L’indice di resistenza renale può predire un aumentato rischio di danno renale acuto? Protocollo per una revisione sistematica

Pubblicato il Scarica PDF

Vincenzo Calabrese

DOI: 10.69097/42-02-2025-02

Giuseppe Cuttone1, Giulio Geraci2, La Via Luigi3, Sinatra Nicola4, Maria Rita Stancanelli5, Vincenzo Calabrese6
La revisione del protocollo è stata eseguita dal Dr. Alberto Rosati

1 School of Medicine and Surgery, “Kore” University, 94100 Enna, Italy
2 Unit of Internal Medicine, Department of Medicine and Surgery, University of Enna “Kore”, 94100, Enna, Italy
3 Department of Anesthesia and Intensive Care 1, University Hospital Policlinico "G. Rodolico - San Marco", 95123 Catania, Italy
4 Unit of Hemodialysis, Hospital “P.Paolo Borsellino” of Marsala (TP), 91025, Italy
5 Unit of Nephrology and Dialysis, Hospital “Umberto I” of Enna, Enna, 94100, Italy
6 Unit of Nephrology and Dialysis, Department of Medicine and Surgery, University of Enna “Kore”, 94100, Enna, Italy

Corrispondenza a:
Vincenzo Calabrese
E-mail: v.calabrese@outlook.it

 

Abstract

Introduzione. L’insufficienza renale acuta (IRA) è una grave complicanza nei pazienti in condizioni critiche associata a significativa morbilità e mortalità. L’individuazione precoce e la stratificazione del rischio rimangono oggetto di studio, soprattutto in condizioni complesse come lo shock settico, dove le alterazioni emodinamiche complicano il quadro clinico. L’Indice di Resistenza Renale (IRR), misurato tramite ecografia Doppler, sembrerebbe uno strumento non invasivo capace di valutare l’emodinamica renale e le alterazioni microcircolatorie. Sebbene vari studi abbiano indagato la relazione tra IRR e IRA, non c’è stata una valutazione sistematica completa dell’utilità dell’IRR nella previsione e nella valutazione dell’IRA in terapia intensiva.
Obiettivo. L’obiettivo principale è valutare la differenza nell’IRR tra i pazienti che hanno manifestato IRA e i pazienti che non hanno manifestato IRA. Inoltre, verrà calcolato il rischio di insorgenza di IRA correlato all’IRR.
Metodi. Eseguiremo una ricerca sistematica in PubMed e Scopus secondo le linee guida PRISMA. Selezioneremo studi osservazionali, con disegni sia retrospettivi che prospettici, su pazienti in condizioni critiche, senza restrizioni di sesso o età.
Risultati attesi. Questa revisione sistematica dovrebbe fornire una valutazione completa ed estesa della relazione tra IRR e IRA. La presente revisione sistematica sarà basata su studi osservazionali, essendo l’IRR un fattore di rischio non soggetto a controllo da parte dello sperimentatore. Inoltre, oltre a valutare l’associazione tra IRR ed IRA, lo studio si pone l’obbiettivo di evidenziate possibili lacune nelle conoscenze attuali, suggerendo nuove ricerche.
Conclusioni. Il presente protocollo di revisione sistematica includerà tutte le evidenze esistenti da articoli pubblicati che valutano i valori di IRR in pazienti che manifestano o meno IRA.

Parole chiave: danno renale acuto, indici di resistenza renale, revisione sistematica, terapia intensiva.

Ci spiace, ma questo articolo è disponibile soltanto in inglese.

Introduction

Renal resistive index (RRI) measurement has emerged as a valuable, non-invasive tool for assessing renal hemodynamic changes in various acute and chronic kidney conditions. It provides an ultrasound-based Doppler measure of renal artery resistance, which reflects intrarenal vascular impedance and indirectly indicates renal perfusion. In acute settings, particularly in patients with Acute Kidney Injury (AKI), the RRI can offer critical insights into renal microcirculatory dynamics and perfusion states [1–4]. In septic shock, a frequent precipitant of AKI, systemic and intrarenal hemodynamic alterations often complicate the clinical scenario, leading to high mortality and morbidity rates. Septic shock is characterized by profound vasodilation, increased capillary permeability, and impaired autoregulation of renal blood flow [5, 6]. These alterations often precipitate ischemic damage and oxidative stress, which are pivotal in the pathophysiology of sepsis-induced AKI. Given the challenges in early identification and management of AKI in septic shock, the RRI presents a potential marker for identifying hemodynamic compromise and risk stratification [7, 8].

This meta-analysis aims to synthesize existing data on the utility of the renal resistive index in acute kidney injury, with a focus on septic shock-induced AKI. By reviewing recent literature, we will evaluate the diagnostic accuracy and prognostic relevance of RRI in identifying renal injury severity, its potential to guide therapeutic interventions, and its role as a predictor of outcomes in acute septic settings.

 

Aims and scope

The main objective is to evaluate the difference in RRI between patients who manifested AKI and patients who did not manifest AKI. Furthermore, the risk of AKI occurrence related to RRI will be computed. Moreover, mortality, cardiovascular events, and combined outcomes will be highlighted.

 

Methods

Design and registration

This protocol is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA-P) guidelines [9], and will also be registered in the PROSPERO database.

Search strategy

We will perform systematic research in Pubmed and Scopus. Due to RRI being a risk factor, independent of researchers, observational studies will be included. We will also screen the reference list of the included studies. Age, sex, and admission reasons data retrieved into included studies will also be included in the analysis.

We will search for papers in the English language. References with different study designs will also be reviewed, to find additional potential eligible studies.  Search details are summarized in Table 1.

(cardiac failure OR liver failure OR acute respiratory distress syndrome OR ARDS OR sepsis OR septic shock) AND (acute kidney injury OR AKI) AND ((renal resistive index) OR (RRI) OR (renal) OR (resistive) OR (Index)) AND doppler)
Table 1. Search strategy PubMed and Scopus.

Eligibility criteria

PICO strategy, where Intervention and comparison correspond to AKI or no-AKI, will be applied.  Preliminary search showed studies reporting data spilt for AKI and no-AKI, for this reason, we chose to detail PICO as reported.

  • Population: we will evaluate the difference in RRI between AKI and no AKI, and the risk of AKI occurrence related to RRI will be computed.
    Eligible: Studies performed on critically ill patients, will be included, without sex or age restriction
    Exclusion criteria correspond to patients on dialysis, and patients with CKD.
  • Intervention: Acute kidney diseases
  • Comparator: not acute kidney diseases
  • Outcome: RRI
  • Study design: due to it being a comprehensive review of risk factors, observational studies can be considered as the highest level of evidence and will be included.

Literature screening and study selection

The summary will be shown using the PRISMA flow diagram [9]. Duplicate will be removed.

Studies will be screened first by title and abstracts by two independent pairs of authors (N.S. and G.C.) and any disagreement will be discussed with a third author (L.V.L). All abstracts will be screened using Rayyan software, whereas all full-text articles will be screened using the Mendeley software desktop.

Data extraction

Studies will be screened first by title and abstracts by two independent authors and any disagreement will be discussed with a third author with Rayyan software. Subsequently, the full texts of the selected studies will be read and assessed by two independent authors and any disagreement will be discussed with a third author. Reasons for the exclusion will be reported for each study. The selection process will be described through the PRISMA flow diagram.

The following data will be extracted through a standardized extraction Excel sheet by two independent authors:

1: general characteristics of the study (design, settings, sample size);

2: participant characteristics: inclusion and exclusion criteria, number of participants screened and included, average age, comorbidities, sex, area of recruitment;

3: intervention characteristics: duration of the follow-up

4: death or cardiovascular events.

Missing data will be obtained by contacting the included studies’ authors. We will send e-mails three times in three months.

Data items

Identification of the study: authors, article title, name of the journal, article DOI, publication year, short citation, and country will be detailed.

Methods: Study aims, study design, inclusion and exclusion criteria, intervention, comparator characteristics, population characteristics and results will be detailed.

For population, mean age, sex, and number of participants will be screened and reported. Results will describe summary statistics, effect estimates, confidence intervals, p-values, subgroup analyses, sensitivity analyses, risk of bias, and GRADE.

We plan to perform subgroup analyses based on age of patients enrolled (pediatric vs adult patients)

Main findings: This will include patient characteristics and other relevant clinical outcome measures.

Methodological quality assessment 

The method of assessing the risk of bias in this systematic review, as well as the study quality assessment and the data extraction, will be made screening first by title and abstracts by two independent pairs of authors and any disagreement will be discussed with a third author with Rayyan software.

The study selection, data extraction, and risk of bias assessment will be performed in blinded mode for the pairs of authors, to maintain the independence of the evaluation. The study authors or the journal of publication will be not hidden for the screening.

Strategy for data synthesis

Qualitative synthesis of the results based on risk of bias will be performed. If applicable, quantitative synthesis through a meta-analysis will follow. The risk of bias will be assessed independently by two authors, using the ROB 2.0 Tool for each outcome of interest. Any disagreement will be discussed with a third reviewer. RobVis visualization tool will be used to create the RoB graph.

Meta-analysis

The primary analysis will compute RRI differences between AKI and no-AKI. The secondary analysis proposes to compute the risk of AKI based on RRI values. All data will be analyzed with the fixed-effect model or random-effect model based on the heterogeneity of the studies.

Mean differences and 95% confidence interval (CI) will be calculated for continuous outcomes. For dummy outcomes, the Odds Ratio (OR), computing 95% confidence interval (CI), will be computed. Data were pooled using the fixed-effects model and also analyzed with the random-effects method to guarantee the strength of the model. We plan to test for heterogeneity using the χ² statistic related to freedom degrees, with a p-value of 0.05 used as the cut-off value to determine statistical significance. In addition, the degree of heterogeneity will be investigated by calculating the l² statistics. We will consider l² low if <25%, moderate if 25-50%, moderate-high if 50-75% and very high if >75%. In case of high heterogeneity, we will perform sensitivity analyses to explore sources of heterogeneity, such as study quality, year of publication, intervention or control variables, participants characteristics, and risk of bias. In addition, sub-group analyses will be conducted. We will use RevMan 5.4 software to perform the meta-analysis of all outcomes, and R4.4.0 software to perform the Network meta-analysis of all outcomes.

In addition, for the second analysis, standardized mean difference (SMD) will be computed using the formula “SMD = (RRI in AKI group – RRI in nonAKI group) / sqrt((standard deviation of RRI in AKI^2/sample size of AKI group) + (standard deviation of RRI in non-AKI^2/sample size of non-AKI group)”, when only RRI differences between AKI and non-AKI will be reported. SMD will be used as the dependent variable in a logical metaregression to compute the OR of AKI occurrence related to RRI values.

Subsample analysis will be performed based on admission cause, such as septic shock or hypovolemic causes or pulmonary diseases.

We will assess funnel plot asymmetry and the contour-enhanced funnel plot to explore Publication bias. GRADE System will be used to evaluate the certainty of the evidence and to summarize the study conclusions.

 

Ethics

Not applicable, because systematic reviews include only published data and does not require ethical approval. However, each study has to enrol patients after written consent and approval ethical code to be included in the metanalysis.

 

Status of the study and dissemination plan

We started the literature search, but not the screening process. We expect to complete the project and report it in 9 months. We will follow the updated PRISMA guideline to report the final paper and we will upload the progress on the PROSPERO website. Furthermore, we hope to publish a systematic review in a Nephrological journal.

 

Discussion

This systematic review protocol aims to comprehensively evaluate the relationship between renal resistive index (RRI) and acute kidney injury (AKI) in critically ill patients. The significance of this review lies in several key aspects.

First, early detection and risk stratification of AKI remain challenging in critical care settings, particularly in conditions like septic shock where hemodynamic alterations complicate the clinical picture. RRI, as a non-invasive ultrasound-based measurement, could potentially serve as a valuable tool for the early identification of patients at risk for AKI. Second, while various studies have examined the relationship between RRI and AKI, there has not been a comprehensive systematic review that specifically focuses on comparing RRI values between AKI and non-AKI patients while also analyzing the predictive value of RRI for AKI occurrence. Indeed, it is known that worsened vascular stiffness is a risk factor for kidney diseases, both acute and chronic [10]. By synthesizing available evidence, this review will help clarify the clinical utility of RRI measurements in critical care settings.

The observational design of the included studies is appropriate, as RRI is a risk factor that cannot be randomly assigned; this aspect does not affect the quality of the systematic review. This approach will allow for a more complete evaluation of the available evidence, though it may introduce certain methodological challenges in terms of controlling for confounding factors.

Potential limitations of this review may include heterogeneity in RRI measurement techniques across studies, variations in AKI definitions used, and differences in patient populations. The planned subgroup analyses and assessment of heterogeneity will help address these concerns and provide more nuanced insights into the relationship between RRI and AKI.

The findings from this systematic review will have important clinical implications for critical care practice, potentially supporting the use of RRI as a prognostic tool in AKI risk assessment and management. Additionally, identifying gaps in current knowledge will help guide future research directions in this field.

 

Conclusion

This systematic review protocol outlines a rigorous methodology to evaluate the relationship between renal resistive index and acute kidney injury in critically ill patients.  Summing up the RRI values between AKI and non-AKI patients, and analyzing the predictive value of RRI for AKI occurrence, this review will provide valuable insights into the utility of RRI as a diagnostic and prognostic tool. The findings will help clinicians better understand the role of RRI measurements in critical care settings and potentially inform evidence-based guidelines for AKI risk assessment and management. Furthermore, by identifying current knowledge gaps, this review will help direct future research efforts in this important area of critical care medicine. The results of this systematic review will be particularly relevant for intensivists, nephrologists, and other healthcare providers involved in the care of critically ill patients at risk for acute kidney injury.

 

Bibliography

  1. Tublin ME, Bude RO, Platt JF. The resistive index in renal Doppler sonography: where do we stand? AJR Am J Roentgenol. 2003;180(4):885-92. https://doi.org/10.2214/ajr.180.4.1800885.
  2. Granata A, Zanoli L, Clementi S, et al. Resistive intrarenal index: myth or reality? Br J Radiol. 2014;87(1038):20140004. https://doi.org/10.1259/bjr.20140004.
  3. Gomez H, Ince C, De Backer D, et al. A unified theory of sepsis-induced acute kidney injury: inflammation, microcirculatory dysfunction, bioenergetics, and the tubular cell adaptation to injury. Shock. 2014;41(1):3-11. https://doi.org/10.1097/shk.0000000000000052.
  4. Bellomo R, Kellum JA, Ronco C, et al. Acute kidney injury in sepsis. Intensive Care Med. 2017;43(6):816-28. https://doi.org/10.1007/s00134-017-4755-7.
  5. Ninet S, Schnell D, Dewitte A, et al. Doppler-based renal resistive index for prediction of renal dysfunction reversibility: A systematic review and meta-analysis. J Crit Care. 2015;30(3):629-35. https://doi.org/10.1016/j.jcrc.2015.02.008.
  6. Dewitte A, Coquin J, Meyssignac B, et al. Doppler resistive index to reflect regulation of renal vascular tone during sepsis and acute kidney injury. Crit Care. 2012;16(5):R165. https://doi.org/10.1186/cc11517.
  7. Schnell D, Darmon M. Renal Doppler to assess renal perfusion in the critically ill: a reappraisal. Intensive Care Med. 2012;38(11):1751-60. https://doi.org/10.1007/s00134-012-2692-z.
  8. Deruddre S, Cheisson G, Mazoit JX, et al. Renal arterial resistance in septic shock: effects of increasing mean arterial pressure with norepinephrine on the renal resistive index assessed with Doppler ultrasonography. Intensive Care Med. 2007;33(9):1557-62. https://doi.org/10.1007/s00134-007-0665-4.
  9. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4: 1. https://doi.org/10.1186/2046-4053-4-1.
  10. Calabrese V, Gembillo G, Longhitano E, La Placa C, Ferio C, Cernaro V, Santoro D. Timing of the CKD Complications: A Longitudinal Analysis. G Ital Nefrol. 2024 Dec 23;41(6):2024-vol6. https://doi.org/10.69097/41-06-2024-10. PMID: 39931968.