Comparison between Analgesia Nociception Index (ANI) and self-reported measures for diagnosing pain in conscious individuals: a systematic review and meta-analysis

Baroni, Daniela; Abreu, Lucas Guimarães; Paiva, Saul Martins; Costa, Luciane Rezende

doi:10.1038/s41598-022-06993-z

Cited by 9 publications

(3 citation statements)

References 57 publications

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“…In addition, some studies have reported that ANI values in patients differ when under general anesthesia and when in a conscious state [ 56 ]; thus, ANI in an awake state is difficult to interpret [ 57 ]. Baroni et al performed a meta-analysis of nine studies that assessed ANI and self-reported measures in conscious patients [ 58 ]. They found a weak negative correlation between ANI and NRS in the post-anesthetic recovery room ( r = −0.0984; 95% CI −0.397 to 0.220, I 2 = 95.82%).…”

Section: Limitations Of Animentioning

confidence: 99%

Analgesia nociception index and high frequency variability index: promising indicators of relative parasympathetic tone

2022

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At present, there is no objective and absolute measure of nociception, although various monitoring techniques have been developed. One such technique is the Analgesia Nociception Index (ANI), which is calculated from heart rate variability that reflects the relative parasympathetic tone. ANI is expressed on a non-unit scale of 0–100 (100 indicates maximal relative parasympathetic tone). Several studies indicated that ANI-guided anesthesia may help reduce intraoperative opioid use. The usefulness of ANI in the intensive care unit (ICU) and during surgery has also been reported. However, some limitations of ANI have also been reported; for example, ANI is affected by emotions and some drugs. In 2022, a high frequency variability index (HFVI), which was renamed from ANI and uses the same algorithm as ANI, was commercialized; therefore, ANI/HFVI are currently in the spotlight. Unlike ANI, HFVI can be displayed along with other biometric information on the Root ® monitor. ANI/HFVI monitoring may affect the prognosis of not only patients in the perioperative period but those in ICU, those who receive home medical care, or outpatients. In this article, we present an updated review on ANI that has been published in the last decade, introduce HFVI, and discuss the outlooks of ANI/HFVI.

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Section: Limitations Of Animentioning

confidence: 99%

Analgesia nociception index and high frequency variability index: promising indicators of relative parasympathetic tone

2022

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“…The overarching objectives of incorporating ANI are to mitigate pain experiences, curtail the consumption of opioids, and consequently diminish the incidence of opioid-related adverse outcomes [12,13]. Despite its proven efficacy in sedated patients, the applicability and effectiveness of ANI in conscious patients remain an area shrouded in ambiguity, necessitating more exhaustive research endeavors [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

The Relationship between Pre-Anesthetic Analgesia and Nociception (ANI) and Propofol Injection Pain among Patients Receiving Remifentanil: A Prospective, Randomized, Controlled Study

Lee,

Lim

et al. 2024

Medicina

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Background and Objectives: The analgesia/nociception index (ANI) potentially monitors nociceptive status during anesthesia, but its link to preoperative pain sensitivity is unclear. We investigated the relationship between pre-anesthetic ANI scores and propofol injection pain (PIP) in patients receiving remifentanil. Materials and Methods: This study included 124 male patients aged 19–60 undergoing general anesthesia (ASA class I or II). Patients were randomized to group R (n = 62, remifentanil 4 ng/mL) or group C (n = 62, saline). The primary outcome was the association between PIP and ANI. Secondary outcomes included the incidence and severity of PIP or rocuronium-induced withdrawal movement (RIWM) and their association with ANI. Results: PIP and RIWM incidence and severity were lower in group R than in group C. A weak negative correlation between PIP and ANI at pre-induction (rpb = −0.21, p = 0.02, rpb = −0.37, p < 0.01) and a moderate negative correlation during propofol injection (rpb = −0.48, p = 0.02) were observed. A significant negative correlation was found between RIWM and ANI during rocuronium injection (τb = −0.61, p < 0.01). AUC, cut-off value, specificity, and sensitivity in ANI at pre-induction for predicting PIP were 0.67 (p = 0.02), 59, 76%, and 55%, respectively. AUC, cut-off value, specificity, and sensitivity in ANI during propofol injection for PIP were 0.77 (p < 0.01), 65, 81%, and 67%, respectively. Conclusions: ANI scores demonstrated significant differences between groups, suggesting potential predictive value for PIP despite the low pre-induction AUC value. This study highlights the potential of using ANI scores to predict and manage PIP in patients receiving remifentanil.

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“…Both classical and recent experiments show that patients with decreased HRV significantly increased the risk for poor clinical outcomes, including death with or without congestive heart failure [ 13 – 15 , 17 , 18 ]. Meta-analysis investments are also implemented to further explain the relationship between HRV and diagnosis [ 19 ]. Therefore, HRV has shown a promising result as a predicting marker for cardiovascular-related disorders.…”

Section: Introductionmentioning

confidence: 99%

The prognostic value of intraoperative HRV during anesthesia in patients presenting for non-cardiac surgery

Niu

et al. 2023

BMC Anesthesiol

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Objective To examine the prognostic value of HRV measurements during anesthesia for postoperative clinical outcomes prediction using machine learning models. Data sources VitalDB, a comprehensive database of 6388 surgical patients admitted to Seoul National University Hospital. Eligibility criteria for study selection Cases with ECG lead II recording duration of less than one hour were excluded. Cases with more than 20% of missing HRV measurements were also excluded. A total of 5641 cases were eligible for the analyses. Methods Six machine learning models including Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Trees (GBT), Extreme Gradient Boosting (XGB), and an ensemble of the five baseline models were developed to predict postoperative clinical outcomes. The prediction models were trained using only clinical information, and using both clinical information and HRV features, respectively. Feature importance based on the SHAP method was used to assess the contribution of the HRV measurements to the outcome predictions. Subgroup analysis was also performed to evaluate the risk association between postoperative ICU stay and various HRV measurements such as heart rate, low-frequency power (LFP), and short-term fluctuation DFA $${\alpha }_{1}$$ α 1 . Result The final cohort included 5641 unique cases, among whom 4678 (83.0%) cases had ages over 40, 2877 (51.0%) were male, 1073 (19.0%) stayed in ICU after surgery, 52 (0.9%) suffered in-hospital death, and 3167(56.1%) had a total length of hospital stay longer than 7 days. In the final test set, the highest AUROC performance with only clinical information was 0.79 for postoperative ICU stay, 0.58 for in-hospital mortality, and 0.76 for the total length of hospital stay prediction. Importantly, using both clinical information and HRV features, the AUROC performance was 0.83, 0.70, and 0.76 for the three clinical outcome predictions, respectively. Subgroup analysis found that patients with an average heart rate higher than 70, low-frequency power (LFP) < 33, and short-term fluctuation DFA $${\alpha }_{1}$$ α 1 < 0.95 during anesthesia, had a significantly higher risk of entering the ICU after surgery. Conclusion This study suggested that HRV measurements during anesthesia are feasible and effective for predicting postoperative clinical outcomes.

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Comparison between Analgesia Nociception Index (ANI) and self-reported measures for diagnosing pain in conscious individuals: a systematic review and meta-analysis

Cited by 9 publications

References 57 publications

Analgesia nociception index and high frequency variability index: promising indicators of relative parasympathetic tone

Analgesia nociception index and high frequency variability index: promising indicators of relative parasympathetic tone

The Relationship between Pre-Anesthetic Analgesia and Nociception (ANI) and Propofol Injection Pain among Patients Receiving Remifentanil: A Prospective, Randomized, Controlled Study

The prognostic value of intraoperative HRV during anesthesia in patients presenting for non-cardiac surgery

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