Antiretroviral therapy-naïve people living with HIV tend to have more severe symptoms of COVID-19
Notice bibliographique
Résumé
To the Editor: Coronavirus disease 2019 (COVID-19), instigated by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has manifested as a formidable global pandemic, precipitating significant economic implications and leading to extensive mortalities. Simultaneously, the acquired immune deficiency syndrome (AIDS) epidemic caused by the human immunodeficiency virus (HIV) persists as a salient global health exigency. Cumulatively by the termination of 2022, AIDS-related pathologies accounted for approximately 40.4 million fatalities, with an extant global HIV population of roughly 39 million people living with HIV (PLWH), as a potentially immunocompromised population, have received limited attention in the realm of COVID-19 research. The majority of existing studies have compared HIV-treated subjects with their HIV-negative counterparts. Of the global tally of HIV cases, an estimated 9.2 million PLWH who have not received antiretroviral therapy (ART) might be at a more pronounced immunodeficiency risk than those on ART.[1] The discrepancy in COVID-19 severity and clinical presentation between ART-experienced and ART-naïve PLWH has yet to be comprehensively understood. In light of this, our study endeavors to illuminate the distinctions in COVID-19 severity between ART-experienced and ART-naïve PLWH through a retrospective case–control analysis. The research protocols received ethical approval from the Shanghai Public Health Clinical Center (SPHCC) Ethics Committee (No. 2021-S051-01). The committee decided to waive the need for written informed consent from the participants in the study because the data were analyzed retrospectively and anonymously. In this retrospective case–control study, we opted for a case–control group allocation ratio of 1:2. This decision was motivated by the relatively low prevalence of cases in the target population. We calculated the sample size to meet the requirements of a two-tailed test with a significance level (α) of 0.05 and a power (β) of 0.9. The estimated disease rate in the control group was 0.25, and the expected odds ratio (OR) was set at 4. Based on these calculations, we determined a minimum sample size of 44 cases and 88 controls. Medical records of patients hospitalized and co-infected with HIV and SARS-CoV-2 from March 2022 to July 2023 were meticulously collated in SPHCC. The parameters of interest encompassed age, gender, CD4+ T cell count, CD4+ T cell/CD8+ T cell ratio, HIV RNA viral load, ART history, specific ART regimen and its duration, concurrent comorbidities, clinical manifestations, imaging manifestations of COVID-19 pneumonia, status of COVID-19 vaccination, and duration of SARS-CoV-2 viral shedding. The values for CD4+ T cell count, CD4+ T cell/CD8+ T cell ratio, and HIV RNA viral load were extrapolated from the most proximate test results post-COVID-19 diagnosis. Clinically, symptoms documented comprised fever, cough with expectoration, chest tightness, weakness, and peak body temperature. Radiologically, COVID-19 pneumonia is typically presented as bilateral ground-glass opacities and infiltrative patterns. Virus shedding time is defined as the interval from the initial positive nucleic acid test result to its eventual negation. Participants were divided into ART-naïve and ART-experienced groups based on whether they were undergoing ART at the time of COVID-19 diagnosis. The basic and clinical characteristics of the two groups were compared. COVID-19 includes the following five clinical classifications according to Corona Virus Disease 2019 Diagnosis and Treatment Program (Trial 10th Edition):[2] asymptomatic, mild, moderate, severe, and critical. Continuous variables with normal distribution were represented as the mean ± standard deviation (SD), and compared by Student's t-test. Continuous variables with non-normal distribution were represented by the median, interquartile range (IQR), and compared using the Wilcoxon rank-sum test. Categorical variables and ordinal data were represented as frequency (percentage) and compared using the χ2 test. All analyses were performed using the Stata Statistical Software 16 (StataCorp., TX, USA). Drawing pictures using GraphPad Prism version 9.0.0 (GraphPad Software, San Diego, CA, USA). In this study, the clinical classification of COVID-19 acted as the dependent variable (asymptomatic, mild and moderate, severe and critical), mirroring the spectrum of disease severity. The independent variables encompassed factors such as age (>65 years old vs. ≤65 years old), CD4+ T cell count (<200 cell/mm3vs. ≥200 cell/mm3), vaccination status (without vaccination vs. with vaccination), ART treatment (ART-naïve vs. ART-experienced), and the presence of comorbidities (with comorbidities vs. without comorbidities). We employed a multivariate ordinal logistic regression analysis to discern risk factors that potentially modulate disease severity. Effect sizes were characterized using ORs accompanied by their 95% confidence intervals (CIs). These insights were further graphically illustrated through a forest plot. Additionally, a survival time analysis was undertaken to juxtapose the viral shedding durations between the ART-naïve and ART-experienced cohorts. The log-rank test facilitated the comparison of survival curves across these groups. Observations yielding a P-value below 0.05 were deemed to hold statistical significant difference. This study enrolled a total of 132 participants, including 125 males and 7 females. The average age of the participants was 45 years old. The median CD4+ T cell count and CD4+ T cell/CD8+ T cell ratios were 72.58 cells/mm3 and 0.21, respectively, and the median HIV RNA was 5.13 log10 copies/mL. Forty-six (34.85%) patients had opportunistic infections, the most frequent type being fungus. Sixty-eight (51.51%) patients had comorbidities, with lymphoma accounting for the largest number (11 [8.33%]). In addition, 98 patients (74.24%) were vaccinated with the SARS-CoV-2 vaccine. There were 44 participants in the ART-naïve group and 88 participants in the ART-experienced group. The average age of the ART-naïve group was younger than that of the ART-experienced group (41.52 years old vs. 47.46 years old, t = 2.164, P = 0.032), while there was no significant difference in gender distribution between the two groups. The CD4+ cell count (cells/mm3) and CD4+/CD8+ ratio in the ART-naïve group were both lower than those in the ART-experienced group (18.34 vs. 127.94, Z = 5.914, P = 0.001; 0.07 vs. 0.58, Z = 5.950, P = 0.001), while HIV viral load (log10 copies/mL) and the proportion of opportunistic infections was higher in the ART-experienced group (5.83 vs. 1.34, Z = -4.405, P = 0.001, 52.27% [23/44] vs. 25.64% [23/88], χ 2 = 8.187, P = 0.004). The proportion of participants vaccinated with the SARS-CoV-2 vaccine did not differ between the two groups. In the ART-experienced group, the median duration of ART was 4 years, and the most frequently used ART regimen was non-nucleoside reverse transcriptase inhibitors (NNRTIs) based therapy (41/88 [31.06%]) [Supplementary Table 1, https://links.lww.com/CM9/B782]. Among all the subjects, the predominant clinical manifestations were fever and cough (93 [70.45%], 82 [62.12%]), while chest tightness and fatigue were less frequent (48 [36.36%], 44 [33.33%]). The mean of the highest fever temperature was 38.86℃ and there were 45 (34.09%) participants with imaging manifestations of COVID-19 pneumonia. In terms of clinical classification, 87 (65.90%) were asymptomatic and mild, while 40 (30.30%) were moderate and 5 (3.79%) were severe and critical. Seventy-three (55.30%) subjects received anti-SARS-CoV-2 drugs. In terms of clinical outcome, one subject died in the ART-naïve group and all the rest survived at discharge. All clinical symptoms were present in a higher percentage in ART-naïve group than in ART-experienced group, which were fever (41 [93.18%] vs. 52 [59.09%], χ2 = 16.454, P = 0.001), cough and expectoration (34 [77.27%] vs. 48 [54.54%], χ2 = 6.687, P = 0.009), chest tightness (28 [63.63%] vs. 20 [22.72%], χ2 = 21.56, P = 0.001), and weakness (22 [50.00%] vs. 22 [25.00%], χ2 = 8.250, P = 0.004). The maximum fever temperature (39.05℃ vs. 38.71℃, t = 1.756, P = 0.043) and percentage of imaging manifestations (24 [54.54%] vs. 21 [23.86%], χ2 = 8.769, P = 0.003) was also higher in ART-naïve group. Consequently, the clinical classification of the two groups also showed significant differences, with a lower percentage of mild and asymptomatic cases (20 [45.45%] vs. 67 [76.14%], χ2 = 12.38, P = 0.001) in ART-naïve group [Supplementary Table 1, https://links.lww.com/CM9/B782]. Ordinal logistic regression indicated that the absence of ART, but not age, SARS-CoV-2 vaccination, comorbidities, and low CD4+ T cell count was a risk factor for the severity of COVID-19 among PLWH, with an OR of 5.06 (95% confidence interval [CI] 1.71–14.92, P = 0.003) [Figure 1A]. The loss to follow-up rate in the ART-naïve group for the virus shedding duration was 18.2% (8/44), while in the ART-experienced group, it was 19.3% (17/88). Kaplan–Meier curve showed that the viral shedding time in the ART-naïve group was longer than that in the ART-experienced group (median 30 days vs. 15 days, P = 0.015, hazard ratio = 0.536) [Figure 1B].Figure 1: Ordinal logistic regression analysis of factors influencing the severity of COVID-19 in PLWH (A) and the Kaplan–Meier curves of viral shedding time between two groups (B). ART: Antiretroviral therapy; CI: Confidence interval; COVID-19: Coronavirus disease 2019; PLWH: People living with HIV.Multiple reasons can be posited for the heightened clinical severity observed in the ART-naïve group relative to the ART-treated cohort. Primarily, PLWH who are not under ART might grapple with immune insufficiencies, which potentially impede the efficient elimination of SARS-CoV-2. This could also heighten their susceptibility to opportunistic infections, further intensifying the severity of COVID-19. In this study, a strikingly low median CD4+ T cell count of merely 18 cells/mm3 was noted, indicative of profound immunosuppression. Analogous studies focusing on other immune-deficient demographics, like organ transplant beneficiaries and those with hematologic malignancies, have similarly underlined augmented COVID-19 severity compared to their immunocompetent peers. Such findings buttress the premise that compromised immunity is a pivotal determinant in adverse disease trajectories. Second, existing literature indicates that HIV patients with optimal management exhibit COVID-19 clinical trajectories similar to those without HIV.[4] This aligns with our observations in the ART-experienced group, where a significant proportion had effectively controlled HIV, translating to milder COVID-19 manifestations. Beyond merely preserving immune functionality, certain ART drugs, particularly tenofovir, manifest symptom-mitigating effects on COVID-19 due to their ribonucleic acid polymerase inhibition and dampening of specific inflammatory pathways.[5] A considerable segment of our study participants received tenofovir-inclusive regimens. Amidst this pandemic backdrop, ART-naïve PLWH co-infected with SARS-CoV-2 warrant meticulous clinical investigation, and the expedited commencement of both antiviral therapies for COVID-19 and ART could be advantageous. Past research highlighted a correlation between diminished CD4+ T cell counts and protracted SARS-CoV-2 viral shedding durations in PLWH.[5] This study observed notably reduced CD4+ T cell counts in the ART-naïve cohort compared to their ART-experienced counterparts, potentially elucidating the prolonged viral shedding exhibited by the former group. Additionally, the mean viral shedding duration in non-HIV individuals stands at 16 days, mirroring that of the ART-experienced subset in our study, yet eclipsing that of the ART-naïve group. This further underscores the heightened COVID-19 severity in those without ART. This study is not without its constraints, namely its retrospective nature, potential recall inaccuracies during data compilation, and absent data, such as certain patient viral loads. Though the ART-naïve group exhibited an increased prevalence of opportunistic infections, specifics regarding the causative agents and infection locales were absent, introducing possible confounding factors like Pneumocystis jirovecii pneumonia.[6] Additionally, our study focused solely on inpatients, limiting its broader applicability. To conclude, our research delineates that ART-naïve PLWH contending with COVID-19 manifests more acute clinical symptoms and endures? extended viral shedding periods in comparison to ART-initiated PLWH. Consequently, immediate ART induction is advised upon HIV detection. Conflicts of interest None.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».