are several reasons for HIV/AIDS underreporting on death certificates. Physicians may not be familiar with proper documentation of causes of death on the certificates; either the physician or the deceased relatives may be averse to the presence of HIV/AIDS codes on the death certificate due to stigmatization and the unawareness of the HIV status among patients who pass away in emergency rooms 35, to name just a few.

The major strength of our study is that retrospectively followed nearly 110,000 PLHIV found in official HIV/AIDS surveillance databases for a 6-year time frame so as to assign their vital status through linkage to the official mortality system. Such strategy yielded a considerable number of events (10,698 deaths) thus endowing the analyses with great statistical power.

Our study also has limitations worth acknowledging. As is frequent in population-based studies, especially those involving solely death certificates information, the influence of unmeasured confounders cannot be assured to be kept at bay. Also, the linkage algorithm employed, though proven to be accurate enough 22, may have introduced some amount of false-positive and/or false-negative pairings, which we consider to be insufficient to impact on our findings.

The changing pattern of mortality of PLHIV challenges not only physicians to consider the broader clinical spectrum of HIV infection but also surveillance officers to improve death monitoring. Cross-referencing HIV/AIDS databases to the all-cause mortality system on a regular basis is expected to mitigate the underreporting issue in order to produce bona fide mortality estimates.

While the Brazilian official HIV/AIDS death estimates can be in some measure biased, an alternative approach to circumvent this issue would be using ancillary sources of information, such as the Global Burden of Disease initiative, which combines crude data (as those from SIM) to statistical models to account for potential sources of errors, e.g, misclassification of underlying cause of death and underreporting 10.

The evidence presented here supports the suboptimal accuracy of death certificates to classify HIV/AIDS-related deaths. As an example, when ICD-10 was compared to a standardized algorithm developed specifically to classify causes of deaths among PLHIV, the proportion of HIV/AIDS-related conditions was overestimated while liver-related conditions, infections and ill-defined causes of death were downsized, as cirrhosis deaths due to viral or unknown aetiologies are likely to be assigned to HIV/AIDS-related causes 36.

Efforts to gauge and to mitigate the underreporting of deaths among PLHIV are needed in order to improve the estimates of mortality, which are instrumental in monitoring the burden of HIV infection and, ultimately, to guide public policies to hold the epidemic back.

Further analyses are needed to guide programmatic interventions among PLHIV in regions with widespread use of cART, by directing special efforts to the evolving morbimortality spectrum of HIV if curbing the HIV/AIDS epidemic is the goal.

The underreporting of both cases and deaths, along with the late diagnosis and entry into care are the main stumbling blocks to the cost-effectiveness of the HIV/AIDS control program in Brazil. These are enduring obstacles the country needs to be cleared of in order to accelerate the HIV response, with new agendas such as the “test and treat” and “treatment as prevention” programs and the implementation of services for key and priority populations, including sex workers, men who have sex with men and imprisoned individuals.

Conclusion

We found a high proportion of underreported deaths among people living with HIV in the state of Rio de Janeiro, indicating that local HIV/AIDS mortality coefficients could be underestimated. The changing patterns of mortality of PLHIV challenges both physicians to consider the broader clinical spectrum of HIV infection and surveillance officers to improve death monitoring.

Acknowledgments

Data were kindly provided by the Department of Chronic Illnesses and Sexually Transmitted Diseases/Brazilian Ministry of Health.

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