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BACKGROUND AND AIMS: Following antiretroviral therapy (ART) initiation, HIV-associated immune reconstitution inflammatory syndrome (IRIS), indicated by an array of opportunistic infections, may occur, presenting as either paradoxical, a worsening of a previously treated infection, or unmasking, a flare-up of an underlying, previously undiagnosed infection. The impact of ART as the backbone of HIV treatment and prevention has prolonged the survival of people living with HIV. In pregnancy, benefits have been shown by slowing HIV progression and preventing perinatal transmission; however, there have been risks of adverse reactions with ART, including immune responses to both the fetus and mother. This study sought to estimate the incidence of HIV-IRIS cumulatively and by type either paradoxical or unmasking IRIS, determine the baseline maternal and HIV clinical markers as predictors of, and analyze the log-rank test for survival time to IRIS outcome assessed by relying on an increase in CD4 count and/or a rapid decrease in viral load. METHODS: An active records study was conducted between June 2019 and March 2020 among ART-naïve pregnant women attending the antenatal care units (ANCu) at the Kenyatta National and Mbagathi Hospitals, Nairobi, Kenya. Participants were aged between 20 and 49 years and had a confirmed HIV-positive test. To ascertain a true case of IRIS, the diagnosis was adjudicated for accuracy and consistency by an independent review committee. Plasma HIV viral load, CD4 counts, and routine laboratory evaluations (hemoglobin, white blood cell count (WBC)) were performed by each hospital's clinical laboratory. The IRIS incidence was assessed using the International Network for Studies Against HIV-Associated IRIS (INSHI) during the first three months after ART initiation. Multivariate Cox regression with IRIS as the outcome, using the SPSSSurvival package, examined the relationship between baseline maternal characteristics and HIV clinical markers before ART initiation and IRIS, and finally, decision-tree analysis for predicting IRIS was performed. RESULTS: From a pool of 532 ART-naïve pregnant women, 133 (25%) developed IRIS, and 97 (72.9%) were in the unmasking category. The accumulated risk of experiencing IRIS symptoms increased from week two (hazard ratio (HR)=0.0287) to week 12 (HR=3.6158). Participants with a maternal BMI (MBMI) of 25-29.9 kg/m2 at baseline were at a higher risk of unmasking IRIS (HR=2.478; P=0.010). The WHO-HIV clinical stages 1 and 2 skewed towards paradoxical IRIS (regression coefficients =-0.111 and -0.276 (P<0.05)), while stage 4 skewed towards unmasking IRIS (regression coefficient=0.047, HR=1.048, P=0.941). A CD4 count > 500 cells/mm^3 skewed towards unmasking IRIS (regression coefficient=0.192, HR=1.211, P=0.416), while RNA-HIV viral loads >50 copies/ml towards paradoxical IRIS (regression coefficient=-0.199, HR=0.820, P=0.360. On decision tree analysis, 85% (P=0.001) of ART-naïve pregnant women with a baseline CD4 count below 500 copies/mm^3 presented with unmasking IRIS. CONCLUSION: For ART-naïve pregnant women, unmasking IRIS is the most common type, and an MBMI of 25-29.9 kg/m2, advanced HIV infection, a CD4 count <500 cells/mm^3, and a higher parity at baseline may be clinically useful predictors. The higher proportion of ART-naïve pregnant women experiencing unmasking as compared to paradoxical IRIS supports the need for earlier assessment based on potential predictors.
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The aim of this review was to evaluate the risk of COVID-19 cytokine release syndrome (CRS) with HIV infection and meta-regress for indicator covariates. Electronic databases, including Google Scholar, Cochrane Library, Web of Sciences (WOS), EMBASE, Medline/PubMed, COVID-19 Research Database, and Scopus, were systematically searched till February 30, 2022. All human studies were included, irrespective of publication date or region. Eleven studies, with a total of 2,005,274 detailing cytokine release syndrome defined by specific parameters, were included. To pool the estimate, a random-effects model with risk ratio (RR) as the effect measure was used. Moreover, publication bias and sensitivity analysis were evaluated followed by meta-regression analysis to account for any possible covariates. This systematic review, meta-analysis, and meta-regression trial was registered (CRD42021264761) on the PROSPERO register. HIV infection showed an increased risk for COVID-19 cytokine release syndrome (RR= 1.48, 95% CI (1.16, 1.88) (P=0.002)) with substantial heterogeneity (I2 > 80%) and a 4.6% cumulative incidence. The true effects size in 95% of all the comparable populations (prediction interval) fell between 0.67 to 3.29. HIV infection further showed an increased risk for intensive care unit (ICU) admission ((P<0.0001) (I² = 0%)] and mechanical ventilation (MV) ((P=0.04) (I² = 0%)) as the key indicators of cytokine release syndrome. Meta-regression analysis demonstrated that COVID-19 cytokine release syndrome was influenced by the year a study was published (R² = 0.55) and the region from where the study was conducted (R² = 0.11). On meta-regression analysis, the combined impact of all covariates in the model explained at least some of the variance in effect size (Q = 16.21, df = 6, P= 0.0127), and the proportion of variance explained by covariates on comparing the model with and without the covariates was 73 % and highly significant (Tau² = 0.1100, Tau = 0.3317, I² = 86.5%, Q = .99, df = 10, P<0.0001) (R² = 0.73). Our updated meta-analysis indicated that HIV infection was significantly associated with an increased risk for COVID-19 cytokine release syndrome, which, in addition, might be moderated by the year a study was published and the region in which the study was conducted. Further, the risk for intensive care unit (ICU) admission and mechanical ventilation (MV) were identified as the key indicators of cytokine release syndrome. We believe the updated data anchoring cytokine release syndrome will contribute to more substantiation of the findings reported by similar earlier studies.
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BACKGROUND: COVID-19 was first identified in Wuhan, China, in December 2019, spreading to the rest of the globe, becoming a pandemic. Some studies have shown an association between pregnancy status and severe COVID-19 with a cytokine storm, whereas others have shown contrasting results. OBJECTIVE: The aim of this study was to examine the relationship between pregnancy status and the clinical COVID-19 severity characterized by the cytokine storm through a systematic review and meta-analysis. METHODS: We searched the Google Scholar, PubMed, Scopus, Web of Science, and Embase databases to identify clinical studies suitable for inclusion in this meta-analysis. Studies reporting pregnancy status and comparing the COVID-19 severity cytokine storm outcome were included. COVID-19 severity characterized by a cytokine storm was described using parameters such as intensive care unit admission, invasive mechanical ventilation, mechanical ventilation, hospital admission, pro- and anti-inflammatory cytokine levels, consolidation on chest computed tomography scan, pulmonary infiltration, extreme fevers as characteristic of a cytokine storm, syndromic severity, higher neutrophil count indicative of a cytokine storm, and severe COVID-19 presentation. RESULTS: A total of 17 articles including data for 840,332 women with COVID-19 were included. This meta-analysis revealed a correlation between positive pregnancy status and severe COVID-19 with a cytokine storm (random-effects model odds ratio [OR] 2.47, 95% CI 1.63-3.73; P<.001), with a cumulative incidence of 6432 (14.1%) and 24,352 (3.1%) among pregnant and nonpregnant women with COVID-19, respectively. The fixed-effects model also showed a correlation between pregnancy status and severe COVID-19 with a cytokine storm (OR 7.41, 95% CI 7.02-7.83; P<.001). Considerable heterogeneity was found among all pooled studies (I²=98%, P<.001). Furthermore, the updated analysis showed substantially low heterogeneity (I²=29 %, P=.19), and the funnel plot revealed no publication bias. The subanalysis between single-center and multicenter studies demonstrated similar heterogeneity (I2=72% and 98%, respectively). Sensitivity analysis on each subgroup revealed that pregnancy was significantly related to severe COVID-19 with a cytokine storm from single-center studies (fixed-effects model OR 3.97, 95% CI 2.26-6.95; P<.001) with very low heterogeneity (I²=2%, P=.42). CONCLUSIONS: Being pregnant is clearly associated with experiencing a severe course of COVID-19 characterized by a cytokine storm. The COVID-19 pandemic should serve as an impetus for further research on pregnant women diagnosed with COVID-19 to map out the salient risk factors associated with its severity. TRIAL REGISTRATION: PROSPERO CRD42021242011; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=242011.