Coinfections and In-Hospital Mortality in a Group of Patients With HIV/AIDS: A Longitudinal Study

Abstract

Human immunodeficiency virus (HIV) is a global public health problem. Coinfections in HIV patients are frequent complications that increase their mortality. The aim of this study was to assess coinfections and in-hospital mortality in a group of patients infected with HIV in Colombia. A retrospective longitudinal study was carried out. Patients treated in 4 highly complex clinics in Colombia between 2015 and 2023 were included. The cases were identified from International Classification of Diseases codes related to HIV. Sociodemographic, clinical, laboratory and pharmacological variables were collected. Descriptive, bivariate, and multivariable analyses were performed. Of the 249 patients identified, 79.1% were men, and the median age was 38.0 years. Approximately 81.1% had a diagnosis of acquired immune deficiency syndrome (AIDS). Coinfections caused by Mycobacterium tuberculosis (24.1%) and Treponema pallidum (20.5%) were the most frequent. A total of 20.5% of the patients had sepsis, 12.4% had septic shock, and the fatality rate was 15.7%. Antibiotics and antifungals were used in 88.8% and 53.8%, respectively, of the patients. Patients with a diagnosis of HIV before admission, those infected with M. tuberculosis, and those who presented with sepsis were more likely to die, whereas patients who received antiretroviral agent treatment before admission presented a lower risk. In this study, most HIV patients were in an advanced stage of the disease. Coinfection with M. tuberculosis was common and was associated with an increased risk of death. Previous HIV diagnosis and sepsis also increased the risk. Approximately half of the patients with a previous HIV diagnosis were receiving antiretroviral therapy and had a better prognosis.

Keywords

HIV AIDS coinfection sepsis anti-retroviral agents mortality Colombia

- Human immunodeficiency virus (HIV) is a global public health problem. Coinfections in HIV patients are frequent complications that increase their mortality.

- Of a group of 249 patients with HIV, 81.1% had a diagnosis of acquired immune deficiency syndrome (AIDS).

- Infections caused by Mycobacterium tuberculosis (24.1%) and Treponema pallidum (20.5%) were the most frequent.

- A total of 20.5% had sepsis, 12.4% had septic shock, and the fatality rate was 15.7%.

Introduction

Human immunodeficiency virus (HIV) continues to be a global public health problem.¹ Since the beginning of the acquired immune deficiency syndrome (AIDS) pandemic, more than 40 million people have died from HIV-related diseases.² The World Health Organization (WHO) estimated that by the year 2022, 39 million people were living with HIV worldwide, of whom 1.3 million had contracted it in the past year and 630 000 had died during that same time.¹ Antiretroviral therapy reduces virus transmission, patient morbidity, and mortality.^3,4 Globally, 76% of all people living with HIV in 2022 had access to treatment.² Without treatment, HIV-infected patients progress to AIDS and frequently present complications in different systems (neurocognitive disorders, dyslipidemia, atherosclerosis, kidney failure, etc.).⁵ In addition, they are more susceptible to infections (eg, tuberculosis, candidiasis, toxoplasmosis, and cryptococcosis), as well as some cancers (such as lymphomas and Kaposi’s sarcoma).⁵ Infections are among the main causes of hospitalization in patients with HIV/AIDS.⁶

In Colombia, general data on HIV/AIDS are available.^7,8 There are 141 787 people living with HIV, 53.8% of whom have AIDS.⁷ In 2022, there were 2098 deaths, with an incidence of 4.1 per 100 000 inhabitants.⁷ The percentage of patients with antiretroviral coverage in Colombia is 88.4%.⁷ In patients with HIV/AIDS, tuberculosis is the most common infection and Kaposi’s sarcoma is the most prevalent neoplasm.^7,8 However, there is not much information about the factors involved in the in-hospital mortality of these patients.⁹ Penagos Gaviria et al reported that an increase in the APACHE II score, and the presence of neuroinfections and malignancy increase the risk of death in patients admitted to the intensive care unit.⁹ In Colombia, it is not clear whether the immunological condition, chronicity of HIV and antiretroviral therapy influence the prognosis of these patients. Consequently, these factors need to be examined in more detail. In addition, it is important to know these data in hospitalized patients in general.

The Colombian Health System has a health benefits plan that provides universal coverage to all people through 2 regimes: contributory and subsidized. The contributory regime is paid for people who have a labor contract and their employers, as well as independent workers and pensioners with the ability to pay. The subsidized scheme is paid for by the state. The health benefits plan is the same for both regimens and includes a significant number of medications and outpatient and hospital procedures, including antiretroviral treatment. Therefore, it is necessary to understand the epidemiology of coinfections in patients with HIV/AIDS, their mortality and the factors that influence it, to formulate interventions that would improve the prognosis. The objective of this study was to analyze coinfections and in-hospital mortality in a group of patients infected with HIV in Colombia.

Methods

Study Design and Patients

This observational, longitudinal, and retrospective study was conducted on coinfections and in-hospital mortality in HIV-infected patients. The cases were identified from the International Classification of Diseases, version 10, codes for HIV diseases: B200-B213, B217-B222, B227, B230-B232, B238, B24X, R75X, and Z21X. Patients were also assigned to the Ospedale Group network in 4 clinics located in the cities of Cali, Manizales, Pereira, and Popayán. Patients aged 18 years or older were selected. Patients of any sex and city of residence who were seen between January 1, 2015 and June 30, 2023, were included. The date of first admission to the clinic was considered the index date. The patient’s electronic medical records were individually reviewed during the observation and follow-up periods (until hospital discharge or death). Patients who did not have medical records and those who did not have confirmed HIV and co-infections were excluded. The study has followed the relevant EQUATOR guideline.¹⁰

Variables

From the information obtained, a database that collected the following groups of variables was created:

a. Sociodemographic variables: sex, age, education, affiliated regime (contributory or subsidized), and city/department of origin.

b. Clinical and laboratory

● Vital signs including systolic blood pressure, diastolic blood pressure, heart rate, respiratory rate, oxygen saturation, temperature, and state of consciousness at the time of initial care (the first report in clinical records).

● Anthropometric measurements including weight and body mass index (BMI).

● HIV/AIDS: new diagnosis versus diagnosis before admission, immunological stratification (CD4⁺ T lymphocytes: <200 cells/µL, 200-499 cells/µL and ≥500 cells/µL), and quantitative ribonucleic acid (RNA) analysis of HIV-loaded viruses and AIDS patients.

● Coinfections: including fungal (histoplasmosis, pneumocystosis, cryptococcosis, candidiasis, etc), bacterial (tuberculosis, syphilis, etc), viral (herpes simplex, cytomegalovirus, SARS-CoV-2, hepatitis B and C, etc), and parasitic (amoebiasis, malaria, among others) infections.

Comorbidities including diabetes mellitus, arterial hypertension, dyslipidemia, ischemic heart disease, and heart failure, among other diseases. The age-adjusted Charlson comorbidity index was calculated.

● Laboratory: hemogram, alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, total bilirubin, direct bilirubin, electrolytes (sodium, potassium), urea nitrogen, C-reactive protein, and creatinine at the time of initial care. The glomerular filtration rate (GFR) was calculated via the Chronic Kidney Disease Epidemiology Collaboration (CKD EPI) 2021 equation.

● Complications: The quick Sequential Organ Failure Assessment (qSOFA) score was calculated. Cases of sepsis, septic shock, and in-hospital mortality were identified. In-hospital mortality was considered the outcome of the study.

c. Therapeutics/Management:

● General: time of hospitalization, management in the intensive care unit (ICU), and requirement of invasive mechanical ventilation.

● Antimicrobials: antibiotic drugs (penicillins, sulfonamides, cephalosporins, macrolides, etc.), antifungal drugs (imidazoles, polyenes, etc.), anti-viral drugs (acyclovir, ganciclovir, etc.), and antiparasitic drugs (nitroimidazoles, benzimidazoles, etc.); use of antiretrovirals drugs before admission.

● In-hospital comedications included vasopressors, inotropics, antihypertensive agents, diuretics, antidiabetic agents, anticancer agents, anticoagulants, analgesics, anti-inflammatories, benzodiazepines, systemic glucocorticoids, antipsychotics, antidepressants, antiepileptic agents, and antihistamines.

Ethical Statement

The present protocol was approved by a Bioethics Committee of a University in the category of risk-free research (endorsement code: 02-091120). The ethical principles established by the Declaration of Helsinki were respected. Written informed consent from the subjects before the start of the study was not necessary due to the study design (observational, longitudinal and retrospective).

Data Analysis

The data were analyzed with the statistical package SPSS Statistics, version 26.0 for Windows (IBM, USA). Descriptive analysis was performed with frequencies and proportions for the qualitative variables and measures of central tendency (median) and dispersion (interquartile range, IQR) for the quantitative variables. Quantitative variables were compared via the Mann‒Whitney U test, and categorical variables were compared via the χ² test or Fisher’s exact test.¹¹ Multivariable binary logistic regression models (exploratory) were developed that included the associated variables in the bivariate analyses, as were those that could plausibly (eg, sex, age) be related to in-hospital mortality (yes/no). The Hosmer–Lemeshow test was performed to evaluate the goodness of fit.¹¹ The predictive capacity of the model was determined according to the area under the curve (AUC).¹¹ A P value <.05 was considered to indicate statistical significance. No imputation of missing data was performed. Confounding variables were controlled using exploratory multivariable analysis.

Results

A total 505 patients with an ICD-10 diagnosis related to HIV were identified and 256 patients were excluded (Supplemental Figure 1). A total of 249 patients who had confirmed HIV infection and some form of coinfection were identified from 41 different cities.

Sociodemographic

The median age was 38.0 years (range: 19.0-77.0), and 79.1% (n = 197) were men. A total of 25.3% (n = 63) were less than 30 years old, 51.8% (n = 129) were between 30 and 49 years old, and 22.9% (n = 57) were 50 years old or older. Most of the patients had secondary schooling (n = 107; 43.0%) and were affiliated with the contributory scheme of the health system (n = 152; 61.0%; Table 1).

Table 1.

Sociodemographic, Clinical and Paraclinical Variables of a Group of 249 Patients Infected With HIV, Treated in 4 Tertiary Care Clinics, Colombia.

Variables	Total
Variables	n = 249	%
Sociodemographic	-	-
Male (n = 249; 100%)	197	79.1
Age, median (IQR; n = 249; 100%)	38.0 (29.0-49.0)
Department of origin (n = 249; 100%)	-	-
Risaralda	97	39.0
Cauca	84	33.7
Valle del Cauca	50	20.1
Caldas	16	6.4
Others	2	0.8
Affiliation regime to the health system (n = 244; 98%)	-	-
Contributory	152	61.0
Subsidized	92	36.9
Comorbidities	-	-
Charlson index, median (IQR; n = 249; 100%)	6.0 (6.0-8.0)
Malnutrition	57	22.9
Chronic kidney disease	29	11.6
Solid neoplasms	23	9.2
Arterial hypertension	20	8.0
Hypothyroidism	12	4.8
Vital signs (on admission), median (IQR)	-
Systolic blood pressure (mmHg; n = 212; 85.1%)	110.5 (100.0-120.0)
Diastolic blood pressure (mmHg; n = 212; 85.1%)	70.0 (60.0-75.0)
Heart rate (bpm; n = 212; 85.1%)	80.0 (75.0-96.8)
Respiratory rate (rpm; n = 208; 83.5%)	20.0 (18.0-20.0)
Temperature (°C; n = 204; 81.9%)	36.4 (36.0-37.0)
Oxygen saturation (%; n = 208; 83.5%)	96.0 (94.0-97.0)
State of consciousness (Glasgow; n = 218; 87.6%)	15.0 (15.0-15.0)
Anthropometric measurements, median (IQR)	-
Weight (kg; n = 62; 24.9%)	55.0 (45.8-63.5)
Body mass index (kg/m2; n = 49; 19.7%)	19.7 (17.3-23.5)
Laboratory studies, median (IQR)	-
Hemogram	-
Hemoglobin (g/dL; n = 239; 96%)	11.6 (9.9-13.3)
Hematocrit (%; n = 239; 96%)	34.5 (30.0-39.5)
Leukocytes (/mm³; n = 242; 97.2%)	6360.0 (4060.0-8945.0)
Neutrophils (/mm³; n = 240; 96.4%)	3950.0 (2357.5-6200.0)
Lymphocytes (/mm³; n = 227; 91.2%)	1120.0 (660.0-1800.0)
Platelets (mil/mm³; n = 241; 96.8%)	256 000.0 (172 000.0-334 500.0)
Renal function	-
Creatinine (mg/dL; n = 223; 89.6%)	0.8 (0.7-1.1)
Glomerular filtration rate (mL/min; n = 223; 89.6%)	110.6 (83.6-123.2)
Urea nitrogen (mg/dL; n = 199; 79.9%)	13.6 (10.0-19.9)
Liver function	-
Total bilirubin (mg/dL; n = 113; 45.4%)	0.5 (0.3-1.0)
Direct bilirubin (mg/dL; n = 118; 47.4%)	0.3 (0.2-0.5)
Alanine aminotransferase (U/L; n = 135; 54.2%)	33.0 (19.0-61.0)
Aspartate aminotransferase (U/L; n = 133; 53.4%)	40.0 (23.0-107.5)
Lactic acid dehydrogenase (U/L; n = 90; 36.1%)	252.5 (185.5-523.5)
Electrolytes	-
Sodium (mEq/L; n = 190; 76.3%)	135.0 (132.0-139.0)
Potassium (mEq/L; n = 194; 77.9%)	4.1 (3.7-4.5)
C-reactive protein (mg/L; n = 172; 69.1%)	41.9 (10.1-100.0)

Note. HIV = human immunodeficiency virus; IQR = interquartile range.

Clinical and Laboratory

A total of 71.5% (n = 178) of the patients knew their HIV status before admission, and 53.4% (n = 95/178) were on antiretroviral medication. A total of 81.1% (n = 202) had AIDS. Information on the immunological stratification of HIV was found for 54.2% (n = 135) of the patients. The median CD4⁺ T lymphocyte count was 66.0/µL (IQR: 26.0-167.0), and the majority had <200 cells/µL (n = 106/135; 78.5%). The median quantitative HIV RNA concentration was 172 200 copies/mL (IQR: 7722.8-566 000.0), and only 11.1% (n = 14/126) had an undetectable viral load or <50 copies/mL.

The median Charlson comorbidity index was 6 points (range: 0.0-16.0), and endocrine (n = 27; 10.8%) and cardiovascular (n = 26; 10.4%) comorbidities and neoplasms were the most common. A total of 12.4% (n = 31) were active smokers, and 9.6% (n = 24) were consumers of psychoactive substances. At the time of the initial medical assessment, 80.3% (n = 200) of the patients had diagnoses related to infections. The median qSOFA score was 0.0 (IQR: 0.0-1.0), 34.9% (n = 87) had a qSOFA score 1 point at admission and 6.8% (n = 17) had a qSOFA score ≥ 2 points at admission. Some 66.9% (n = 160/239) had anemia, 24.0% (n = 58/242) had leukopenia, and 7.1% (n = 17/241) had thrombocytopenia. The vital signs, anthropometric measurements, and baseline paraclinical data of the patients are listed in Table 1.

The patients had concomitant infections, mainly involving Mycobacterium tuberculosis (24.1%) and Treponema pallidum (20.5%; Table 2). A total of 20.5% (n = 51) presented with sepsis during hospitalization, 12.4% (n = 31) had septic shock, and 15.7% (n = 39) died during the hospital stay. The median time of death was 7.0 days (IQR: 3.0-21.0; range: 0.0-49.0) after admission.

Table 2.

Coinfections, Antimicrobials and Comedications Used in a Group of 249 Patients Infected With HIV, Treated in 4 High-Complexity Clinics, Colombia.

Variables	Total
Variables	n = 249	%
Coinfections
Mycobacterium tuberculosis infection	60	24.1
Treponema pallidum infection	51	20.5
Community-acquired pneumonia	51	20.5
Acute diarrheal disease	48	19.3
Superficial candidiasis	29	11.6
Toxoplasma gondii infection	28	11.2
Histoplasma capsulatum infection	26	10.4
Pneumosistis jiroveci infection	26	10.4
Deep candidiasis	25	10.0
Cytomegalovirus infection	18	7.2
Herpes simplex virus infections	17	6.8
Urinary tract infection	17	6.8
Bacteremia	16	6.4
Herpes zoster virus infections	13	5.2
Skin and soft tissue	13	5.2
Cryptococcus neoformans infection	12	4.8
Hepatitis B virus infection	8	3.2
SARS-CoV-2 infection	8	3.2
Hepatitis A virus infection	2	0.8
Hepatitis C virus infection	2	0.8
Plasmodium falciparum malaria	2	0.8
Neurocysticercosis	2	0.8
Liver abscess	1	0.4
Pelvic inflammatory disease	1	0.4
Antimicrobials
Antibiotics	221	88.8
Sulfonamides	154	61.8
Penicillins	126	50.6
Macrolides	97	39.0
Cephalosporins	61	24.5
Glycopeptides	41	16.5
Carbapenems	31	12.4
Lincosamides	27	10.8
Fluoroquinolones	25	10.0
Aminoglycosides	7	2.8
Oxazolidinones	5	2.0
Tetracyclines	4	1.6
Monobactams	1	0.4
Nitrofurans	1	0.4
Antifungals	147	59.0
Imidazoles	134	53.8
Polyenes (systemic)	31	12.4
Polyenes (oral)	27	10.8
Echinocandins	7	2.8
Flucytosine	4	1.6
Antiretrovirals	48	19.3
Nucleoside reverse transcriptase inhibitors	41	16.5
Non-nucleoside reverse transcriptase inhibitors	26	10.4
Integrase inhibitors	12	4.8
Protease inhibitors	7	2.8
Antiparasitics	46	18.5
Nitroimidazoles	36	14.5
Benzimidazoles	11	4.4
Ivermectin	4	1.6
Antivirals	45	18.1
Acyclovir/valacyclovir	27	10.8
Ganciclovir/valganciclovir	19	7.6
Comedications
Analgesics/anti-inflammatories	176	70.7
Antiulcerants	174	69.9
Anticoagulants	88	35.3
Systemic glucocorticoids	72	28.9
Antispasmodics	57	22.9
Benzodiazepines	43	17.3
Antihypertensives/diuretics	39	15.7
Antiepileptics	35	14.1
Antihistamines	35	14.1
Antidepressants	34	13.7
Inhaled bronchodilators/glucocorticoids	33	13.3
Antipsychotics	31	12.4
Vasopressors/inotropes	21	8.4
Antiplatelet agents	10	4.0
Hypolipidemics	10	4.0

Note. HIV = human immunodeficiency virus; SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2.

Treatment

The median hospital stay was 8.0 days (IQR: 2.5-18.0; range: 0.0-66.0). In total of 16.9% (n = 42) of the patients required intensive care units (ICU) management, and 9.2% (n = 23) received invasive mechanical ventilation. Most of the patients were managed with antibiotics (n = 221; 88.8%), especially sulfonamides (n = 154; 61.8%), penicillins (n = 126; 50.6%), and antifungals (n = 147; 59.0%), mainly imidazoles (n = 134; 53.8%). Only 19.3% of the patients received antiretroviral treatment during their hospital stay. The antimicrobial agents and comedications received by the patients during hospitalization are listed in Table 2.

Multivariate Analysis

Binary logistic regression adjusted for sociodemographic, clinical and pharmacological variables revealed that patients who had a previous diagnosis of HIV, were coinfected by M. tuberculosis and presented with sepsis were more likely to die during hospitalization, whereas those who were receiving antiretroviral treatment before admission had a lower risk (Hosmer-Lemeshow test P = .948 and area under the curve = 0.913, 95% CI: 0.865-0.961; Table 3).

Table 3.

Binary Logistic Regression of the Variables Related to In-Hospital Mortality in Patients Infected With HIV, and Treated in 4 High-Complexity Clinics, Colombia.

Variables	Sig.	OR	95% CI
Variables	Sig.	OR	Lower	Upper
Man (yes/no)	.178	0.437	0.131	1.456
Age (continuous)	.057	1.038	0.999	1.078
Contributory affiliation regime (yes/no)	.584	0.717	0.218	2.358
Care in Clinic 1 (yes/no)	.372	1.668	0.542	5.130
Charlson comorbidity index (continuous)	.274	1.126	0.910	1.394
HIV diagnosis prior to admission (yes/no)	.033	3.720	1.113	12.430
Previous treatment with antiretrovirals (yes/no)	.016	0.227	0.068	0.760
QuickSOFA on admission (continuous)	.111	1.740	0.881	3.436
Sepsis (yes/no)	<.001	23.715	8.019	70.137
Pancytopenia on admission (yes/no)	.238	2.558	0.537	12.176
Coinfection with tuberculosis (yes/no)	.011	4.436	1.402	14.038
Use of antibiotics (yes/no)	.535	0.587	0.109	3.153
Use of antifungals (yes/no)	.286	0.548	0.181	1.655
Use of antivirals (yes/no)	.616	0.730	0.213	2.498
Comedication with systemic glucocorticoids (yes/no)	.254	1.899	0.630	5.723
Comedication with antihypertensives/diuretics (yes/no)	.195	2.440	0.633	9.399

Note. HIV = human immunodeficiency virus; Sig = statistical significance; OR = odds ratio; CI = confidence interval; qSOFA = Quick Sequential Organ Failure Assessment.

Discussion

We determined the clinical and laboratory characteristics of patients with HIV from Colombia who were hospitalized for complications of an infectious nature, as well as the microorganisms identified, the antimicrobial treatment they received, the severity of the condition, and the proportion of patients who died during their hospitalization. M. tuberculosis infection was the most frequent co-infection found in HIV-positive patients. In-hospital mortality was 15.7%, especially in patients with sepsis or tuberculosis. This information is useful for informing physicians, hospital administrators, and decision-makers regarding the treatment needs of this group of patients.

The median age of the patients was similar to that reported in other Colombian studies (38.0-39.0 years)^9,12,13 and lower than that reported in other international studies (38.0 vs 45.0-46.7 years),^14,15 with a predominance of men identified in all the studies (79.1% vs 69.8%-92.7%).^9,12
-19 This group of patients is characterized by a history of HIV, an advanced stage of disease, and a high viral load, in line with other local^9,12,13,16 and international^17,19
-21 studies. In one English report, the proportion of patients with undetectable viral loads was greater (46.0%).¹⁴

In different observational studies, in-hospital fatality rates between 8.5% and 58.2% have been reported.^13,16
-21 The proportion of patients who died was similar to that observed in earlier studies in Colombia (13.8%)¹⁶ and in Asian countries (8.5%-9.0%)^17
-19 but lower than that reported in African countries (15.7% vs 30.1%-53.9%).^20,21 The proportion of deaths was greater when the studies included only patients managed in the ICU (38.5%-58.2%).^13,14 These variations in the probability of dying are influenced by methodological aspects of the studies, such as the inclusion and exclusion criteria, the severity and progression of disease, adherence to the clinical practice guidelines, and the resources available in each country for the comprehensive care of these patients.^13,16
-21

According to the World Tuberculosis Report, people living with HIV are 18 times more likely to develop active tuberculosis than people who do not have HIV.²² These data are in line with our findings: the most common coinfection was caused by M. tuberculosis, which is consistent with findings in Colombia (37.0%-38.0%)^9,16 and Sierra Leone (24.3%).²⁰ In contrast, other studies have shown a predominance of lower respiratory tract infections without specifying their etiology (28.4%-39.8%).^14,15,18 In studies conducted in Asian countries, fungal infections predominated^17,19,23: In China, candidiasis prevailed (50.4%),¹⁷ whereas in Qatar and Shanghai, Pneumocystis jirovecii infections were common (25.0%-42.1%).^19,23 According to the WHO, in 2019 tuberculosis was the leading cause of death among people infected with HIV, accounting for 30% of the 690 000 AIDS-related deaths worldwide.²⁴ In an observational study in China, Li et al reported that hospitalized patients with HIV and tuberculosis had a greater risk of death (hazard ratio [HR] = 2.22; 95% CI = 1.32-3.74),¹⁷ a finding that is consistent with this report.

Most of the patients had an HIV diagnosis before admission, as in other studies (65.4%-82.8%).^9,13
-15 These patients had a greater risk of dying. This is probably because their longer disease course made them more likely to be at an advanced pathological stage, especially if they did not receive antiretroviral therapy or did not adequately adhere to this treatment.²⁵ On the other hand, one-fifth of the patients presented with sepsis during their hospital stay, which is consistent with a previous study in Colombia (30%)⁹ and higher than rates reported in China (2.5%),¹⁸ Sierra Leone (3.5%),²⁰ and France (12.3%).¹⁵ This group of people had the highest risk of dying during their hospital stay. A meta-analysis of 17 studies (n = 82 905 patients) revealed that mortality from sepsis was 28% higher in HIV-infected patients, especially in those treated in low-income countries.²⁶ Therefore, adequate adherence to sepsis management protocols is crucial to improve prognosis in these patients.^27,28 However, in this study the qSOFA score was not associated with an increased risk of mortality. A systematic review and meta-analysis revealed that the qSOFA score has low sensitivity and specificity for determining in-hospital mortality.²⁹ On the other hand, different studies have shown that an increase in the APACHE II score,^9,14 a reduction in CD4⁺ lymphocytes,¹² and the presence of neuroinfections,^9,12 malignancy,^9,15,17 or liver disease^15,20 increase the risk of death^{9,12,14,15,17,20}; these factors were not found in this cohort.

Patients who were receiving antiretroviral treatment had a lower risk of dying. This finding is consistent with 2 studies conducted in the Chinese population¹⁷ and in Colombia,¹³ that yielded real-world evidence. Antiretroviral therapy suppresses the viral load, preserves or improves immune function, and reduces the risk of opportunistic infections and cancer, increasing survival, improving quality of life, and preventing HIV transmission.⁴ However, just over half of the patients were receiving antiretroviral therapy, which is consistent with what has been reported in other studies in Colombia (31.8%-62.0%),^9,12,13,16 Africa (37.0%-60.7%),^20,21 Europe (58.9%-71.8%),^14,15 and Asia (43.3%-72.7%).^17,19 This is far from the goals of antiretroviral therapy access proposed by the WHO for the year 2025¹ and from global and national reports of the proportion of patients in treatment (76.0% and 88.4%, respectively).^2,7 In addition, the proportion of patients who received antiretroviral medication during hospitalization was even greater than that in other cohorts (19.3% vs 12.0%-15.0%).^30,31 In some opportunistic infections (eg, cytomegalovirus retinitis, cryptococcosis, and tuberculosis), temporarily delaying the start of antiretroviral therapy is preferred because of the potentially fatal induction of immune reconstitution inflammatory syndrome.^32,33 Adherence to antiretroviral therapy should continue to increase to reduce morbidity and mortality in HIV-infected patients.³⁴

Certain limitations inherent to observational studies should be considered when interpreting our results. First, the information was obtained from the registered data of a group of patients from 4 tertiary-care clinics located in different cities, consequently, the findings may not be extrapolated to all types of health care institutions or to all regions of the country. In addition, for some variables, information was not available from all patients because the data were taken from medical records. There was also no information on the antiretroviral treatment regimens that patients had previously received information, nor adherence to therapy. Immunological stratification was not available for all patients. The information obtained could not determine whether the prescribed antimicrobials were used empirically or under laboratory guidance. Binary logistic regression had wide confidence intervals for some variables, however, the goodness of fit of the multivariate model was very good. Finally, sample size and power analyses were not performed because this study was descriptive that and included an exploratory multivariable analysis.

Conclusions

In this study most HIV patients were in an advanced stage of the disease. Coinfection with M. tuberculosis was common and was associated with an increased risk of death. Previous HIV diagnosis and sepsis also increased the risk. Approximately half of the patients with a previous HIV diagnosis were receiving antiretroviral therapy and had a better prognosis. Efforts should be strengthened to achieve the antiretroviral therapy goals set by the WHO.

Supplemental Material

sj-jpg-1-inq-10.1177_00469580241288429 – Supplemental material for Coinfections and In-Hospital Mortality in a Group of Patients With HIV/AIDS: A Longitudinal Study

Supplemental material, sj-jpg-1-inq-10.1177_00469580241288429 for Coinfections and In-Hospital Mortality in a Group of Patients With HIV/AIDS: A Longitudinal Study by Luis Fernando Valladales-Restrepo, María Camila Oyuela-Gutiérrez, Catalina Díaz-Arteaga, María Alejandra Torres-Campo, Allyson Rengifo-Montes, Alfonso Sebastián Erazo-De Los Ríos, Alejandra Sabogal-Ortiz, Manuel Enrique Machado-Duque, Andrés Gaviria-Mendoza and Jorge Enrique Machado-Alba in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

Acknowledgements

We thank Ximena Andrea Córdoba Castro for her work in obtaining the database.

Author Contributions

LFVR participated in the article drafting, data collection, data analysis, description of results and discussion of the findings. MCOG participated in the article drafting, description of results, and discussion of the findings. CDA participated in the article drafting, description of results, and discussion of the findings. MATC participated in the article drafting, description of results, and discussion of the findings. ARM participated in the article drafting, description of results, and discussion of the findings. ASED participated in the article drafting, description of results, and discussion of the findings. ASO participated in the article drafting, description of results, and discussion of the findings. MEMD participated in the article drafting, data analysis, description of results, and discussion of the findings. AGM participated in the article drafting, data analysis, description of results, and discussion of the findings. JEMA participated in the article drafting, data collection, data analysis, description of results, discussion, critical revision of the article, and evaluation of the final version of the manuscript.

Data Availability

https://www.protocols.io/private/80F4542CE14411EEA5730A58A9FEAC02

Data Access

DOI: dx-doi-org.web.bisu.edu.cn/10.17504/protocols.io.yxmvm3dj5l3p/v1

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethics Approval

The present protocol was approved on February 13, 2023 by the Bioethics Committee of the Universidad Tecnologica de Pereira in the category of risk-free research (endorsement code: 02-091120). The ethical principles established by the Declaration of Helsinki were respected. Written informed consent from the subjects before the start of the study was not necessary due to the study design (observational, longitudinal, and retrospective).

ORCID iDs

Luis Fernando Valladales-Restrepo

Andrés Gaviria-Mendoza

Supplemental Material

Supplemental material for this article is available online.

References

World Health Organization. HIV and AIDS. Accessed: November 28, 2023. https://www.who.int/news-room/fact-sheets/detail/hiv-aids

ONUAIDS. Global HIV & AIDS statistics. Accessed: November 23, 2023. https://www.unaids.org/es

Bekker

Beyrer

Mgodi

, et al. HIV infection. Nat Rev Dis Primers. 2023;9(1):42. doi:10.1038/s41572-023-00452-3

WHO. Global HIV Programme: Treatment & Care. World Health Organization. Accessed November 28, 2023. https://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/hiv/treatment

Chu

Selwyn

PA.

Complications of HIV infection: a systems-based approach. Am Fam Physician. 2011;83(4):395-406.

Ford

Shubber

Meintjes

, et al. Causes of hospital admission among people living with HIV worldwide: a systematic review and meta-analysis. Lancet HIV. 2015;2(10):e438-e444. doi:10.1016/S2352-3018(15)00137-X

Cuenta de Alto Costo (CAC), Fondo Colombiano de Enfermedades de Alto Costo, Cuenta de Alto Costo (CAC). Situación del VIH en Colombia, 2022; 2023. Accessed November 23, 2023. https://cuentadealtocosto.org/vih/

Castillo-Cañón

Trujillo-Cáceres

Álvarez-Moreno

, et al. Colombian HIV/AIDS registry and health risk management. Infectio. 2021;26:113-120. doi:10.22354/in.v26i2.1009

Penagos Gaviria

Zapata

Villa

, et al. HIV/AIDS infection in critical care: epidemiological profile and risk factors for mortality in a Colombian cohort. J Infect Dev Ctries. 2023;17(01):102-110. doi:10.3855/jidc.15859

10.

von Elm

Altman

Egger

Pocock

Gotzsche

Vandenbroucke

. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Accessed August 20, 2024. https://www.goodreports.org/reporting-checklists/strobe-cross-sectional/

11.

IBM Corp. IBM SPSS Statistics for Windows, Version 26.0. IBM Corp; Core features 2019. Accessed June 24, 2023. https://www.ibm.com/docs/en/spss-statistics/26.0.0?topic=edition-core-features

12.

Torres-Urazán

Cajicá-Martínez

Valencia-Enciso

Espinosa-Jovel

Characterisation and variables associated with mortality in a population with HIV and central nervous system opportunistic infections in a Colombian public hospital in Bogotá. Neurol Perspect. 2023;3(3):100127. doi:10.1016/j.neurop.2023.100127

13.

Ruiz

Herrera

CFL

Bohórquez

JAM

Betancur

JE.

Mortality in patients with acquired human immunodeficiency virus infection hospitalized in an intensive care unit during the period 2017–2019. Sci Rep. 2022;12(1):15644. doi:10.1038/s41598-022-19904-z

14.

Kanitkar

Dissanayake

Bakewell

, et al. Changes in short-term (in-ICU and in-hospital) mortality following intensive care unit admission in adults living with HIV: 2000-2019. AIDS. 2023;37(14):2169-2177. doi:10.1097/QAD.0000000000003683

15.

Gaillet

Azoulay

de Montmollin

, et al. Outcomes in critically ill HIV-infected patients between 1997 and 2020: analysis of the OUTCOMEREA multicenter cohort. Crit Care. 2023;27(1):108. doi:10.1186/s13054-023-04325-9

16.

Montúfar Andrade

Quiroga

Builes

, et al. Epidemiología de la infección por el virus de inmunodeficiencia humana en pacientes hospitalizados en una institución de alta complejidad y enseñanza universitaria en Medellín, Colombia. Infectio. 2016;20(1):9-16. doi:10.1016/j.infect.2015.05.004

17.

Zhou

Wang

, et al. In-hospital mortality and causes of death in people diagnosed with HIV in a General Hospital in Shenyang, China: A cross-sectional study. Front Public Health. 2021;9:774614. doi:10.3389/fpubh.2021.774614

18.

Meng

Tang

Xie

, et al. Spectrum and mortality of opportunistic infections among HIV/AIDS patients in southwestern China. Eur J Clin Microbiol Infect Dis. 2023;42(1):113-120. doi:10.1007/s10096-022-04528-y

19.

Luo

Sun

Cai

, et al. Spectrum of opportunistic infections and risk factors for In-hospital mortality of admitted AIDS patients in Shanghai. Medicine. 2016;95(21):e3802. doi:10.1097/MD.0000000000003802

20.

Lakoh

Jiba

Kanu

, et al. Causes of hospitalization and predictors of HIV-associated mortality at the main referral hospital in Sierra Leone: a prospective study. BMC Public Health. 2019;19(1):1320. doi:10.1186/s12889-019-7614-3

21.

Lamprecht

Martinson

Variava

Effect of HIV on mortality among hospitalised patients in South Africa. South Afr J HIV Med. 2023;24(1):1477. doi:10.4102/sajhivmed.v24i1.1477

22.

WHO. Global Tuberculosis Report 2020. World Health Organization. Accessed: November 23, 2023. https://www.who.int/publications/i/item/9789240013131

23.

Ali

Razok

Gassim

, et al. HIV and AIDS-defining opportunistic illnesses in the state of Qatar: a cohort population-based retrospective study covering 17 years (2000-2016). Ann Med Surg. 2022;78:103842. doi:10.1016/j.amsu.2022.103842

24.

WHO. Global HIV Programme: Tuberculosis & HIV. World Health Organization. Accessed November 23, 2023. https://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/hiv/treatment/tuberculosis-hiv

25.

Melhuish

Lewthwaite

Natural history of HIV and AIDS. Medicine. 2022;50(5):298-303. doi:10.1016/j.mpmed.2022.02.011

26.

Pyarali

Iordanov

Palacio

Tamariz

Excess mortality risk from sepsis in patients with HIV - a meta-analysis. J Crit Care. 2020;59:101-107. doi:10.1016/j.jcrc.2020.05.018

27.

Evans

Rhodes

Alhazzani

, et al. SIRS, SOFA, qSOFA, and NEWS in the diagnosis of sepsis and prediction of adverse outcomes: a systematic review and meta-analysis. Intensive Care Med. 2021;49(11):1974-1982. doi:10.1097/CCM.0000000000005357

28.

Guarino

Perna

Cesaro

, et al. 2023 update on sepsis and septic shock in adult patients: management in the emergency department. J Clin Med. 2023;12(9):3188. doi:10.3390/jcm12093188

29.

Qiu

Lei

Zhou

RX.

SIRS, SOFA, qSOFA, and NEWS in the diagnosis of sepsis and prediction of adverse outcomes: a systematic review and meta-analysis. Expert Rev Anti-Infect Ther. 2023;21(8):891-900. doi:10.1080/14787210.2023.2237192

30.

Jacobs

Feaster

Pan

, et al. Initiation of antiretroviral therapy in the hospital is associated with linkage to human immunodeficiency virus (HIV) care for persons living with HIV and substance use disorder. Clin Infect Dis. 2021;73(7):e1982-e1990. doi:10.1093/cid/ciaa838

31.

Goswami

Colasanti

Khoubian

Huang

Armstrong

del Rio

A minority of patients newly diagnosed with AIDS are started on antiretroviral therapy at the time of diagnosis in a large public hospital in the Southeastern United States. J Int Assoc Providers AIDS Care. 2017;16(2):174-179. doi:10.1177/2325957417692679

32.

Vinhaes

Araujo-Pereira

Tibúrcio

, et al. Systemic inflammation associated with immune reconstitution inflammatory syndrome in persons living with HIV. Life. 2021;11(1):65. doi:10.3390/life11010065

33.

Brust

McGowan

Fine

, et al. Management of IRIS. Johns Hopkins University; 2021.

34.

Kanters

Park

Chan

, et al. Interventions to improve adherence to antiretroviral therapy: a systematic review and network meta-analysis. Lancet HIV. 2017;4(1):e31-e40. doi:10.1016/S2352-3018(16)30206-5

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB