The incidence of postoperative acute kidney injury (AKI) in adult non-cardiac surgical patients reportedly ranges from 3% to 35% [1,2]. Much attention has been paid to postoperative AKI as it can independently result in poor patient outcomes. In particular, some studies have reported that AKI affects both short- and long-term outcomes even in patients with mild severity who recovered after a short period of time following cardiac or non-cardiac surgery [1,3,4]. Therefore, it is important to reduce the incidence of postoperative AKI by identifying high-risk patients through preoperative assessment, intraoperative monitoring, and through the provision of appropriate management during and after surgery [5,6]. There has been extensive research on the risk factors of perioperative AKI and an increasing number of studies are using machine learning and big data to predict AKI [5,7,8]. Known risk factors (some of which are not modifiable) reported by these studies include advanced age; pre-existing kidney disease or elevated preoperative serum creatinine levels; pre-existing comorbidities such as hypertension (HTN), congestive heart failure, and insulin-dependent diabetes mellitus (DM); obesity; sex; intraoperative blood transfusion; hemodynamic instability; and use of vasopressors or diuretics [1,9–13]. Interestingly, a recent study reported that peripheral perfusion index (PPI) during surgery may also be associated with postoperative morbidity and mortality, indicating that PPI may be a risk factor worthy of further investigation [14,15]. To date, though there have been many studies that seek to predict high-risk groups for AKI or provide recommendations for controlling risk factors, there have been no studies that assessed the relationship between intraoperative PPI and postoperative AKI.

Therefore, in this study, we hypothesized that low PPI is related to the occurrence of postoperative AKI and aimed to determine whether this was an independent risk factor.

This study revealed that low intraoperative PPI was associated with postoperative AKI. The PPI value is known to reflect two main determinants: the cardiac output and the balance between the sympathetic and parasympathetic nervous systems [22,23]. Its usefulness as a vital sign for risk stratification or for determining early intervention has been studied in various scenarios such as emergency departments, ICUs, and operating rooms. PPI can be used to evaluate disease severity or fluid responsiveness in critically ill patients, and can also be used to predict hypotension or poor outcomes [24–27]. Moreover, fluid responsiveness can be evaluated in patients undergoing surgery as PPI reflects cardiac output [23,28]. From the perspective of oxygen delivery and tissue perfusion, it is important to maintain adequate cardiac output rather than the more commonly monitored blood pressure, because blood pressure is affected not only by cardiac output, but also by systemic vascular resistance [29]. Similarly, in critically ill patients with a low flow state, organ dysfunctions such as AKI are likely to occur due to a decrease in tissue perfusion even if blood pressure is maintained at normal with increased vascular resistance [30,31]. While hypotension was a risk factor for postoperative AKI in some previous studies [14,32], hypotension did not significantly increase AKI occurrence in our study. It may be because the cut-off value for hypotension is not a fixed MBP level but a value that differs for each patient. Another reason could be because blood pressure is not a good indicator of cardiac output that is more critical for organ perfusion. Since PPI could reflect cardiac output [23,28], monitoring of PPI during surgery could provide additional information on tissue perfusion and oxygenation. As cardiac output was not measured for the patients in our study, we were unable to evaluate the correlation between cardiac output and PPI. However, low PPI may reflect a decrease in cardiac output that may increase AKI occurrence by altering kidney perfusion; furthermore, it may cause poor outcomes by altering perfusion of other major organs; further research on this will be needed for a better understanding of this mechanism [31].

Other risk factors showed similar results to those reported in previous studies [7,9,12]. In terms of ORs, pre-existing renal disease had the highest OR at 5.82, followed by intraoperative transfusion at 3.64, followed in turn by male sex, emergent operation, prolonged duration of surgery, higher ASA physical status, obesity, and older age. Unfortunately, anesthesiologists are unable to modify most of these factors. Additionally, the effects of sex on AKI occurrence are controversial. A study on patients who underwent cardiac surgery suggested that male sex had a protective effect [12], but another study on patients who underwent general surgery showed the opposite result [1]. In this study, we found that men were 3.17 times more likely to develop AKI. This is consistent with the results of the previous studies that showed a higher likelihood of AKI development in male hospitalized patients during follow-up [33,34]. The reasons behind this should be investigated in the future.

Patients who developed AKI had a higher likelihood of ICU admission, new initiation of renal replacement therapy, longer hospital stays, and higher all-cause mortality. Considering that the incidence of in-hospital mortality or postoperative complications was not high in our study, additional studies with larger number of patients are needed to determine whether low intraoperative PPI or AKI itself are causes or predictors of these outcomes.

The present study had several limitations. First, our study was based on a review of recorded data, and the SUPREME system was unable to filter erroneous data or incorrectly entered information. In the case of vital signs collected automatically during surgery, errors may occur due to mechanical or electrical stimulation. To reduce such errors, the SUPREME system information was reconfirmed individually through electronic medical records if the input information was judged to be an outlier. Through this process, it was possible to identify cases where patient height and weight were entered in the reverse order, and where laboratory results from body fluid and not blood were entered incorrectly. Additionally, we checked whether blood pressure and plethysmography waveforms collected in vitalDB had a normal shape to ensure that there were no errors in vital sign data.

Second, the participants of this study were limited to patients who underwent general surgery to reduce the number of confounding variables such as intraoperative cardiopulmonary bypass, one-lung ventilation, or different targets of surgery. Additionally, a postoperative laboratory test was routinely performed by the surgeon that may have biased patient selection. Further studies are required to confirm these results in other patients.

Lastly, although it is known that PPI is associated with poor prognosis, it is not known how PPI can be improved since many of the risk factors for AKI identified so far, including the results of this study, cannot be modified. If a method to improve upon these risk factors can be found and applied to patients with intraoperative and preoperative PPI, this can help reduce postoperative AKI, and in turn morbidity and mortality.

In conclusion, we found that low PPI is a risk factor for postoperative AKI. Future studies based on this finding may be able to construct a more comprehensive model for AKI prediction, or aid patient prognosis through improvement of PPI.