INTRODUCTION
Hypokalemia, characterized by serum potassium concentration less than 3.5 mmol/L, is a pervasive clinical concern that becomes particularly critical in the perioperative setting.
1-3) Although mild hypokalemia (serum K
⁺ 3.0–3.5 mmol/L) is often asymptomatic, epidemiological evidence recognized it as an increased risk of stroke and mortality.
4)
Progressive declines in serum potassium levels can lead to significant systemic complications, including muscle weakness, flaccid paralysis, metabolic alkalosis, renal dysfunction, and paralytic ileus. Severe cases may provoke life-threatening cardiac arrhythmias, which can rapidly progress to respiratory failure and cardiac arrest.
1,3,5) Its prevalence and impact are magnified in surgical populations,
6) especially those with underlying cardiovascular comorbidities,
7,8) such as patients undergoing carotid endarterectomy (CEA), a condition that primarily affects older patient populations.
In the surgical patient, even mild hypokalemia can lower the threshold for cardiac arrhythmias, particularly in the context of anesthesia, intraoperative stress, blood loss, and the use of vasoactive drugs.
9-11) It can also potentiate the effects of neuromuscular blocking agents and delay recovery from anesthesia.
12) For vascular surgery patients, this electrical instability poses a direct threat to cerebral and cardiac perfusion.
13-15) Postoperative hypokalemia further exacerbates arrhythmogenic susceptibility, impairs hemodynamic stability, and is associated with an increased incidence of adverse neurological and cardiovascular events.
13-15) Moreover, preoperative hypokalemia has been established as an independent predictor of 30-day major adverse cardiovascular events after noncardiac surgery.
2)
Consequently, prompt identification and correction of hypokalemia are imperative to optimizing postoperative recovery and outcomes, particularly in older patients who tolerate electrolyte imbalances poorly. Nonetheless, a clear understanding of predictive factors and a validated risk assessment tool for postoperative hypokalemia specifically following CEA, with consideration of geriatric-specific risk profiles, remains lacking.
Therefore, the primary aim of this study was to identify perioperative factors associated with potassium dysregulation that correlate with the incidence of postoperative hypokalemia in patients undergoing standard CEA, with emphasis on variables relevant to aging populations. Based on these factors, we sought to develop and validate an individualized predictive nomogram to facilitate early risk stratification and tailored perioperative management.
MATERIALS AND METHODS
Study Population
This retrospective cohort study recruited 1,189 patients with severe carotid artery stenosis who underwent standard CEA at Peking University Third Hospital from October 2021 to May 2023.
The inclusion criteria were as follows: (1) diagnosis of severe carotid artery stenosis (NASCET standard) and undergoing standard CEA at Peking University Third Hospital, and (2) availability of standardized electrolyte assessments both preoperatively and postoperatively.
The exclusion criteria were as follows: (1) nonatherosclerotic causes of carotid artery stenosis, such as arteritis or arterial dissection; (2) incomplete laboratory test results; (3) coexisting primary disorders that cause hypokalemia, including primary aldosteronism, renal tubular acidosis, Cushing's syndrome, and hereditary conditions such as hypokalemic periodic paralysis; and (4) long-term use of medications that significantly affect serum potassium levels, such as oral potassium supplements or diuretics.
A total of 1,076 patients with complete datasets were ultimately enrolled (
Fig. 1). The study protocol was approved by the Ethics Committee of Peking University Third Hospital (ethics number: S2018206). Written informed consent was acquired from all participants prior to their enrollment in the study. All procedures were conducted in accordance with the Declaration of Helsinki.
Data Collection
Data were retrospectively collected from the electronic medical record system. Variables of interest encompassed demographic characteristics (age, sex, body mass index), admission laboratory profiles (including complete blood count, potassium level, liver and renal function tests, blood glucose, lipid profile, cardiac enzymes, albumin, and homocysteine levels), left ventricular ejection fraction (LVEF), and documented medical history (including hypertension, diabetes, coronary heart disease, and cerebral infarction). Frailty was assessed at hospital admission using the Fried Frailty Phenotype. This tool defines frailty based on the presence of three or more of the following five criteria: unintentional weight loss, self-reported exhaustion, weakness (measured by grip strength), slow walking speed, and low physical activity. Additionally, postoperative visual analogue scale (VAS) to measure pain intensity were also obtained.
The primary outcome of this study was the occurrence of postoperative hypokalemia, defined as a serum potassium level of <3.5 mmol/L based on the first available measurement within 24 hours following surgery. According to this definition, patients were categorized into two groups: the hypokalemia group (serum K⁺ <3.5 mmol/L) and the non-hypokalemia group (serum K⁺ ≥3.5 mmol/L).
Detailed information regarding specific surgical procedures and postoperative pain assessment is provided in
Supplement A.
Statistical Analysis
Patient characteristics were summarized using descriptive statistics. Continuous and categorical variables are presented as mean±standard deviation or median (interquartile range) and frequencies (%), respectively. Groups were compared using Student t-test or Mann-Whitney U test for continuous variables and chi-square or Fisher exact test for categorical variables, as appropriate.
Variables with a p-value <0.05 in univariate analysis were included in the multivariate binary logistic regression model to control for potential confounders and identify independent risk factors for postoperative hypokalemia. Results were reported as odds ratios (OR) with corresponding 95% confidence intervals (CI). A pre-specified subgroup analysis was performed on patients aged ≥70 years, employing both descriptive statistics and univariate logistic regression. In addition, we also performed a new subgroup analysis comparing patients with postoperative potassium levels >4.0 mmol/L versus those with levels of 3.5–4.0 mmol/L to identify preoperative predictors of maintaining higher postoperative potassium levels.
A nomogram was constructed based on the final multivariate model to visualize individualized risk prediction. The discriminative ability was evaluated using the time-dependent area under the receiver operating characteristic curve (AUC), internally validated via bootstrapping. An AUC value >0.7 was defined as indicative of reasonable predictive performance.
Random Forest and XGBoost models were also developed (80% training, 20% testing) to predict postoperative hypokalemia. Model performance was evaluated by AUC, Brier score, and accuracy, with interpretability assessed via SHAP (SHapley Additive exPlanations) analysis.
All analyses were performed using Python 3.12.11 and R version 4.4.2 (
https://cran.r-project.org), with a two-sided p-value <0.05 considered statistically significant.
DISCUSSION
This cohort study establishes that postoperative hypokalemia is a common complication, occurring in 17.9% of patients following standard CEA for high-grade stenosis—a finding consistent with the broader hospital-based literature reporting rates of 14%–40%.
1) Such potassium (K
⁺) imbalances are frequently observed in the perioperative setting, with an incidence of 0.2%–16.0% in the general surgical population, escalating markedly to 2.9%–71.0% among high-risk patient cohorts.
16)
We focused specifically on CEA because this standardized vascular procedure is performed in a patient population particularly susceptible to hypokalemia due to prevalent cardiovascular comorbidities and age-related physiological changes.
6-8) Furthermore, in CEA patients, even mild hypokalemia carries heightened clinical significance, as electrolyte disturbances can precipitate arrhythmias or hemodynamic instability that may compromise cerebral perfusion critically.
13-15) This procedural homogeneity helps control for surgical variability and strengthens internal validity. However, we acknowledge that this focus inherently limits generalizability to other surgical contexts. Future research should validate and adapt this predictive model in diverse surgical cohorts to assess broader clinical applicability.
In the present study, preoperative potassium, HGB, BMI, frailty and postoperative VAS were identified as independent risk factors for postoperative hypokalemia. Among these, preoperative serum potassium, HGB, and BMI were protective factors, while frailty and postoperative VAS score were risk factors. This suggested that the occurrence of hypokalemia after CEA arose from the synergistic interplay of multiple pathophysiological mechanisms, primarily involving pre-existing potassium depletion, frailty and compromised nutritional status, and pain-induced stress responses.
The strong inverse correlation between preoperative potassium levels and the risk of postoperative hypokalemia highlighted the critical role of pre-existing potassium depletion. This observation was consistent with previous studies across various surgical contexts,
17-21) which collectively underscored that preexisting hypokalemia or even physiologically low-normal potassium reserves, constituted the strongest predictor of postoperative hypokalemia. For instance, a retrospective cohort study on patients undergoing en bloc resection for oral cancer identified a preoperative serum potassium cutoff of 3.98 mmol/L as a significant predictor of postoperative hypokalemia (relative risk=1.76).
17) Similarly, another study in the same population reported that preoperative levels below 3.87 mmol/L were independently associated with hypokalemia (OR=2.484, p=0.008).
21) These thresholds lied above the conventional lower limit of normal (3.5 mmol/L), supporting the notion that even within the normal range, relatively lower levels may reflect ongoing potassium depletion and reduced buffering capacity, thereby increasing perioperative risk.
21) Surgical stress exacerbates potassium loss and transcellular shifts. In patients with preoperative negative potassium balance, sympathetic activation
22) and insulin secretion
23) further promoted intracellular shifting. Consequently, there were growing evidence to suggest that the potassium target should be raised to at least 4.0 mmol/L, with proactive supplementation considered when levels fall below.
1,17,24) The aforementioned findings were supported by studies in elderly patients and those undergoing total joint arthroplasty, which also identified preoperative hypokalemia as an independent risk factor for postoperative potassium disturbances.
18-20)
Although neither group in our study met the criteria for anemia, a modest peri-operative decline in hemoglobin was still associated with a higher risk of postoperative hypokalemia. This observation was consistent with the findings of Pan et al.,
19) who identified preoperative red blood cell count as an independent predictor of hypokalemia after total joint arthroplasty (OR=0.417, p=0.027) and suggested that the effect might be attributable to intra- and postoperative loss of red blood cells and fluids. From a pathophysiological perspective, the following mechanisms may explain this link: (1) acute loss of red-cell mass reduces total-body potassium buffering capacity
25); (2) consequent blood-volume contraction triggers sympathetic activation and subsequent β₂-adrenergic stimulation of the Na
⁺/K
⁺-ATPase, thereby promoting a shift of potassium into cells.
26,27)
Large-scale observational studies have consistently demonstrated a strong association between nutritional vulnerability and hypokalemia. In the multinational PDOPPS cohort, lower serum potassium was associated with poorer nutritional status, reflected through reductions in BMI, body weight, serum albumin, phosphorus, urea, and muscle mass, along with elevated inflammatory markers and impaired residual kidney function.
28) Similarly, in patients with anorexia nervosa during refeeding, low BMI, together with hypoalbuminemia and binge-purge behavior, served as a critical predictor for hypokalemia risk, which could lead to life-threatening conditions.
29) Low BMI and frailty represented overlapping clinical manifestations of nutritional depletion that converge on potassium homeostasis disruption through shared mechanisms. Compared with non-frail older adults, those with severe frailty exhibited a stepwise increase in electrolyte disturbances, including hypokalemia.
30) Central to this relationship is the reduction in lean body mass, as skeletal muscle contain approximately 80% of the intracellular potassium and was the single largest pool of body potassium.
31) Lower BMI is often indicative of reduced muscle mass, directly limiting potassium storage capacity.
32,33) This was especially consequential in older adults, in whom sarcopenia and frailty frequently coexist.
34,35) Moreover, frailty often accompanied and exacerbated chronic malnutrition and inadequate intake
36); it was also associated with comorbidities and polypharmacy that promote potassium wasting.
37-39) Under physiological stress such as surgery, these patients lacked metabolic reserve to compensate for potassium losses from bleeding, drainage, or internal shifts, markedly increasing their susceptibility to hypokalemia. Empirical evidence supported this elevated risk. Frailty has been identified as an independent predictor of hypokalemia in patients with acute ischemic stroke,
40) and significantly increased the risk of postoperative complications across in non-cardiac and cardiac surgery, with higher morbidity, longer hospital stay, and greater mortality compared with non-frail patients.
41,42) The consensus for orthopedic patients advocated systematic peri-operative management of frailty, including regular electrolyte monitoring to prevent frailty-related complications.
43) In our study, although underlying medical histories were similar between groups, the higher prevalence of frailty in the hypokalemia group suggested that frailty captured a dimension of vulnerability not reflected by binary comorbidity data. This association was biologically plausible: frail individuals likely exhibited reduced total body potassium stores due to sarcopenia (muscle loss), chronic subclinical malnutrition with inadequate dietary potassium intake, and impaired neurohormonal responses to surgical stress. These mechanisms reflected decreased physiological reserve rather than specific disease diagnoses, explaining why frailty was elevated in the hypokalemia group despite comparable comorbidity profiles. In summary, low BMI and frailty were interrelated indicators of poor nutritional reserve that predisposed to hypokalemia through shared mechanisms—reduced potassium storage, impaired intake, and diminished adaptive capacity. Their co-occurrence identified a high-risk phenotype prone to postoperative hypokalemia requiring intensified monitoring and prevention in clinical practice.
Our study identified postoperative pain as an independent determinant of hypokalemia. This finding was consistent with previous research demonstrating that intravenous patient-controlled analgesia significantly reduced the severity and incidence of postoperative hypokalemia following laparoscopic cholecystectomy.
44) The association was likely mediated through several mechanisms: First, pain-induced catecholamine release stimulated β₂-adrenergic receptors and activated Na
⁺/K
⁺-ATPase, promoting intracellular potassium translocation.
9) Second, pain-related discomfort may suppress oral intake, thereby exacerbating negative potassium balance. Although patients in our study resumed oral intake within 6 hours post-surgery, inadequate consumption due to pain may have contributed to potassium depletion. Third, although less commonly observed, pain-associated anxiety could provoke hyperventilation, leading to respiratory alkalosis,
45) which further facilitated potassium shifts into cells.
46)
Furthermore, our analysis revealed a paradoxical association: patients who maintained higher postoperative potassium levels presented with baseline characteristics traditionally predictive of adverse outcomes. This counterintuitive observation invites mechanistic interpretation. The recently published POTCAST trial in
the New England Journal of Medicine (NEJM) provides a critical framework for understanding this phenomenon.
47) That multicenter, randomized study demonstrated that actively maintaining serum potassium in the high-normal range (4.5–5.0 mmol/L) reduced the composite risk of sustained ventricular tachycardia, appropriate ICD therapy, arrhythmic or heart failure hospitalization, and mortality by 24% (hazard ratio=0.76, 95% CI 0.61–0.95, p=0.01) in high-risk patients with cardiovascular disease.
47) Building on this foundation, we hypothesize that the mild renal impairment frequently observed in older, comorbid patients may trigger compensatory potassium conservation mechanisms that inadvertently confer arrhythmic protection. This adaptive renal response could stabilize perioperative potassium homeostasis, effectively “pre-conditioning” these patients against ventricular arrhythmias despite their otherwise unfavorable risk profile.
The developed nomogram offers a practical tool for individualized risk assessment, and the predictive stability of these variables was further confirmed by machine learning algorithms. The nomogram achieved an AUC of 0.710, indicating moderate discriminative ability. While not exceptional, this performance is generally considered acceptable for initial model development, particularly for complex multifactorial outcomes like perioperative hypokalemia. The model's utility lies in its practical application as a low-cost screening tool using routine preoperative variables to identify high-risk patients who may benefit from increased vigilance and preemptive measures, rather than serving as a definitive diagnostic instrument. Its clinical value should be evaluated through prospective implementation studies focused on improving patient outcomes. For clinical implementation, this tool could be integrated into electronic health records during preoperative assessment to flag potentially high-risk patients. As an illustrative example, one might consider a predicted risk threshold, such as approximately 30%, which could represent a substantially elevated risk, to trigger a bundled care pathway:
1) Proactive potassium supplementation: For instance, patients with preoperative K⁺ below an illustrative cutoff like 4.0 mmol/L might be candidates for supplementation.
2) Enhanced nutritional support: For example, patients with BMI below 24 kg/m² or HGB under 130 g/L might receive dietitian consultation. These values could serve as potential markers of compromised metabolic reserve, particularly relevant in certain populations.
3) Frailty-specific management: For frail patients, implement comprehensive geriatric assessment, medication review, and early mobilization.
4) Aggressive multimodal pain control: Prioritize regional anesthesia and scheduled non-opioid analgesia to maintain postoperative VAS scores at a low level (e.g., ≤3/10), which might help minimize catecholamine-driven potassium shifts.
5) Postoperative monitoring: For illustration, patients above a certain risk threshold, such as roughly 20%, could undergo serum potassium measurements at intervals like 6, 12, and 24 hours postoperatively.
48) These stratified interventions could facilitate resource allocation and preemptive management in vulnerable older adults, though all proposed thresholds require prospective validation to establish optimal cutoffs and improve clinical efficacy.
Several limitations should be acknowledged. First, medication data that can influence potassium levels, such as diuretics, ACE inhibitors/ARBs, corticosteroids, and insulin, were not systematically collected.
49) In this surgical cohort, loop diuretic use was uncommon, and thiazide exposure was likely limited to low-dose combination formulations. Nevertheless, this remains an important limitation, as uneven distribution of these medications between groups could have confounded our findings. Future studies should incorporate detailed medication records to better control for these factors and refine the model. Second, our study relied on a single postoperative potassium measurement within 24 hours. Serial measurements at key timepoints (e.g., immediately post-surgery in the post-anesthesia care unit, at 6, 24, and 48 hours) would provide a more comprehensive and physiologically relevant profile, enabling detection of transient hypokalemia, capturing trends over time, identifying distinct temporal risk patterns, and assessing the effectiveness of corrective interventions. Future studies should implement structured potassium monitoring protocols with time-series analysis to better guide intervention timing. Third, the single-center design limits external generalizability, and our internal bootstrapping validation may not capture population-level heterogeneity. While internal validation suggests robustness, the model currently lacks external validation. Future multicenter, prospective studies involving diverse patient populations, healthcare settings, and surgical teams are required to externally validate the nomogram before widespread clinical implementation. Finally, observational design precludes causal inference—randomized trials are needed to test whether correcting identified deficits improves outcomes.
In conclusion, we developed a validated tool to predict postoperative hypokalemia after CEA. The model highlights that in addition to biochemical and surgical factors (preoperative hypokalemia and pain), geriatric syndromes like frailty and nutritional status (reflected by low BMI and hemoglobin) are pivotal risk determinants. This facilitates early, individualized management, including tailored potassium supplementation, nutritional support, and aggressive pain control, especially for vulnerable older adults, to mitigate complications and promote recovery.