Prognostic value of renal resistive index for predicting renal recovery in critically ill patients with acute kidney injury

Abstract

Background:

Renal recovery after acute kidney injury is a clinical outcome that influences prognosis in critically ill patients. The renal resistive index was measured by Doppler ultrasound and has been proposed as a potential predictor of renal recovery; however, its prognostic value remains inconsistent.

Methods:

This prospective study included acute kidney injury patients admitted to the intensive care unit at Cho Ray Hospital from November 2021 to July 2022. Renal resistive index was measured by Doppler ultrasound at intensive care unit admission, after 24 hours, and after 48 hours. Renal recovery was assessed on days 2 and 7 and at hospital discharge.

Results:

Among 95 patients with acute kidney injury, renal recovery occurred in 16.8% at day 2, 37.9% at day 7, and 47.4% at hospital discharge. Renal resistive index measured at day 2 (renal resistive index 2) was significantly higher in the non-recovery group than in the recovery group (0.755 ± 0.071 vs. 0.692 ± 0.091; p = 0.001). Both renal resistive index 2 and its percentage change (% renal resistive index 2) demonstrated moderate discriminative ability for predicting renal recovery at day 7. In multivariable analysis, acute kidney injury stage 3, cumulative fluid balance >5%, renal resistive index 2 >0.722, and a reduction in percentage renal resistive index 2 <5% were independently associated with impaired renal recovery at day 7.

Conclusion:

Renal resistive index on day 2 and its dynamic changes were associated with renal recovery in critically ill patients with acute kidney injury. Repeated renal resistive index assessment may provide complementary prognostic information when integrated with clinical factors. Further multicentre studies are needed to validate its clinical utility and to combine the renal resistive index with clinical and biochemical parameters.

Keywords

acute kidney injury Doppler ultrasound renal resistive index renal recovery

Introduction

Acute kidney injury (AKI) is a common organ dysfunction affecting 30%–57% of intensive care unit (ICU) patients and is associated with high mortality.¹ Following each episode of AKI, the balance between adaptive and maladaptive repair plays a crucial role in renal recovery; however, the underlying mechanisms remain unclear.² The extent and timing of renal recovery from AKI may significantly influence short- and long-term outcomes.^3,4 Kellum et al.⁴ demonstrated that in critically ill patients with AKI stage 2 or 3 (KDIGO), the mortality rates for early sustained reversal, late sustained reversal, and non-recovery AKI were 10%, 25%, and 60%, respectively.

Doppler-based renal resistive index (RRI) measurement is a non-invasive, repeatable tool that reflects changes in renal vascular distensibility and resistance. RRI is a dynamic parameter that reflects renal vascular characteristics, enabling the evaluation of preclinical renal dysfunction and renal vascular injury.^5
–7 Previous studies have suggested that RRI may predict the development of AKI and its short-term reversibility.⁸ Although renal recovery after AKI is strongly associated with short- and long-term outcomes in critically ill patients, early identification of patients at risk of non-recovery remains challenging. Conventional markers such as serum creatinine and urine output may be delayed or influenced by fluid balance, renal replacement therapy, and changes in muscle mass. However, previous studies have reported inconsistent findings regarding the prognostic value of RRI for renal recovery, and limited data are available on whether dynamic changes in RRI during the early ICU course provide additional predictive information. Several barriers have limited progress in this field, including heterogeneous definitions of renal recovery, variability in RRI measurement timing, restriction to specific patient populations, operator-dependent Doppler techniques, and confounding by haemodynamic variables such as vasopressor therapy, fluid balance, cardiac output, and intra-abdominal pressure.

Therefore, this study aimed to determine the incidence of renal recovery among critically ill patients with AKI and to evaluate whether serial RRI measurements and their early percentage changes could predict renal recovery.

Methods

Study design

This study was a prospective observational study of AKI patients in a medical-surgical ICU at Cho Ray Hospital, Vietnam, from November 2021 to July 2022.

Patient selection

We included adult patients aged 18 years or older who were diagnosed with AKI according to KDIGO 2018 criteria at the time of admission to the ICU. The exclusion criteria involved cardiac arrhythmia, moderate to severe aortic valve stenosis, any severe valvular heart disease, pre-existing renal artery stenosis, post-renal obstruction, chronic kidney disease (CKD) with a glomerular filtration rate (GFR) less than 30 mL/min/1.73 m², or a history of kidney transplantation, pregnancy, or a patient with a hospital stay <72 hours.

Ultrasound RRI measurements

RRI was measured by a trained intensivist using a Siemens Acuson 3 ultrasound machine with a 4-MHz convex-array probe. Both kidneys were initially evaluated using B-mode and color Doppler ultrasound to exclude chronic structural abnormalities, urinary obstruction, and suspected renal vascular abnormalities, such as renal artery stenosis or accessory renal arteries, before resistive index (RI) measurement. The right kidney was preferentially selected because it is generally more accessible for ultrasound examination in critically ill patients and allows a more reliable acoustic window through the liver.⁹ RI was measured from interlobar or arcuate arteries using pulse-wave Doppler. An optimal Doppler spectrum was visualised in at least three similar consecutive waveforms (the left kidney was used if the right was not obtainable). Pulsed-wave Doppler was used with the sample volume placed in the arterial lumen; at least three uniform arterial waveforms were obtained, and the peak systolic velocity (V_max) and the minimal diastolic velocity (V_min) were recorded, and the RI was calculated with the following formula: (V_max–V_min)/V_max. Three measurements were averaged to obtain the mean RI values used for the study.⁹ Ultrasound assessments were performed at ICU admission, categorised as R0 (first 24 hours), R1 (24–48 hours), and R2 (48–72 hours). For each patient, we also calculated the percentage change in RRI from baseline at days 1 and 2: %RRI x = (RRI at day x—RRI0)/ RRI0, where x = 1 or 2, as illustrated in Figure 1.

Data collection

We collected patient demographics (age, sex, body mass index), comorbidities, the reason for admission, and the severity score using the Acute Physiology and Chronic Health Evaluation II (APACHE II) score and the Sequential Organ Failure Assessment (SOFA) score at ICU admission.

Patient clinical and laboratory parameters were recorded at ICU admission and again at 24 and 48 hours, concurrent with RRI measurements. These included vital signs (heart rate, blood pressure), serum creatinine, serum urea, hematocrit, and urine output. We recorded the use of vasopressor support and quantified vasoactive intensity using a norepinephrine-equivalent (NEE) dose. The NEE was calculated to account for various vasopressors as follows: NEE (µg/kg/min): Norepinephrine dose (µg/kg/min) + epinephrine dose (µg/kg/min) + 1/150 × dopamine dose (µg/kg/min) + 1/10 × phenylephrine dose (µg/kg/min) + 2.5 × vasopressin dose (U/min). Exposure to nephrotoxic agents (such as vancomycin, aminoglycosides, polymyxins, amphotericin B, or iodinated contrast) before ICU admission and within the first week of ICU stay was recorded. AKI was classified according to the Kidney Disease: Improving Global Outcomes (KDIGO) 2012.¹⁰ For each patient, baseline sCr was defined according to the sCr measured 3 months before hospital admission. When the baseline sCr level was unknown, this variable was estimated using the Modification of Diet in Renal Disease (MDRD) formula’s back-calculation method.¹⁰ Renal recovery was defined as the absence of AKI criteria for at least 24 hours or a downgrade to stage 1 AKI (if initially classified at a higher stage), as per the KDIGO 2012 guidelines, and independence from renal replacement therapy (RRT).⁴ Independence from RRT was defined as the discontinuation of dialysis for at least 7 days after the last RRT session.¹¹ Cumulative fluid balance was calculated as follows:¹² CFB (%) = (cumulative fluid input–output within the first 72 hours of ICU stay) in liters × 100 / Hospital admission weight (kg).

Outcomes

The primary outcome was renal recovery by day 7 of ICU admission. Secondary outcomes included renal recovery by 48 hours and at hospital discharge, need for RRT, and survival to hospital discharge.

Statistical analysis

Data were analysed using SPSS version 26.0. Continuous variables are presented as mean ± standard deviation (SD) if normally distributed or median (interquartile range (IQR)) if non-normally distributed. Categorical variables are presented as counts and percentages. We compared patient characteristics and outcomes between groups (recovery vs. non-recovery) using appropriate tests: the Student’s t-test for normally distributed continuous data, the Mann–Whitney U test for non-normal data, and the chi-square or Fisher’s exact test for categorical data. Repeated measures were analysed using analysis of variance (ANOVA) or appropriate non-parametric equivalents. Correlations were assessed using Spearman’s rank test. The predictive value of RRI for renal recovery was evaluated using receiver operating characteristic (ROC) curves for RRI at R1, R2, and %RRI, with a focus on recovery by day 7, as defined by the AKI criteria. Area under the curve (AUC) with 95% confidence intervals was calculated. Optimal cutoff values were determined using Youden’s index, and corresponding sensitivity, specificity, positive predictive value, and negative predictive value were reported. Independent predictors of day-7 recovery were identified using multivariable logistic regression, including variables with p < 0.10 in univariate analysis or deemed clinically relevant (e.g., age, AKI stage, fluid balance, and RRI metrics). Age ⩾60 years was included, given its association with nephrosclerosis and elevated RRI. Results are presented as odds ratios (ORs) with 95% CIs. Kaplan–Meier analysis was used to compare survival across recovery patterns, with log-rank testing for significance. A two-tailed p < 0.05 was considered statistically significant.

Ethical approval

The study protocol was approved by the Ethics Committee in Biomedical Research of the University of Medicine and Pharmacy at Ho Chi Minh City (Number 522/HĐĐĐ -ĐHYD), which approved this study on November 9, 2021. All study procedures complied with the institutional and national ethical standards and the 1964 Helsinki Declaration and its amendments.

Results

Characteristics of the patients

A total of 95 patients diagnosed with AKI were eligible for the study, admitted to the ICU from November 2021 to July 2022. The mean age was 50.5 ± 16.1 years, and 60% male. Baseline characteristics of the study population stratified by renal recovery status at day 7 are summarised in Table 1.

Table 1.

Baseline characteristics of the patients and comparison of acute kidney injury recovery at day 7.

Variables	All (n = 95)	Non-recovery (n = 59)	Recovery (n = 36)	p
Age (years), mean ± SD	50.5 ± 16.1	50.7 ± 16.9	50.2 ± 14.9	0.87
Male sex, n (%)	57 (60)	36 (37,9)	21 (22,1)	0.79
BMI, median (IQR)	22.9 [20.7–25.0]	22.8 [20.0–24.2]	23.1 [20.8–25.0]	0.82
Comorbidities, n (%)
Chronic heart failure, n (%)	3 (3.2)	2 (3.4)	1 (2.8)	0.87
Hypertension, n (%)	19 (20)	12 (20.3)	7 (19.4)	0.92
Diabetes mellitus, n (%)	24 (25.3)	15 (25.4)	9 (25.0)	0.80
Chronic kidney disease, n (%)	2 (2.1)	1 (1.7)	1 (2.8)	0.72
Liver cirrhosis, n (%)	2 (2.1)	1 (1.7)	1 (2.8)	0.72
Severe score
APACHE II, median (IQR)	30 (12; 35)	30 (12; 35)	30 (12; 35)	0.21
SOFA, median (IQR)	11 (9; 15)	12 (8.5; 15)	11 (9; 13)	0.29
Sepsis or septic shock, n (%)	58 (61)	33 (55.9)	25 (69.4)	0.26
Vasoactive drugs, n (%)	55 (57.9)	32 (54.2)	23 (63.9)	0.36
NEE >0.5 µg/kg/min, n (%)	18 (19.0)	9 (9.5)	9 (9.5)	0.24
Serum lactate (mmol/L), median (IQR)	2.6 [1.8–4.9]	2.8 [1.6–5.0]	2.8 [2.0–4.6]	0.67
Creatinine (mg/dL), median (IQR)	2.3 [1.6–3.8]	2.11 [1.3–3.3]	2.8 [1.7–3.9]	0.16
AKI stage 1, n (%)	35 (36.8)	20 (33.9)	15 (41.7)	0.08
AKI stage 2, n (%)	20 (21.1)	10 (16.9)	10 (27.8)
AKI stage 3, n (%)	40 (42.1)	29 (49.2)	11 (30.5)
RRT within first 12 hours, n (%)	30 (42.9)	11 (15.7)	2.29 (0.65; 8.09)	0.19
CFB >5%, n (%)	26 (27.4)	21 (22.1)	5 (5.3)	0.04
Exposure to nephrotoxic drugs before ICU admission, n (%)	52 (54.7)	32 (54.2)	20 (38.5)	0.90
Exposure to nephrotoxic drugs within the first week, n (%)	35 (36.8)	26 (27.4)	9 (9.5)	0.07
Mechanical ventilation, n (%)	80 (84.2)	50 (84.7)	30 (83.3)	0.86

AKI, acute kidney injury; APACHE, Acute Physiologic Assessment and Chronic Health Evaluation; BMI, body mass index; CFB, cumulative fluid balance; NEE, norepinephrine equivalent; ICU, intensive care unit; RRT, renal replacement therapy; SOFA, Sequential Organ Failure Assessment.

Regarding renal characteristics, the most common AKI stage was stage 3 (42.1%), followed by stage 1 (36.8%) and stage 2 (21.1%). Seventy patients (73.7%) received RRT. Nephrotoxic drugs were administered to 52 (54.7%) patients before ICU admission and 35 (36.8%) patients within the first week after admission (Table 1). The incidence of renal recovery at day 7 and hospital discharge was 37.9% and 47.4%, respectively. Among patients who recovered renal function during the first week, 16/95 (16.8%) recovered within the first 2 days, while 20/95 (21.1%) recovered beyond 48 hours (Figure 2). There were no differences between the recovery and non-recovery groups, including age, sex, body mass index, comorbidities, NEE, serum lactate, or exposure to nephrotoxic agents within the first week. However, a CFB greater than 5% was significantly greater in the non-recovery group than in the recovery group (22.1% vs. 5.3%, p = 0.04). The progression of renal recovery status from day 2 to hospital discharge is shown in Figure 2.

Renal Doppler ultrasound measurements and changes in RRI are presented in Table 2. The RRI2 was higher in the non-recovery group compared with the recovery group (0.755 ± 0.071 vs. 0.692 ± 0.091, p = 0.001). Moreover, patients in the renal non-recovery group showed a positive median %RRI2 value, indicating persistently elevated or increasing RRI over the first 48 hours, whereas the recovery group demonstrated a reduction in RRI from baseline (2.3 vs. −6.1, p = 0.002). Although RRI2 and %RRI2 did not predict renal recovery at hospital discharge, both showed recovery by day 7, with AUCs of 0.702 and 0.704, respectively. A cutoff value of 0.722 for RRI2 showed a sensitivity of 63.9% and specificity of 72.4%, while a ⩾5.4% reduction in %RRI2 achieved a specificity of 82.7%. The AUC (95% confidence interval (CI)) for predicting renal recovery at day 7 was 0.702 (0.589–0.816) for RRI2 and 0.704 (0.586–0.821) for %RRI2 (Figure 3). Based on the ROC curve, a cutoff of RRI2 >0.722 and a 5.4% reduction in %RRI2 were associated with impaired renal recovery, as shown in Supplemental Appendix Tables S1 and S2. Univariable and multivariable logistic regression analyses for predictors of renal recovery at day 7 are shown in Table 3.

Table 2.

Performance of Doppler-derived renal resistive index (RRI) and percentage change in RRI (%RRI) for predicting renal recovery at day 7.

Variables	Non-recovery (n = 59)	Recovery (n = 36)	p
RRI 0	0.744 ± 0.081	0.736 ± 0.065	0.69
RRI1	0.732 ± 0.082	0.706 ± 0.078	0.14
RRI2	0.755 ± 0.071	0.692 ± 0.091	0.001
%RRI1	−2.1 [−10.1 to 3.2]	−1.3 [−10.7 to 1.3]	0.88
%RRI2	2.3 [−5.8 to 10.4]	−6.1 [−14.0 to 1.8]	0.002
RRI2 >0.722	43 (45.3)	13 (13.7)	0.001
%RRI2 <5%	47 (49.5)	13 (13.7)	0.001

RRI, Renal resistive index; RRI0, RRI at baseline; RRI1, RRI at 24 hours; RRI2, RRI at 48 hours; %RRI1, percentage change in RRI from RRI0 to RRI1; %RRI2, percentage change in RRI from RRI0 to RRI2.

Table 3.

Factors predicting renal recovery at day 7.

Variable	Model 1 OR (95% CI)	p	Model 2 OR (95% CI)	p
Age ⩾60 years	0.73 (0.24–2.17)	0.57	0.69 (0.23–2.08)	0.52
Exposure to nephrotoxic agents within the first week	0.42 (0.15–1.21)	0.11	0.36 (0.12–1.06)	0.06
AKI Stage 3	0.36 (0.13–0.99)	0.04	0.33 (0.11–0.95)	0.04
CFB >5%	0.23 (0.07–0.79)	0.02	0.26 (0.08–0.95)	0.04
RRI 2 >0.722	0.31 (0.11–0.83)	0.02	–	–
Reduction in RRI 2 <5%	–	–	0.19 (0.07–0.52)	0.001

AKI, acute kidney injury; CFB, cumulative fluid balance; RRI, renal resistive index; RRI2, renal resistive index at 48 hours; OR, odds ratio; CI, confidence interval.

In addition, the patients in the non-recovery group had longer ICU stay, hospital stay, duration of mechanical ventilation, and RRT days compared with the recovery group (Figure 4)

Discussion

This cohort study suggests that Doppler-derived RRI can discriminate renal recovery in the critical care setting. In this study of 95 AKI patients admitted to the ICU, the renal recovery occurred in 37.9% of patients within the first week and in 47.4% at hospital discharge. Using RRI2 to predict recovery by day 7 demonstrated moderate discriminative performance, with an AUC of 0.702 (95% CI = 0.589–0.816). Notably, our study also examined dynamic RRI trends, in which a <5% fall in %RRI2 from baseline was independently associated with non-recovery by day 7, suggesting that serial RRI measurements may carry additional prognostic information beyond a single time-point assessment. The literature shows that half of ICU patients who survive AKI eventually recover significant function, while non-recovery is associated with increased mortality. Kellum et al.⁴ found that among severe AKI (KDIGO 2–3) patients, early sustained renal reversal was associated with a 10% mortality versus 60% in non-recovered patients. These findings underscore the importance of early prediction, as non-recovery carries a poor prognosis.

The incidence of renal recovery in our study is comparable to previous reports of AKI reversal in critically ill populations, despite the definitions of recovery varying in studies. However, the predictive performance of RRI remains inconsistent. Schnell et al.¹³ found that a high RRI at ICU admission predicted AKI stages 2–3, with an RRI cutoff of 0.74 (AUC = 0.72) for progression to AKI, 53% sensitivity, and 87% specificity. In addition, Garnier et al.¹⁴ showed that RRI measured within 12 hours had excellent predictive value for persistent AKI (AUC = 0.93), with a cutoff ⩾0.685, 78% sensitivity, and 90% specificity. In contrast, Fu et al.¹⁵ observed only modest discriminative power in septic shock patients (AUC = 0.699), and RRI did not improve clinical prediction models. Both RRI2 and %RRI2 demonstrated moderate discriminative performance for predicting renal recovery at day 7, suggesting that RRI may provide complementary prognostic information when integrated with clinical and biochemical parameters rather than serving as a standalone predictor. Variations in reported RRI values across studies may be attributed to differences in recovery definitions, timing of renal function assessment, patient characteristics, and the specific time points at which RRI was measured. Garnier et al.¹⁴ evaluated renal recovery at day 3, whereas our study assessed outcomes at day 7 and at hospital discharge. Furthermore, most studies have proposed RRI cutoffs of 0.67–0.80 to predict AKI outcomes.

A time-dependent evaluation of RRI trends was a novel feature of our study. The study observed that patients whose RRI2 decreased (or did not increase) during the first 2 days were more likely to recover by day 7. This suggests that repeated Doppler measurements may enhance risk stratification better than a single RRI value. To our knowledge, few prior studies have reported on dynamic changes in RRI. Conceptually, a declining RRI during the first days of ICU care may reflect improving renal perfusion, whereas persistently elevated or increasing RRI values may suggest ongoing renal dysfunction or kidney injury.^16,17 Moreover, our findings showed that a ⩾5.4% reduction in %RRI2 at 48 hours showed a sensitivity of 63.9% and specificity of 82.7% for predicting renal recovery. Although diastolic blood pressure on day 2 was higher than on day 0, and vasopressor dosage was greater at day 0 compared with day 2, there were no significant differences in heart rate, diastolic blood pressure, pulse pressure, or vasopressor requirements between the recovery and non-recovery groups at either time point (Supplemental Table S3). These findings suggest that changes in %RRI2 over time provide better specificity for predicting renal recovery than a single RRI2 value measured at day 2. Trend monitoring of RRI may provide complementary prognostic information regarding renal recovery when interpreted together with the overall clinical context.

Notably, our study found that AKI severity and CFB >5% on day 3 were associated with a reduced likelihood of renal recovery. These support the concept that renal recovery is determined not only by the extent of initial kidney injury but also by disturbances in microcirculation and early fluid management strategies. AKI severity represents a prognostic factor for kidney disease progression.^18,19 Mizuguchi et al.²⁰ reported 10,000 patients undergoing cardiac surgery with a graded increase in the risk of acute kidney disease across AKI stages, with relative risks of 2.31, 9.36, and 22.9 for stages 1, 2, and 3, respectively, independent of baseline renal function, underscoring the pivotal role of initial kidney injury severity. Furthermore, CFB also plays a critical role in AKI prognosis. Zhang et al.²¹ demonstrated that fluid overload was significantly associated with increased mortality in patients with AKI (OR = 2.23; 95% CI = 1.66–3.01), but it was not associated with renal recovery (OR = 0.66; 95% CI = 0.37–1.15). This discrepancy highlights the complex nature of renal recovery and the indirect systemic effects of fluid overload beyond the kidney. It may also reflect heterogeneity in outcome definitions, assessment timing, and patient populations, whereas prior studies have predominantly focused on mortality as the primary endpoint.

Our findings suggest that RRI may provide complementary prognostic information regarding renal recovery when interpreted together with clinical and biochemical parameters. An RRI <0.72 on day 2 with a downward trend implies a reasonably high chance (NPV: 76%) of renal recovery, whereas a higher or rising RRI warns of persistent injury. Importantly, RRI should not be interpreted as a kidney-specific biomarker but rather as an integrated hemodynamic signal influenced by both systemic and renal factors. RRI is affected not only by intrarenal vascular resistance but also by arterial stiffness, pulse pressure, vasopressor therapy, intra-abdominal pressure, and venous congestion. Thus, an elevated RRI may reflect systemic circulatory dysfunction rather than isolated renal injury, which may partly explain its limited predictive performance. Accordingly, RRI should be considered a dynamic hemodynamic marker that complements, rather than replaces, traditional clinical and biochemical predictors of renal recovery. The future, large, multicenter studies should validate RRI thresholds and explore combined prognostic models.

Strengths of our study include its prospective design and repeated RRI measurements by experienced operators in a critical care setting. The prior studies were limited to cardiac surgery or sepsis patients. However, the study has several limitations. First, the sample size and single-center design are limiting the precision of the estimates. Second, although we collected data on heart rate, mean arterial pressure, fluid status, and norepinephrine-equivalent dosage, RRI itself may be influenced by these hemodynamic parameters, which can affect Doppler waveforms. In addition, RRI was measured in only the right kidney; bilateral or multi-vessel assessments might yield different results. Finally, our study used a fixed time point of day 2 for RRI, whereas some studies suggest that earlier measurements within 12–24 hours may better predict reversibility.¹⁴ These issues could explain why our RRI predictive accuracy was lower than that reported in some prior studies.

Conclusion

RRI on day 2 and its dynamic changes were associated with renal recovery in critically ill patients with AKI. Repeated RRI assessment may provide complementary prognostic information when integrated with clinical and biochemical parameters. Further multicentre studies are needed to validate its clinical utility and to explore integrated prediction models combining RRI with clinical and biochemical parameters.

Supplemental Material

sj-docx-1-ult-10.1177_1742271X261456503 – Supplemental material for Prognostic value of renal resistive index for predicting renal recovery in critically ill patients with acute kidney injury

Supplemental material, sj-docx-1-ult-10.1177_1742271X261456503 for Prognostic value of renal resistive index for predicting renal recovery in critically ill patients with acute kidney injury by Yen Hai Le, Dai Quang Huynh, Ngan Hoang Kim Trieu, Bien Huu Thien Le, Linh Thanh Tran and Thao Thi Ngoc Pham in Ultrasound

Footnotes

ORCID iDs

Ngan Hoang Kim Trieu

Bien Huu Thien Le

Thao Thi Ngoc Pham

Ethical considerations

The Institutional Review Board approved this study on November 9, 2021, after the Ethics Committee in Biomedical Research of the University of Medicine and Pharmacy at Ho Chi Minh City (Number 522/HĐĐĐ-ĐHYD) granted it. All study procedures complied with the institutional and national ethical standards and the 1964 Helsinki Declaration and its amendments.

Consent for publication

Written informed consent was obtained from all participants or their legally authorized representatives.

Author contributions

Yen Hai Le: Conceptualization, data curation, methodology, and writing—original draft. Dai Quang Huynh: Writing—original draft and editing the manuscript. Ngan Hoang Kim Trieu: Data curation and editing the manuscript. Bien Huu Thien Le: Conceptualization, data curation, methodology, and editing the manuscript. Linh Thanh Tran: Data curation and editing the manuscript. Thao Thi Ngoc Pham: Methodology and editing the manuscript. All authors read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

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

Data availability statement

The data presented in this study are available from the corresponding author on reasonable request.

Guarantor

Yen Hai Le.

Informed consent to participate

All participants provided written informed consent or their legally authorized representatives.

Supplemental material

Supplemental material for this article is available online.

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