In the current study, both AKI diagnosis and prediction varied in male vs. female patients based on the methods used to estimate baseline kidney function, and criteria used to define AKI (percent vs. absolute change in serum creatinine). The following observations were made: (1) the use of pre-operative serum creatinine as a surrogate for kidney function resulted in higher risk for CS-AKI in female patients due to lack of adjustment for non-GFR determinants of serum creatinine. The risk of CS-AKI was abrogated when eGFR was used to account for sex-based differences in serum creatinine levels due to differences in body muscle mass and creatinine production. (2) At any given absolute change in serum creatinine immediately following surgery, the risk of progression to moderate or severe AKI was higher in female patients compared to an equivalent change in male patients. (3) The use of absolute change in serum creatinine, resulted in higher incidence of 0.3 mg/dL based AKI rates in male vs female patients. (4) The inclusion of patient age, sex, weight and height significantly improved the discrimination and calibration of a previously developed and validated peri-operative serum creatinine-based AKI predictive model in females.

Higher incidence of CS-AKI in female patients has been attributed to higher disease burden due to referral bias [2, 23,24,25]. In the current study, however, surgery type or cardiopulmonary bypass duration was comparable between the sexes. Preoperative eGFR on the other hand was significantly lower in female patients despite corresponding lower serum creatinine levels.

The discord in estimation of baseline kidney function between serum creatinine and estimated GFR is due to confounding where lower muscle mass overestimates kidney function when based on serum creatinine levels in female vs. male patients. Subsequently predictive models which include baseline serum creatinine will invariably have female gender associated with higher incidence of AKI [2, 23, 26]. In the current cohort, there was a significant interaction between pre-operative serum creatinine and patient sex, where the risk of AKI based on matching serum creatinine was higher in female patients as a consequent of lower corresponding kidney function. In addition, the substitution of creatinine with estimated GFR (adjusted for anthropometric differences) as a surrogate for kidney function, also eliminated the increased AKI risk attributed to female sex [27,28,29]. Indeed, consistent with the current findings, AKI models studied post cardiac surgery that are based on GFR estimates rather than serum creatinine, did not show female sex as a risk factor [3, 30].

Of note, when eGFR (BSA indexed eGFR) was used to estimate kidney function, there was a significant attenuation of AKI risk associated with female sex. However, this risk was further reduced when eGFRRAWwas used but with height and weight adjustments performed in a regression model. There are two possible explanations for the additional offset noted in the latter strategy compared to eGFR use. First, there are unaccounted sex differences in BSA estimation that are not captured with the use of equation by Du Bois & Du Bois (irretrievably factored in CKD-EPI equation) [21]. The BSA equation by Du Bois was derived from only 9 subjects, using unsophisticated statistical methods that were available in 1916 [31]. In the present cohort, eGFR showed a differential relationship with height depending on patient’s sex; it showed positive linear correlation in women and no correlation in men. In other words, the relationship with height is not corrected in women as it is in men, by indexing to BSA, which may result in overestimation of GFR in tall and underestimation in short female patients. Moreover, the practice of indexing physiologic measures (such as GFR, cardiac output, etc.), although entrenched in medicine and medical research, is problematic because they rely on strict assumptions which are often violated [32, 33]. In contrast to indexing method, the use of regression to adjust for anthropometric characteristics does not require any assumptions such as having a positive linear relationship, and an intercept of zero. Second, both smaller body size and female sex have been independently associated with smaller coronary arteries; therefore anthropometric measures by their own right could be associated with AKI (rather than through kidney function) [34,35,36]. In the current study, however, the effect of patient’s height or weight on the duration of cardiopulmonary bypass was negligible, discounting an immediate effect of patient size on surgical outcomes.

In contrast to reports of elevated AKI risk post cardiac surgery, female sex has been deemed protective in other settings [11, 12, 37]. Analysis of Veterans Affairs data, which included about 6 thousand female patients, male sex was identified as a risk factor for post-operative AKI in the fully adjusted model [37]. Similarly, the analysis of large national compilation of surgical outcome data from 121 US hospitals showed male sex to be independently associated with post-operative AKI [38]. In many of these reports, AKI diagnosis was based on absolute (0.3 mg/dL) change in serum creatinine after its incorporation in AKI diagnosis and classification criteria in 2007 [9, 39]. Absolute change in creatinine has been adopted initially based on its association with short term mortality in post cardiac surgery patients [40]. Also time to diagnosis based on absolute change in serum creatinine is considerably shorter compared to percentage based criteria in male patients who on average have higher serum creatinine than female patients; where the higher the pre-operative creatinine the longer it would take to reach percentage based endpoint (such as doubling) due to constant rate of creatinine production [22, 41]. An implicit assumption in the use of absolute changes of creatinine in AKI diagnosis is that an equivalent change in serum creatinine represents the same risk in all patients. However, the higher serum creatinine levels in male patients (caused by larger muscle mass) leads to higher incidence of AKI diagnoses exclusively based on small absolute changes in creatinine. Conversely, due to lower kidney function in female compared to male individuals with an identical serum creatinine, an equivalent absolute change in serum creatinine is much more likely to be clinically consequential in female patients. In our study, there was disproportionately higher number of male patients who were labeled with AKI when absolute change in serum creatinine was used, compared to thresholds based on percent change in serum creatinine or provision of dialysis. Also for the same perioperative change in serum creatinine, female patients were much more likely to progress to moderate to severe AKI, particularly in those with elevated preoperative serum creatinine. Differential misclassification of AKI based on absolute change (or thresholds) in serum creatinine is not restricted to female patients who are historically underrepresented in clinical studies, but also betides children and individuals with low muscle mass (chronic illness, prolonged hospitalization, etc.).

It is also important to consider observed biological and analytical variability in serum creatinine measurements that might affect diagnostic accuracy based on criteria used to define AKI. For example, criteria based on absolute change in serum creatinine increase false positive rates in patients with elevated baseline, such as in male compared to female patients [42]. Whereas, AKI definitions based on percent change in patients with very low baseline serum creatinine (as seen in pediatric population) will be due to analytic or biologic variation rather than change in kidney function [43].

The addition of female sex and other determinants of muscle mass such as age, height and weight to a previously developed and validated peri-operative test based predictive model for CS-AKI, improved model performance in female patients, and other subgroups with low muscle mass [22]. The inclusion of patient sex in the model however should not be construed as an intrinsic biological risk for AKI but as necessary effect modifier when serum creatinine is used as a surrogate for kidney function. In fact, the omission of patient sex (and anthropomorphic measures) will lead to poor model performance at its best and to biased results at its worst in marginalized groups.

Our study has limitations. First, the current results apply to AKI in cardiac surgery setting where the etiology and management strategies of AKI are more homogeneous compared to other settings. This favors the detection of biologic differences, but not other factors related to gender, socioeconomic status or delivery of care. Second, the current study reflects the experience and the processes of care delivered in a large volume cardiac surgery referral center and may not be representative of other practices. Third, baseline kidney function assessment by pre-operative serum creatinine or serum creatinine based eGFR assumes steady state, which may not be applicable to all patients. Fourth, the current study does not directly measure muscle mass or GFR. Fifth, the current study did not evaluate the effect of patient sex on AKI diagnosis and classification based on urine output criteria. Finally, due to the observational nature of the study, the current findings are associations and should be considered hypothesis generating.

In conclusion, although clinical and experimental science point to sex differences in susceptibility to AKI, the current study findings show that the association and its direction was dependent on the operational definition of pre-operative kidney function (overestimation), and differential outcome misclassification due to AKI defined by absolute change in serum creatinine (underestimation). It is important to recognize the implications of methods used in baseline kidney function estimation and AKI outcome classification in vulnerable groups, let alone half the population. Furthermore, with the advent of artificial intelligence and big data analytics there is a risk of magnifying and perpetuating conflated variations that may result in unintended consequences and outcomes.