Diabetes mellitus (DM) is the most common cause of chronic kidney disease, which leads to end-stage renal failure worldwide. Glomerular damage, renal arteriosclerosis, and atherosclerosis are the contributing factors in diabetic patients, leading to the progression of kidney damage. Diabetes is a distinct risk factor for acute kidney injury (AKI) and AKI is associated with faster advancement of renal disease in patients with diabetes. The long-term consequences of AKI include the development of end-stage renal disease, higher cardiovascular and cerebral events, poor quality of life, and high morbidity and mortality. In general, not many studies discussed extensively “AKI in DM.” Moreover, articles addressing this topic are scarce. It is also important to know the cause of AKI in diabetic patients so that timely intervention and preventive strategies can be implemented to decrease kidney injury. Aim of this review article is to address the epidemiology of AKI, its risk factors, different pathophysiological mechanisms, how AKI differs between diabetic and nondiabetic patients and its preventive and therapeutic implications in diabetics. The increasing occurrence and prevalence of AKI and DM, as well as other pertinent issues, motivated us to address this topic. Over the past 2 decades, diabetes mellitus incidence and prevalence have steadily increased, from an estimated 30 million in 1985 to 537 million in 2021 and it is anticipated that the number will increase to 643 million by 2030 and 783 million by 2045. Considering recent trends, microvascular and macrovascular disorders are associated with long-term diabetes-related complications. One significant microvascular sequelae of diabetes are diabetic nephropathy (DN) or diabetic kidney disease (DKD). Around 20% to 40% of diabetic patients are thought to suffer from DKD, and approximately 40% will need renal replacement therapy at some point in their lifetime.,5 Risk factors for the progression of CKD include gender, racial disparities, hereditary factors, concurrent comorbid illnesses, for example, diabetes mellitus (DM), metabolic abnormalities, and previous episodes of acute kidney injury (AKI), etc.Type 2 diabetes is one of the primary causes of chronic kidney disease (CKD) and end-stage renal disease (ESRD) globally.–9 Diabetes is a distinct risk factor for AKI. Although baseline DM is also an independent risk factor for AKI in multivariate analyses adjusted for estimated glomerular filtration rate (eGFR). There have been other studies that showed that patients with diabetes may be more prone to AKI.,13 Acute tubular injury caused by renal insults may have an impact on kidney function, leading to chronic functional impairment and later maladaptive recovery and failure to entirely undo the insults.,15 Generally, there is a significant correlation between AKI and the emergence of CKD and ESRD.,17 In a cohort of 4082 patients with diabetes, Thakar et al showed that AKI episodes were related to a cumulative likelihood of developing progressive CKD, regardless of the presence of any other significant risk factors for progression. Subsequently, a large prospective study provided additional evidence that AKI is a strong indicator of unfavorable outcomes (doubling of serum creatinine or ESRD) and mortality in diabetes.AKI, which affects up to 1% of the general population and 15% of all hospitalized patients, is a worldwide health issue. compared 119,966 diabetic patients with 1794,516 nondiabetic patients and showed that the incidence of AKI was significantly higher in diabetic patients . Despite accounting for additional known comorbidities and AKI risk factors, the differences remained statistically significant. However, in their study, a clinical coding system rather than a biochemical definition of AKI was employed, which could result in significant under-ascertainment. Additionally, a meta-analysis by James et al revealed that participants with diabetes had higher AKI hazard ratios than participants without diabetes, regardless of their eGFR levels. Again, the AKI definition in these studies was based on administrative codes, which underestimated mild forms of AKI.Girman et al, an annual AKI incidence was 12.6%. There was a substantial deviation from previously published studies by Thakar et al and Monseu et al, who reported AKI incidence of 2.8% and 5.2%, respectively.In a retrospective cohort study by Prabhu et al found that diabetic patients had higher rates of AKI than controls . The AKI risk among diabetic patients was 5 times higher than that of controls, even in the absence of CKD (121.5 vs 24.6 per 1000 person-years). AKI rates in diabetic patients with CKD were twice as high as in controls .In their retrospective cohort of 16,700 participants (9417 with type 2 diabetes and 7283 nondiabetic controls), Hapca et al in their prospective case-control study, which included patients with severe sepsis and septic shock with or without diabetes, found that the incidence of AKI did not differ between the 2 groups however, diabetic patients requiring dialysis more often, had higher mean serum creatinine levels, and less recovery than nondiabetic patients. However, this study has several limitations, as the diagnosis was made based on the medical history, long-term diabetic complications, and HBA1C levels were not incorporated, initial renal function status was missing, and for the diagnosis of AKI, urine output criteria were not used. Finally, the requirement for dialysis was not assessed using defined criteria. This absence of differences between these 2 groups may be explained by these confounding factors.Recently, Venot et al Table Very few studies have examined concurrent AKI, CKD, and recurrent AKI in this group of patients. reported that diabetes alone was still associated with a higher risk of acute kidney failure, even after accounting for other risk factors, such as chronic kidney disease. Additional risk factors for AKI were increasing age, chronic kidney disease, systemic hypertension, previous history of AKI, and congestive cardiac failure. The combination of type 2 diabetes with congestive cardiac failure or systemic hypertension further increases the risk of AKI. In a previous study, elderly patients with heart failure had a 3.37-fold higher risk of AKI than those without heart failure, whereas hypertension was linked to a 1.94-fold higher risk of acute kidney injury. Acute kidney injury occurred in 21% of patients in a cohort study admitted with congestive heart failure as their primary diagnosis. preexisting proteinuria, hypertension, and diabetes mellitus were all independent AKI risk variables revealed in the study by Hsu et alGirman et al, there was a correlation between AKI incidence and lower baseline eGFR, and higher proteinuria. With every 1 g rise in proteinuria, they have revealed that AKI risk was increased by 15.8%. Moseu et al came to the same conclusion regarding the correlation of AKI incidence with lower eGFR and albuminuria. A large cohort study showed moderate to high proteinuria was a risk factor for AKI among all eGFR groups in hospitalized patients with AKI.According to Prabhu et alIn comparison, nondiabetic patients, surgical patients with diabetes, and those taking oral antidiabetic medications had a 30% higher chance of developing acute renal failure following surgery, while those taking insulin had a 70% higher risk. Patho physiological mechanism depends on the type of drug involved. ACE/ARB (angiotensin-converting enzyme/angiotensin receptor blocker) were the main causes of AKI contributing to 35% of cases due to their increased use in diabetic patients. This risk was even higher in patients with congestive heart failure, volume depletion, diuretics, nonsteroidal anti-inflammatory drugs (NSAIDs), and bilateral renal artery stenosis. Aminoglycoside (gentamicin) and NSAIDs contributed to 16% followed by statins (10%), antitubercular agents (rifampicin), and ifosfamide 6% and 3% respectively. Glomerular filtration rate and renal blood flow are decreased as a result of the suppression of prostaglandin production due to NSAIDs. They also reported dehydration and intravenous rehydration as prognostic factors in their study.Drug-induced AKI represents 20% of all etiologies. Diabetic patients who used hydrochlorothiazide (HCT) frequently experienced renal events (decline in eGFR > 30%), which affected about 20% of individuals as shown in a retrospective study. Similarly, another study showed that diuretic-associated AKI patients had a higher rate of comorbidities  as compared to the non-diuretic AKI group. In the diuretic-induced AKI group, 27.5% was caused by diuretics only and 29.8% was caused by the combination of diuretics with other drugs.The histological lesion of AKI caused by diuretics may primarily manifest as tubular epithelial cell vacuolation. Risk is even higher in a combination of other drugs that is, NSAIDs, antibiotics, ACEi, and contrast. Similarly, from 1992 to 2001, AKI incidence among Medicare beneficiaries increased by 11% annually, with higher rates seen in the elderly, men, and African-Americans.AKI hospitalizations in the US have recently increased considerably, from 35,000 in 1979 to 650,000 in 2002. This increase was attributed to the increasing drug consumption by the elderly, and various comorbidities.Although it is believed that the use of ACE/ARB is linked to acute renal failure, it can be challenging to interpret published studies because those who are most at risk for AKI may also be the ones who are most likely to receive treatment with angiotensin-converting enzyme/ARBs. The combined effect of uncontrolled diabetes along with prerenal AKI may cause intrinsic renal AKI, characterized by renal parenchymal damage and tubular necrosis.Extracellular volume depletion due to glycosuria because of uncontrolled diabetes especially in pediatric patients leads to prerenal AKI. Sepsis was the primary cause of AKI in a retrospective study done by Prabhu et al In addition, they showed that there was a higher eGFR decline secondary to sepsis-related AKI as compared to other etiologies. Diabetes mellitus has been demonstrated to be an independent risk factor in a recent meta-analysis of sepsis-related AKI.Along with dysfunctional immune systems both humoral and cell-mediated, increase neutrophil dysfunction also contributes to an increased risk of sepsis. Due to impaired nitro vasodilation, increased endothelin synthesis, and hyperresponsiveness to adenosine-related vasoconstriction, peritubular blood flow may also be affected. According to data, the incidence of Contrast-induced AKI ranges from 5.7% to 29.4% in diabetes patients and is approximately 13% in nondiabetic patients. A recent meta-analysis showed that diabetes is associated with a higher risk of CI-AKI. Moreover, the subgroup of DM patients with CKD had a greater predictive effect of elevated CI-AKI but this correlation was not significant in the subgroup of patients without CKD.Diabetic patients, particularly those who developed DN, are more prone to contrast-induced injury. Diabetes and contrast-induced acute kidney injury (CI-AKI) are mutually causative, causing kidney function to deteriorate further. Renal hypoxia, generation of reactive oxygen species, and increased oxidative stress in diabetic patients lead to vascular constriction due to vasoactive substances. Immunological changes in diabetic patients also contribute to contrast-induced AKI. Signaling pathways that is, inflammation, reactive oxygen species production, and apoptosis related to both diabetes and contrast-induced AKI.Table ,49The pathophysiologic mechanisms causing diabetes-related kidney damage are multifactorial. Fig.  It has bEndothelial cell dysfunction is one of the main mechanisms underlying DN. Diabetic kidneys are known to produce less nitric oxide (NO), which is produced by the enzyme endothelial nitric oxide synthase (eNOS). Because of diabetes’s distorted NO metabolism, the renal vasculature is more vulnerable to stimuli that cause vasoconstriction.,51 Persistent glomerular hyperfiltration causes intraglomerular hypertension, followed by glomerulosclerosis, which causes a progressive decline in kidney function and eventually DKD.,51It is believed that in uncontrolled diabetes, renal vasculature dysregulation is the primary factor contributing to glomerular hyperfiltration.,53 The absence of a suitable vascular counterregulatory response to sustain kidney blood flow can also significantly worsen kidney hypoperfusion.,51In the case of prerenal AKI, when the body depends on variations in renal vascular resistance to maintain blood pressure, a dysregulation in normal renal vascular tone may hasten the kidney damage. It has been demonstrated that hyperuricemia can cause crystal-mediated and crystal-independent nephropathy, glomerular injury, and tubulointerstitial involvement. It is crucial to remember that hyperuricemia could signify dehydration, which can directly cause renal injury.Chronic and acute renal damage related to diabetes may be exacerbated by hyperuricemia. Apoptosis of endothelial cells, vascular rarefaction and hypoxia, mitochondrial dysfunction, proximal tubular disorder, podocyte disorder, podocyte apoptosis, and autophagy due to diabetes have all been shown in laboratory studies.Persistent hyperglycemia, which is related to prolonged ICU stays and an increased risk of AKI is another pathophysiologic pathway that results in CKD and eventually ESRD. Girman et al in a retrospective cohort showed that diabetic patients were 8 times more likely to have incident acute renal failure than nondiabetic patients. There have been 2 retrospective analyses, both of which had conflicting findings.,57 Diabetic patients had less severe AKI, recovery to baseline renal function and the proportion of patients developing progressive CKD was lower in the diabetic group as shown by Johns et al However, the 10-year retrospective analysis done by Xin S et al showed that the recurrence rate of AKI was higher in the diabetic group than in the nondiabetic group. Between diabetes and nondiabetic groups, mortality was comparable in both retrospective analyses.Diabetic patients are at higher risk of AKI than nondiabetic patients, which can be attributed to diabetes, chronic kidney disease, hyperglycemic crisis, drugs that is, ACE inhibitors and sodium-glucose cotransporter-2 (SGLT2) inhibitors, associated cardiovascular disease and heart failure, and previous AKI episodes. Moreover, being a systemic disorder affecting the heart and kidneys, and it is also associated with type 4 and type 5 CRS. SGLT 2 inhibitors were implicated in CRS due to both renal and cardioprotective effects. Reno protective effects of SGLT2 inhibitors in AKI contributed by increased vascular endothelial growth factor A expression, increase vasodilatation due to NO, and decrease renal fibrosis. Regardless of the presence of atherosclerotic CVD or a history of heart failure, these drugs decrease the hospitalization rate for heart failure and the progression of renal illness. EMPA-REG OUTCOME , DECLARE-TIMI 58, CANVAS (Canagliflozin Cardiovascular Assessment Study), and CREDENCE  are the 4 major trials in diabetic patients showed positive cardiovascular and renal outcomes.–65 In December 2016 there was an FDA alert regarding the use of canagliflozin and dapagliflozin. However, this increased risk of AKI with SGLT2 inhibitors was not supported by studies. Meta-analysis showed the protective effect of SGLT2 inhibitors with AKI, primarily driven by empagliflozin.Cardiorenal syndrome (CRS) is a disease affecting the heart and kidneys simultaneously. T2DM is a significant risk factor for the development of CRS; the National Health and Nutrition Examination Survey in the USA found a strong association between type 2 CRS and T2DM.These drugs should not be started in CRS 1 and 3 but may be continued with close hemodynamic and renal function monitoring. SGLT2 inhibitors are preferred drugs in CRS types 2, 4, and 5 for glycaemic, as well as metabolic, control.In AKI, there is no universal therapy for AKI. The primary goals of treatment are to address underlying causes, such as dehydration, avoiding nephrotoxic drugs, fluid, and electrolyte management, and renal replacement therapy. Moreover, sleep apnea in obese patients causes hypoxic episodes contributing to renal impairment. Hence weight control is an important preventive aspect in terms of decreasing renal injury.Obese patients have glomerulomegaly, increase renal blood flow, hyperfiltration, and higher albuminuria despite the absence of hypertension.,74 As patients with T2DM has more significantly greater urinary albumin-to-creatinine ratios than patients with T1DM even after adjustment for all known risk factors for diabetic kidney disease, as shown in the SEARCH study, hence RASS inhibitors are indicated in diabetic patients treatment frequently. However, these drugs have nephrotoxic effects directly or indirectly by affecting renal hemodynamic function.,74Renin-angiotensin-aldosterone system inhibitors have been shown to attenuate proteinuria and continue to be the cornerstone of current therapeutic methods.–78 However, accumulation of metformin in case of impaired eGFR  causes type B lactic acidosis and toxicity by impairing mitochondrial function. Thiazolidinediones, such as pioglitazone, have been shown to decrease proteinuria in a large meta-analysis. However, no randomized controlled trials showed renal protective effects of thiazolidinediones. Role of dipeptidyl peptidase inhibitors and glucagon-like peptide 1 receptor agonist as nephroprotective agents are controversial. These have been shown to have nephroprotective effects in some studies.,80 However their effects on eGFR were uncertain as shown in a recent Cochrane review. SGLT2 inhibitors were found to have a nephroprotective effect as shown in DECLARE-TIMI 58 and EMPA-REG OUTCOME trials, but in the Cochrane review, it did not show any effect on AKI risk.–82Many antihyperglycemic agents, including metformin, thiazolidinediones, dipeptidyl peptidase inhibitors, Glucagon-like peptide agonists, and SGLT2 (Sodium-glucose Cotransporter-2) inhibitors, also have nephroprotective properties in addition to glucose-lowering effects.Some drugs have been evaluated in animal models and may represent future therapeutic options for AKI prevention, such as mineralocorticoid receptor antagonists, endothelin receptor antagonists, peroxisome proliferator-activated receptors agonists, and phosphodiesterase inhibitors. In animal models, finerenone also decreases the progression of AKI to CKD, and hence it can be an excellent therapeutic option in AKI to prevent long-term complications.In summary, AKI is a complication of diabetes mellitus. It increases the risk of further episodes of AKI, progression to chronic kidney disease, end-stage renal disease, cardiac and cerebrovascular events, and all-cause morbidity and mortality. Additionally, diabetes is the risk factor for AKI irrespective of underlying CKD. Current strategies should focus on its identification and mitigation, reducing proteinuria, weight control, fluid management, removal of precipitant factors , and other supportive measures to improve AKI outcomes. Many glucose-lowering drugs (SGLT2 inhibitors) have nephroprotective against AKI in patients with diabetes in addition to their antidiabetic effects. A promising new approach to treating AKI and CKD using novel classes of medications that target renal hemodynamic dysfunction in diabetic patients. In the interim, healthcare professionals need to be aware of the risks and effects of AKI in patients with diabetes.Conceptualization: Amninder Kaur, Gaurav Shekhar Sharma, Damodar Kumbala.Supervision: Gaurav Shekhar Sharma.Validation: Gaurav Shekhar Sharma, Damodar Kumbala.Visualization: Amninder Kaur, Damodar Kumbala.Writing – original draft: Amninder Kaur.Writing – review & editing: Amninder Kaur, Gaurav Shekhar Sharma.s


AugMAP1 < 102.5 mmHg was associated with a 3-fold-increased risk of all-cause mortality 1-year post-TAVR . A univariate model of AugMAP1 surpassed the STS score model in predicting intermediate-term post-TAVR mortality . Conclusions: Augmented mean arterial pressure provides clinicians with a simple but effective approach to quickly identify patients at risk and potentially improve post-TAVR prognosis.Background: Post-transcatheter aortic valve replacement (TAVR) patient outcome is an important research topic. To accurately assess post-TAVR mortality, we examined a family of new echo parameters (augmented systolic blood pressure (AugSBP) and arterial mean pressure (AugMAP)) derived from blood pressure and aortic valve gradients. Methods: Patients in the Mayo Clinic National Cardiovascular Diseases Registry-TAVR database who underwent TAVR between 1 January 2012 and 30 June 2017 were identified to retrieve baseline clinical, echocardiographic and mortality data. AugSBP, AugMAP and valvulo-arterial impedance (Zva) (Zva) were evaluated using Cox regression. Receiver operating characteristic curve analysis and the c-index were used to assess the model performance against the Society of Thoracic Surgeons (STS) risk score. Results: The final cohort contained 974 patients with a mean age of 81.4 ± 8.3 years old, and 56.6% were male. The mean STS risk score was 8.2 ± 5.2. The median follow-up duration was 354 days, and the one-year all-cause mortality rate was 14.2%. Both univariate and multivariate Cox regression showed that AugSBP and AugMAP parameters were independent predictors for intermediate-term post-TAVR mortality (all  The success of transcatheter aortic valve replacement (TAVR) has substantially changed the landscape of managing aortic valve disease ,2,3. Wit2; AVA < 1 cm2 with AV peak velocity < 4 m/s or mean AV gradient < 40 mmHg. The Institutional Review Board at Mayo Clinic approved the study protocol, and all the patients provided research authorization to utilize their medical information.A chart review was conducted on patients in the Mayo Clinic National Cardiovascular Diseases Registry (NCDR)-TAVR database, which included patients from three major academic medical centers located in Rochester, MN, Phoenix, AZ, and Jacksonville, FL. We identified all patients aged ≥18 years who underwent TAVR between 1 January 2012 and 30 June 2017. Baseline demographics, lab data, device data, STS risk score and follow-up data were directly extracted from the database. Patients who had prior AVR (TAVR or SAVR) procedure(s) were excluded. Low-flow, low-gradient severe AS was defined as SVi < 35 mL/mBaseline transthoracic echocardiography (TTE) with 2-dimension imaging and Doppler were performed pre-procedure using commercially available ultrasound scanners . All echocardiograms were measured and interpreted according to guidelines ,21,22. O(1)Augmented SBP1 (AugSBP1): the mean aortic valve gradient (mean AVG) was added to systolic blood pressure (Equation (2)), and augmented MAP1 (AugMAP1) was calculated by replacing the SBP with augmented SBP1 in the MAP formula (Equation (3));(2)Augmented SBP2 (AugSBP2): the aortic valve maximal instantaneous gradient was added to systolic blood pressure (Equation (4)), and augmented MAP2 (AugMAP2) was calculated by replacing the SBP with augmented SBP2 (Equation (5));(3)Augmented MAP3 (AugMAP3): the aortic valve mean gradient was added to mean arterial pressure (Equation 6)) [) [6]. ZvNoninvasive blood pressure measured at baseline TTE was used to calculate augmented blood pressure parameters. The SVi was calculated using the quantitative Doppler method. In patients with atrial fibrillation, the highest mean transvalvular gradient was used. The augmented blood pressure calculation formulas used are described as follows:t-test and Mann–Whitney U test for normally and non-normally distributed data, respectively. Categorical variables were expressed as counts and percentages, and differences among groups were evaluated with the chi-square test. Kaplan–Meier survival curve and Cox regression were used for survival analysis; the median AugSBP1 and AugMAP1 were used as the cutoffs to stratify the patients for Kaplan–Meier analysis. The augmented blood pressure measurements, Zva and the STS risk score were used to develop univariate Cox regression models separately. In multivariate Cox regression analysis, two multivariate models were created. For model 1, variables were adjusted for STS risk score, right atrial (RA) pressure, right ventricular systolic pressure (RVSP) and albumin level; the variables already involved in the calculation of STS risk score  were not used. Model 2 excluded STS risk score but included the variables in its calculation (Python lifelines 0.26.3). The receiver operating characteristics (ROC) curve with the area under the curve (AUC) and the c-index were used to assess the performance of each univariate model against the STS risk score model. We used the bootstrap method to estimate the 95% confidence interval (95%CI) of AUC and c-index for each univariate model. DeLong’s test was used to assess the differences in AUC, and a paired Student t-test was used to evaluate the differences in the c-indices [p-value of less than 0.05 was used as the cutoff of statistical significance for all the hypotheses. All the analyses were performed in Python version 3.7.10. Patients were grouped into alive versus deceased groups, and higher AugMAP (≥median AugMAP1) versus lower AugMAP (<median AugMAP1) groups and analyzed accordingly. All the two-group comparisons were summarized as alive versus deceased groups if not otherwise specified. Continuous variables were summarized as mean ± standard deviation. The differences among groups were evaluated with the Student -indices . A p-valIt was not appropriate or possible to involve patients or the public in the design, conducting, reporting, or dissemination plans of our research.n = 551), and 97.3% (n = 947) were white. The STS risk score was available for all patients (n = 974), with a mean of 8.2 ± 5.2. The median follow-up duration was 354 days (interquartile range 51–378 days), and the one-year all-cause mortality rate was 14.2% (n = 139). The median time from baseline TTE to TAVR was 1.5 months. Systolic blood pressure , diastolic blood pressure  and mean arterial pressure  were significantly higher in the alive group. Detailed data are summarized in A total of 1071 patients were initially identified. A total of 974 patients were included for the final analysis after excluding 97 patients who had prior aortic valve replacement (TAVR or SAVR). The mean age was 81.4 ± 8.3 years old. In total, 56.6% were male (p = 0.221), mean aortic valve gradient , maximal aortic valve instantaneous gradient  and stroke volume index . Both right atrial pressure  and right ventricular systolic pressure  were significantly higher in the deceased group.There was no significant difference in LV ejection fraction  and AugSBP2  were significantly higher in the alive group. There were similar findings for AugMAP1 , AugMAP2  and AugMAP3 . Box plots were used to visualize the augmented blood pressure data .Regarding augmented blood pressure measurements, both AugSBP1  and the median AugMAP1  (n = 85) (p < 0.0001). In addition, Zva, current dialysis, Afib/Aflutter, hemoglobin level, right atrial (RA) pressure, right ventricular systolic pressure (RVSP), ≥moderate TR and albumin level were also independent predictors for all-cause mortality in univariate regression, while stroke volume index was not associated with intermediate-term mortality . The associations of AugSBP and AugMAP parameters remained significant after adjusting for the STS risk score and other clinical risk factors in model 1 and model 2 . In Kaplan–Meier analysis, we observed significant survival differences when stratifying patients by the median AugSBP1  A,B. Simi(n = 85) . In univp = 0.005) and AugMAP2 model  significantly outperformed the STS score model. AugSBP1 , AugSBP2  and AugMAP3  were comparable/non-inferior in predicting mortality when compared to the STS score model. The AUC for Zva  was numerically smaller than the STS score; however, the difference was not statistically significant. p = 0.001). Details are summarized in The STS score univariate Cox regression model (reference model) had an AUC of 0.587 (95%CI 0.521–0.649) in predicting intermediate-term mortality. Among all other univariate Cox regression models, the AugMAP1 model  surpassed the STS risk score in predicting intermediate-term post-TAVR all-cause mortality. To the best of our knowledge, this is the first application of augmented blood pressure parameters in assessing post-TAVR mortality. Our findings suggest that AugMAP1, as a surrogate marker of cardiac contractile function against systemic afterload in aortic stenosis patients, is closely associated with post-TAVR mortality and superior to the STS risk score. AugMAP is a simple but effective approach clinicians may employ to quickly identify high-risk patients and can potentially improve post-TAVR prognosis.When calculating the augmented blood pressure parameters, we assumed that adding either the mean or maximal instantaneous gradient to the systemic systolic blood pressure can reflect the true systolic pressure generated by the left ventricle . Assuminp = 0.005) and c-index (p = 0.001) comparison. The STS score has been reported as a strong predictor for both short-and long-term post-TAVR mortality [In both univariate and multivariate Cox regression analysis, all the augmented blood pressure parameters were independently associated with intermediate-term post-TAVR mortality. Notably, the AugMAP1 model had the best performance and surpassed the STS risk score in predicting intermediate-term mortality in the head-to-head ROC curve , with the mean SBP in the alive group being reasonably controlled (130.9 ± 21.4 mmHg). There was no significant difference between the alive and deceased groups regarding antihypertensive medications. Earlier studies have shown that higher blood pressure/hypertension after the TAVR procedure is associated with better outcomes [A possible concern in using this approach is that the parameter primarily relies on blood pressure measurements, which can vary from time to time, and suboptimal blood pressure control may cause higher blood pressure readings. In our cohort, all of SBP, DBP and MAP measurements were significantly higher in the alive group  with a mortality endpoint in 21 (18%) patients. Another study based on the Optimized CathEter vAlvular iNtervention (OCEAN)-TAVI registry included 1004 patients but reported that post-TAVR Zva was not associated with two-year all-cause mortality in multivariate analysis; the correlation between baseline Zva and mortality was not assessed in this study [p = 0.519). Compared to the performance of augmented blood pressure measurements, the component of total load  is likely the key of Zva’s association with mortality in prior works [In 2009, Hachicha et al. first demonstrated Zva was independently associated with mortality in aortic stenosis patients who underwent either surgical aortic valve replacement or medical therapy . After tnt in 21 % patientis study ,18,19. Ior works ,18,19. ICompared to the STS risk score, which requires an input of more than 70 variables and relies on an online calculator after completing extensive workup , our modAs a single parameter, augmented mean arterial pressure (AugMAP1) surpassed the STS risk score in predicting intermediate-term post-TAVR mortality. Augmented blood pressure parameters provide a simple but effective approach clinicians may employ to quickly estimate the clinical outcome of TAVR patients and can potentially improve post-TAVR prognosis by early identifying high-risk patients.This study is limited by its retrospective nature, and external validation is not available for the findings. To maintain a sufficient sample size, we did not further divide our patient cohort into subgroups for ROC analysis. To allow comparison with prior studies, we mainly used ROC-AUC as the metric of model performance, but the c-index results also demonstrated similar findings. Concerning the period of TAVR procedures, most of the patients in this cohort were considered to be at intermediate-to-high risk, so low-risk patients may not be well represented in this development cohort. Only a small portion of patients had ≥ moderate AR, which limits the applicability of AugMAP in patients with clinically significant AR. The time from the baseline TTE/blood pressure measurement to the TAVR procedure varied among patients, and the potential changes occurring between these two points were not considered. However, the median time from baseline TTE to TAVR was relatively short (1.5 months) for significant hemodynamic changes. While our approach eliminated the contribution of stroke volume index, the component of systolic blood pressure and transvalvular gradient in this parameter still inherited the intrinsic limitation of Zva . Additio


Introduction: Foot ulceration is a frequent diabetic complication with potentially fatal consequences. The pathophysiology of neuropathic ulcers in the diabetic foot is thought to be influenced by abnormal plantar pressures.Aim: This study aimed to compare the maximum peak pressures among diabetic patients with and without neuropathy. The secondary aim was to evaluate the effect of glycemic control on pressure changes in both feet.Materials and methods: The study used 62 diabetic individuals as participants. BMI was calculated, as well as illness duration, hemoglobin A1c, and the existence of neuropathy. Plantar pressure was measured in static (standing) and dynamic  settings for all patients using the BTS P-Walk system. The plantar pressures (kPa) at the five metatarsal regions, the midfoot region, and the medial and lateral heel regions were measured.Results: We found that the dynamic maximum pressures were significantly higher in patients with diabetic neuropathy (DN) compared to diabetics without neuropathy at the first metatarsal and mid-foot area in both feet (p<0.05). We also found significantly elevated plantar pressure in patients with poor glycemic control under the second metatarsal head in the right foot (p<0.05).Conclusion: Persons with DN have higher maximum plantar pressures compared to diabetics without neuropathy. Patients with poor glycemic control also have a higher maximum pressure. Diabetes is the primary health concern in the current era, posing a significant burden on health and social and economic development. According to a systematic study of the Global Burden of Disease Study 2021, the global diabetes population in 2021 was 529 million, with a worldwide age-standardized total diabetes prevalence of 6.1% (5.8-6.5) . DSPN isThis study was a 15-month cross-sectional study conducted at a tertiary-care teaching hospital in the division of diabetes and metabolism  in collaboration with the physical medicine and rehabilitation department. After obtaining institutional ethics committee clearance , 150 T2DM patients were screened after taking written and informed consent. We included diabetic patients aged more than 18 years of both sexes who can walk independently without any visible, apparent gait abnormalities. Patients with an abnormal gait, non-healing chronic ulcers, acute ulcers, amputation of one or both limbs, foot deformity, spine deformity, severe cardiovascular disease (New York Heart Association class 3 and 4), nephropathy , and other illnesses that impair quality of life and movement were all excluded. We also excluded pregnant women and patients who were unable to follow commands.All participants underwent assessment including history, the duration of diabetes, and any diabetic complications. Height, weight, and BMI were also calculated. They were evaluated for nephropathy by 24-hour urine proteins and retinopathy by a fundus camera. Neuropathy assessment was done using the neuropathy analyzer VIBROTHERM Dx , including vibration perception threshold by a biothesiometer , hot and cold perception threshold, and 10 g Semmes-Weinstein monofilament test . The normal values are shown in Table Each foot was examined in the six regions: great toe, first metatarsal head, third metatarsal head, fifth metatarsal head, midfoot, and heel. The sensitivity and specificity of neuropathy identification differ between studies. However, Mythili et al. discovered that the monofilament study's sensitivity and specificity were 98.5 % and 55 %, respectively. She also discovered that the vibration perception threshold's sensitivity and specificity were 86% and 96%, respectively .The diagnosis of DN was made if any one of the tests mentioned in Table Plantar pressure assessment was done using the BTS P-Walk system. The maximum pressures were taken in standing (static) and walking across the mat system (dynamic). Standardized instructions were given to participants. The pressures were documented in the first metatarsal area M1), the second metatarsal area (M2), the third metatarsal area (M3), the fourth metatarsal area (M4), the fifth metatarsal area (M5), the midfoot area (MF), the medial heel area (MH), and the lateral heal area (LH), as shown in Figure , the secData were recorded using Microsoft Office Excel  and analyzed using SPSS Statistics version 25 . Descriptive statistics were employed to summarize various clinical and demographic parameters. Categorical variables were presented as frequencies and proportions, while continuous variables were reported as either mean ± standard deviation or median with interquartile range, depending on the data distribution.To assess the significance of pressure changes between the two groups, the Mann-Whitney U test was applied. A p-value of less than 0.05 was considered statistically significant.Based on the abovementioned test results, the subjects were grouped according to the presence or absence of neuropathy: DN, in which 31 patients with T2DM were found to have neuropathy based on one positive test  and 13 female patients (41.9%) in each group. The mean BMI in the DN group was 24.9 ± 4.1 and in DC was 26.0 ± 3.4. On comparing the age and BMI, there was no statistically significant difference between them . These data are compiled in Table The mean glycated hemoglobin HbA1c%) in the DN group was 8.6 ± 1.6 and in the DC group 8.4 ± 2.2, without statistically significant difference. The duration of diabetes was significantly higher in the DN group compared to the DC group . This is depicted in Figure c% in thePlantar pressure (KPa) comparison between the two groupsThe maximum pressures in left static pressures were higher in DN in M1, M2, M3, M4, and MH, although the difference was not statistically significant. The maximum pressures in right static pressures were higher in DN in M2 and M3, although the difference was not statistically significant. The data is tabulated in Table The maximum dynamic pressure in the left foot was significantly higher in the DN group at the first metatarsal head  and the midfoot , and in the right foot, it was significantly higher in the DN group at the midfoot . The rest of the values are shown in Table We also grouped the patients based on the HbA1c value as good and poor glycemic control. We compared the dynamic pressures in both groups Table -5 and foThe direct or indirect consequences of hyperglycemia on the vascular system are the leading cause of morbidity and death in both T1DM and T2DM . DiabeteA widely recognized risk factor is plantar pressure, which has been demonstrated to be higher in individuals with diabetes compared to those without diabetes. This heightened plantar pressure has been linked to the development of ulcers, as evidenced by findings from a prospective study .The maximum dynamic pressure in the DN group was considerably greater than in the DC group, even though the groups were age, sex, and BMI matched. The diabetic duration was significantly higher in the DN group. This was comparable with similar results found by Sacco et al., who demonstrated higher plantar pressure among various stages of neuropathy patients compared with DC in the heel and forefoot areas . The autRichard et al. demonstrated higher dynamic pressures in the medial and lateral metatarsals . In a stin this study population, we compared the foot pressure changes in patients with poor and good glycemic control indicated by glycated hemoglobin concentration, although glycated hemoglobin concentration was considerably higher in both diabetes groups and was comparable in both groups. The maximum pressure while walking was considerably higher in patients with poor glycemic control at toe 1 and first, second, and third metatarsal heads. At the right second metatarsal head, there was a statistically significant difference.Similar results were found by Qiu et al. They found that HbA1c was positively correlated to the maximum pressure at the first metatarsal head . Some stThese findings, combined with previous results, suggest that the link between glycemic changes and peak plantar pressure is hazy and that it is more likely to be exerted indirectly through the effect of glycemia on the natural progression of peripheral neuropathy and the resulting impact of neuropathy on plantar pressure changes, foot abnormalities, and gait changes. The results of our study need to be explored by future studies on the Indian population.Attempts to establish a maximum pressure threshold for ulceration have been unsuccessful, and the apparent magnitude of pressure levels across studies is variable . DiffereLimitations of the studyObservational studies rely on the selection of participants from a specific population or sample, which is known as selection bias. It may be challenging to obtain a representative sample during the COVID-19 pandemic due to limitations on patient visits, lower participation rates, or adjustments in healthcare-seeking behavior. The absence of a comparison group of healthy individuals to know the pressure changes variation in diabetic patients without neuropathy. The study misses an opportunity to gather vital data regarding the development of the disease by failing to follow individuals who develop ulcers after having increased foot pressures. Understanding the progression of ulcer formation over time, its risk factors, and relevant therapies might be aided by this data. The ability to demonstrate a causal link between higher foot pressures and ulcer formation is constrained by the lack of follow-up data. Without monitoring the development of ulcers in patients with high pressures over time, it is difficult to say if the pressures alone cause ulceration or if other variables play a role.In conclusion, persons with DN have higher maximum plantar pressures. Poor glycemic control indicated by higher glycated hemoglobin may also correlate to higher pressures in those patients. Future research is needed to fully understand the processes and effects of neuropathy and glycemic management on diabetic foot pressure variations.


Spinal anaesthesia complicates maternal hemodynamic and may expose the parturient to dangerous cardiovascular problems. Up to 7% to 89.2% of pregnant women can suffer from spinal anaesthesia-related hypotension. The aim of this study to compare the hemodynamic changes between preeclamptic and normotensive parturients who underwent caesarean section under spinal anaesthesia at North Showa Zone Public Hospitals, Oromia Region, from February 15 to May 15, 2022.. Data were collected from patient charts and intraoperative observations and entered into the Epi Data software version 4.6 and exported to the Statistical Package for the Social Sciences version 25 software. Hemodynamic change =  * 100. The independent t-test, Mann–Whitney U test, two ways mixed ANOVA, chi-square, and Fisher's exact test was used to analyze the data as appropriate. A P < 0.05 was statistically significant.A prospective cohort study was conducted on a total of 140 parturients (70 in each group) who underwent cesarean delivery under spinal anesthesia. The study participants were chosen using a consecutive sampling techniquep = 0.638. The proportion of preeclamptic parturients who develop hypotension was 47%, compared to 74% of normotensive parturients, and the RR of developing hypotension, if participants were preeclamptic, was 0.63, with a 95% confidence interval of 0.412 to 0.978 and a p = 0.039. The mean change in heart rate during the first 15 min was comparable between the groups.The mean percentage change in SBP, DBP, and MAP after spinal anaesthesia was a statistically significant difference between the normotensive and preeclamptic groups, except MAP at 15 min was comparable between the two groups with In contrast to normotensive parturients undergoing caesarean section under spinal anaesthesia, our study found that the hemodynamic change was lower in preeclamptic parturients. The proportion of preeclamptic women who develop hypotension was 47%, compared to 74% of normotensive parturients. Spinal anesthesia is a popular anesthesia technique for cesarean sections because it avoids the risks associated with general anesthesia, such as difficult intubation and aspiration of gastric contents , 2. The A drop in mean arterial pressure (MAP) of more than 20% from baseline is considered hypotension following spinal anesthesia . DespiteCesarean delivery complicates maternal hemodynamics and may expose the parturient to dangerous cardiovascular problems. Spinal anesthesia-related hypotension affects up to 7% to 89.2% of pregnant women after cesarean delivery , 7. NausDespite the fact that spinal anesthesia is frequently the favored approach for caesarean birth , 9, due Furthermore, the incidence of spinal anesthesia-induced maternal hypotension varied among research, making it impossible to establish standard guidelines and create a local therapeutic plan –17. OtheIn 2015, Sub-Saharan Africa accounted for two-thirds, of all maternal deaths worldwide. From the two thirds of deaths, the magnitude of spinal anesthesia related deaths is around 6% . DespiteAn institutional-based prospective cohort study was carried out at public hospitals in North Showa Zone, Oromia region, from the seven public hospitals in the North Showa zone, those three hospitals, Salale University Comprehensive Specialized Hospital (SUCSH), Kuyu General Hospital (KGH), and Chancho Hospital, were selected by simple random sampling. SUCSH, which is located 112 km from Addis Ababa, KGH, which is located 43 km from SUCSH and 165 km from Addis Ababa, and Chancho Hospital, which is located 40 km from the capital city of Ethiopia.Ethical approval for this study was obtained from the ethical review board of Wolaita Sodo University, College of Health Sciences and Medicine, with protocol unique No. CHSM/ERC/03/14. Then, a support letter was obtained from the Medical Director of the hospital to conduct the research, and written informed consent was obtained from study participants. Privacy and confidentiality of the interviews and information gathered was assured at all level of study.All Parturients who underwent caesarean section delivery under spinal anesthesia at public hospitals in the Oromia Region, North Showa zone served as population’s source. ASA physical status II and III parturients, women over 18 years old, and women carrying a singleton pregnancy were included in the study from February 15 to May 15, 2022. Those who are in active labor, Patients with chronic hypertension, renal, or cardiac disease, diabetes, hypothyroidism, or hyperthyroidism in a parturient, Parturients with placenta abruption, placenta previa, BMI > 35 kg/m2, and adjuvants added to local anesthesia were excluded from the study.The sample size was calculated using G*power version 3.1.9.7 software and the mean with standard deviation between the two groups were taken from a previous study done in Gondar on the topic of hemodynamic changes after spinal anesthesia in preeclamptic patients undergoing cesarean section , 28. BasThree trained BSc anesthetists used structured check lists and questionnaires developed by reviewing various literature to collect data from patient charts and intraoperative observations. Before the actual data collection, the adapted format was evaluated by an expert researcher. Patients were monitored with non-invasive automated blood pressure cuffs, an ECG, and pulse oximetry. Before any invasive procedure or spinal anesthesia, baseline blood pressure and heart rate were measured. All patients were preloaded with crystalloids (500–1000 ml) 10–15 min prior to SA being given, with oxytocin 10–20 IU, and then 10–12.5 mg of 0.5% isobaric bupivacaine was given between lumbar three and four and lumbar four and five levels. Immediately after spinal anesthesia administration, the parturients were put in a supine position with a pillow inserted under their shoulder, and the maternal hemodynamics parameters  were recorded. The exposed group was those with a systolic blood pressure (SBP) of greater than 140 mm Hg and a diastolic blood pressure (DBP) of greater than 90 mm Hg using noninvasive automated blood pressure (NIBP) measurement and urine protein dipstick plus one or two, and the controlled group was those with normal blood pressure and no protein urea (trace or negative protein dipstick). All patients selected for the study were asked for their consent, and after a complete sensory (> T10) block, a skin incision was started. Assessments of hemodynamic parameters were made at three-minute intervals, initially for the first twenty minutes, then at five-minute intervals until the end of the procedure. Supervisors checked each questionnaire daily, with a further cross-check by the principal investigator for completeness and consistency of data.The data was checked for completeness, coded, and entered into Epi Data software version 4.6 before being exported into Statistical Package for the Social Sciences (SPSS) version 25 software, where missing values were checked before analysis.A mean with a standard deviation was used to summarize data, tables, and figures to display results. The data were tested for normality using the Shapiro–Wilk normality test and histogram inspection, and homogeneity of variance was assessed using Levene’s test for equality of variances of two samples in SPSS version 25 software. Outliers were assessed by box plots. Normal distributed continuous variable was compared by using the independent t test and expressed by mean ± SD. Non normal distributed continuous data was compared using the Mann–Whitney U-test and expressed as the median or interquartile range (IQR).The Chi-square test, or Fisher exact test, was used to calculate the categorical data between two groups as appropriate. The relative risk (RR) with a 95% confidence interval (CI) was used to determine the incidence of hypotension. A P value of less than 0.05 is considered significant. For repeated measures, homogeneity of covariance was assessed by Box’s M test. Mauchly’s test was used to check for sphericity, and the Greenhouse–Geisser correction was used when the assumption of sphericity was violated for the two-way interaction.Preeclampsia is defined as a systolic blood pressure (SBP) of greater than 140 mm Hg, a diastolic blood pressure (DBP) of greater than 90 mm Hg using noninvasive automated blood pressure (NIBP) measurement and urine protein dipstick plus one or two, which is recorded from the patient's chart ['s chart .Severe preeclampsia is defined as systolic blood pressure (SBP) being greater than 160 mm Hg, diastolic blood pressure (DBP) being greater than 110 mm Hg using noninvasive automated blood pressure measurement (NIBP) and urine protein dipstick plus two or more, which is recorded in the patient's chart ['s chart .Hemodynamic change is defined as blood pressure and heart rate change from baseline by 20%, either an increase or decrease [decrease , 30, 31.Mild hypotension: less than 20% decline in mean arterial blood pressure (MAP) below the base line in both groups [h groups .Moderate hypotension: Blood pressure reduction of 20% to 30% from the mean arterial blood pressure baseline [baseline –34Severe hypotension: more than 30% decline in mean arterial blood pressure below the base line in both groups [h groups , 33.The percentage fall in blood pressure and heart rate from base line  between two measurements is calculated as:Percentage of hemodynamic change =  * 100.Negative (-) values indicate the percent fall of a parameter  from its corresponding baseline value and are higher than baseline values at some intervals after spinal anesthesia.Normotensive: Having normal blood pressure and have no protein urea (trace or negative protein dipstick) [ipstick) .One hundred forty parturients who underwent cesarean sections and fulfilled inclusion criteria were enrolled into two groups (70 in each group). In terms of age, weight, height, BMI, new-born weight, and parity, there was no significant difference between the two groups Table .Table 1p = 0.001  = 6.12.In terms of the mean preload fluid, baseline HR, dose of bupivacaine, dose of oxytocin, speed of bupivacaine administration, level of sensory block, surgeon status, and experience of anesthetist, these were comparable in both groups Tables  and 3. TP = 0.001)  ml, while in the normotensive group it was 1900(550) ml (1) Table . The est01 Table .The mean change in heart rate between the two groups was no different from the start of SA to first15 minutes. The mean change in heart rate from 18 to 31 min was a statistically significant difference between the groups Table .Table 4p value less than 0.05, except at 15 min. At 15 min, the mean change in MAP was non-significant, with a 95% CI of -4.00 to 2.46, a p value of 0.638, and t (138) = -0.47  = -6.50  = 94.180; P = 0.001; and Partial eta squared = 0.406. The main effect of time is a statistically significant difference in mean MAP at the different time points: F  = 157.568; P = 0.001, and partial eta squared = 0.533; ε = 0.831. There was no statistically significant interaction between the baseline and other levels of time on MAP for the groups (p > 0.05). When compared to preeclamptic groups, the mean change in MAP, the more decrement, was seen in normotensive groups except at 15 and 21 min of SA  = 38.833; p = 0.039. The preeclamptic group has a 37% lower risk of developing hypotension than the normotensive parturient group.The proportion of preeclamptic women who develop hypotension was 47%, compared to 74% of normotensive women, and the RR of developing hypotension if participants were preeclamptic was 0.63, with a 95% confidence interval of 0.412 to 0.978 and a p = 0.0161  ml, compared to 1000(500) ml in the preeclamptic group (P = 0.001).The normotensive group’s higher vasopressor consumption than that of preeclampsia; around 29% of normotensive parturients took vasopressor but around 11% in preeclamptic groups with In the Republic of Macedonia, a prospective study by Sivevski et al. found that the incidence of hypotension was 25% in preeclamptics compared to 53% in healthy parturients. That blood pressure  falls (%) from baseline was significantly greater in healthy parturients than in those with preeclampsia . This reSignificant variations in SBP, DBP, and MAP were reported in both groups at each time point by Nikooseresht et al. . This reIn spite of receiving fewer crystalloid fluids and a larger dose of 0.5% bupivacaine, a prospective comparative study of 60 parturients by Aya et al. revealed that the incidence of hypotension in severely preeclamptic parturients was 16.6% and 53.3% in normotensive groups. Significant hypotension was defined as a systolic blood pressure reduction of less than 100 mmHg in healthy pregnant women or a mean blood pressure decrease of 30% in both groups . FollowiP < 0.05). Overall, intravenous phenylephrine dosages for treating hypotension were generally less in pre-preeclampsia patients. In terms of age, weight, height, and volume of ringer lactate preloading, patients with preeclamptic and normotensive patients were equivalent [According to Chowdhury et al.’s study, Preeclamptic patients had a lower risk of hypotension than healthy parturients  observed that despite normotensive women receiving more IV fluids, the incidence of hypotension in severely preeclamptic women was found to be much lower (55% versus 89%), (2.5 versus 2.4 L) . DespiteAccording to Mendes et al. (Brazil) a prospective cohort study, the mean drop in systolic blood pressure was 27.5 percent in the severely preeclamptic group and 24.2% in the normotensive group, while diastolic blood pressure decreased by 33.1 percent and 35.9 percent, respectively, and this was not statistically significant. They found no statistically significant difference between the two groups in terms of hypotension, ephedrine use, and total ephedrine dose . This stIn Ethiopia, a prospective cohort study by Alemayehu et al. found that the incidence of hypotension was 34.1 percent in preeclamptics compared to 55.6 percent in healthy parturients. This was similar to our research finding, but the magnitude of hypotension in our finding was relatively higher than that of Alemayehu . The disP < 0.05) [Our finding was supported by Tamiru et al. on 84 parturients undergoing cesarean section, which showed a higher incidence of hypotension in the normotensive group compared to the preeclamptic group  . The defp- value less than 0.05. This result was contradicting previous work [Following spinal anesthetic induction in both groups, the mean values of HR did not alter significantly during the first 15 min. However, the mean change of heart rate from 18 min to the end of the surgery showed a significant difference between the groups with a ous work , 28, 36.The difference in hypotension incidence is caused by factors connected to preeclampsia. The possibility is that chronic vasoconstriction is partially caused by damaged vascular endothelium, as observed in preeclampsia, which produces more endogenous vasopressors like thromboxane and endothelia .In contrast to normal pregnancy, where the altered vascular tone, decreased response to endogenous vasopressors, and increased synthesis of vasodilator prostaglandins and nitric oxide make them particularly sensitive to spinal anesthesia and cause hypotension after spinal anesthesia, this phenomenon does not change after SA in preeclampsia, resulting in fewer hemodynamic changes . StrengtIn contrast to normotensive parturients undergoing caesarean section under spinal anaesthesia, our study found that the hemodynamic change was lower in preeclamptic parturients. The proportion of preeclamptic women who develop hypotension was 47%, compared to 74% of normotensive parturients Fig. .


The intervention group showed significantly shorter durations of hypotension , reduced hospital stays and smaller decreases in post-surgery haemoglobin levels. Additionally, the intervention group experienced shorter times from the end of surgery to extubation. These findings suggest that incorporating targeted interventions during intraoperative care for AIS patients undergoing posterior fusion can lead to improved outcomes.A prospective, single-centre, non-randomised, case–control study aimed to evaluate the effectiveness of intraoperative haemodynamic monitoring, prediction of hypotension and goal-directed therapy on the outcomes of patients undergoing posterior fusion for adolescent idiopathic scoliosis (AIS). The control group ( Adolescent idiopathic scoliosis (AIS) is the most common spinal deformity in children. The most commonly occurring (in 80%) idiopathic scoliosis is a three-dimensional spinal deformity, and the exact cause of which is not yet fully understood. Ongoing research into the aetiology of this condition suggests possible genetic factors. Idiopathic scoliosis is diagnosed when the curvature exceeds 10 degrees. Approximately 2–3% of the entire population is affected by this deformity. It occurs more frequently in children and adolescents from families where this condition has already been present (around 7%). Surgical treatment is indicated when the spinal curvature reaches approximately 40–50 degrees. Surgical correction is a challenge for the anaesthetist because of the large surgical area and the need for specific anaesthetic techniques adapted to intraoperative neurophysiological monitoring of the spinal cord. The risk of spinal cord injury can be reduced by using intraoperative neuromonitoring and maintaining adequate spinal cord perfusion.Intraoperative haemodynamic stability remains an important factor in the post-operative prognosis of patients undergoing surgery for AIS. Hypotension and consequent tissue hypoperfusion are major causes of poor neurological outcomes. Monitoring intraoperative volemia, cardiac function, blood pressure and haemoglobin level helps to ensure adequate oxygen delivery (DO) to the organs. Tissue hypoxia is one of the major causes of perioperative complications . ApproprIntraoperative hypotension (IOH) is common during surgery. There is no universally accepted definition of IOH. Different definitions describe different incidences. IOH has the potential to cause ischaemia–reperfusion injury, which may manifest as dysfunction of any vital organ . There aStandard methods based on non-invasive blood pressure monitoring may not be sufficient to detect perfusion abnormalities. Blood pressure may be normal during hypovolemia due to increased vascular resistance; heart rate may not reflect hypovolemia due to the influence of anaesthesia. What is more important with oscillometric technique, in relation to the invasive blood pressure measurement, is it overestimates low blood pressure readings and underestimates high blood pressure readings. Therefore, more advanced haemodynamic monitoring methods and devices have been developed.Uncalibrated devices use the patient’s anthropometric and demographic characteristics, internal databases and algorithms to calculate the cardiac output from the arterial waveform, which is suitable for perioperative optimisation protocols. Calculated, measured or derived haemodynamic parameters are useful in determining the causes of hypotension. The ability to predict intraoperative hypotension allows a shift from reactive to proactive management. The cause of impending IOH can be identified earlier and appropriate treatment can be initiated sooner. The duration of hypotension can be reduced and hypotension-related complications can be effectively prevented. This idea is now available in practice. An Edwards Lifesciences machine learning algorithm—Acumen Hypotension Prediction Index (HPI)—based on thousands of arterial waveform features, can identify a hypotensive event 15 min before it occurs with high sensitivity and specificity. Currently, there are no other reliable methods of predicting the likelihood of hypotension.Goal-directed therapy (GDT) is a haemodynamic treatment based on the titration of fluid and inotropic agents infused to physiological flow-related endpoints . ImplemeAdvanced haemodynamic parameters routinely used in adults have a poor correlation in children . No arteThe aim of this study was to evaluate the effectiveness of intraoperative haemodynamic monitoring, prediction of hypotension and targeted therapy on the outcome of patients treated with posterior fusion for AIS.A prospective, single-centre, non-randomised, case–control study was conducted. The study included 59 consecutive Caucasian teenagers undergoing posterior fusion due to adolescent idiopathic scoliosis in the Department of Paediatric Orthopaedics and Oncology of the Musculoskeletal System, Pomeranian Medical University, in Szczecin, Poland. The inclusion criteria were first scoliosis operation and age under 18 years. Patients who were qualified for scoliosis surgery in this centre underwent X-ray imaging, computed tomography and magnetic resonance imaging. Patients with a Cobb angle greater than 45 degrees were considered eligible. Prior to anaesthesia qualification, echocardiography and spirometry examinations were performed. The exclusion criteria were advanced chronic respiratory–circulatory failure, emergency surgery, reoperation and scoliosis type other than idiopathic.The “control group” consisted of 35 patients (mean age 15 years), among whom 7 were boys, treated with a standard protocol of blood pressure management during surgery. The results were analysed, and based on these, the protocol of the “intervention group” was established. The “intervention group” consisted of 24 patients (mean age 14 years), with a predominance of females (3 boys). In the latter group, intraoperative minimally invasive haemodynamic monitoring and goal-directed therapy were adopted. The Consort diagram provided in clinicaltrials.gov. under the accession no. NCT 05159505.The study protocol was registered at After the surgery was scheduled, the patients were referred for an anaesthetic consultation and then qualified for general anaesthesia.On the day of the procedure, as a pre-emptive analgesia, the patient received metamizole , along with a carbohydrate-rich fluid  administered orally.All patients underwent general anaesthesia with intubation with a reinforced endotracheal tube and mechanical ventilation with a Primus apparatus . The control group did not follow a defined anaesthesia protocol. The administration of anaesthesia in the intervention group is depicted in The goal-directed therapy (GDT) protocol used in this study consisted of maintaining the desired levels of mean arterial pressure (MAP) and stroke volume (SV) through fluid therapy and vasopressor administration. The protocol is presented in Fluid therapy consisted of balanced crystalloid (Sterofundin—B. Braun/Optilyte—Fresenius Kabi) given at a rate of 4:2:1 mL/kg intravenously. The protocol was initiated when the patient was placed in the prone position, prior to which a bolus of 5 mg IV ephedrine was administered in response to hypotension. The target values were MAP > 60 mmHg, and in the case of depressed motor-evoked potentials (MEPs), MAP was maintained at >75 mmHg. If hypotension (MAP < 60 mmHg) and SV < 50 mL/beat were observed, a bolus of crystalloid at a dose of 5 mL/kg IV was given over 10–15 min. After the bolus, the response to fluid therapy was assessed. If SV increased by >10% and hypotension persisted, another fluid bolus was given. If there was no increase in SV > 10%, norepinephrine infusion was started to maintain MAP > 60 mmHg. If hypotension (MAP < 60 mmHg) was observed and SV was >50 mL/beat, a single dose of 5 mg ephedrine was administered. If the response was inadequate, norepinephrine infusion was started to maintain the target MAP. If SV was <50/beat but without evidence of hypotension (MAP > 60 mmHg) or peripheral perfusion failure—capillary refill time (CRT) < 2 s, no fluid bolus was administered. Colloid administration was prohibited. If blood loss exceeded 7 mL/kg, 1 unit of red blood cells was transfused.In this study, the intervention arm consisted of patients monitored with the Edwards Lifesciences Hypotension Prediction Index (HPI) device, specifically the Acumen sensor and Hemosphere monitor. When the HPI device’s hypotension alarm (HPI > 85) was triggered in the intervention group, the anaesthesiologist responded immediately by using a secondary screen. This screen allowed the assessment of the patient’s stroke volume variation (SVV), systolic slope/contractility (dP/dT) and dynamic arterial elastance (Eadyn) and made treatment decisions accordingly. The anaesthesiologist administered fluid boluses or vasopressors based on the patient’s specific condition and the secondary screen readings. This personalised approach to treatment prevented further hypotensive events .The surgical technique consisted of a posterior approach, ligament and bone release, implant fixations and final correction on titanium rods. The procedures were performed using a screws-only system or hybrid systems . The estimated blood loss for this surgical procedure is over 7 mL/kg. Patients are prepared with 2 units of packed red blood cells. The procedures are performed by two independent operators working simultaneously, utilising two electrocautery instruments concurrently. This approach reduces the surgical time and minimises blood loss.Throughout the procedure, the evoked motor and sensory potentials are monitored in order to control the function of the spinal cord. All screws were checked using direct nerve stimulation (DNS) electromyography.After surgery, all patients were monitored in the post-anaesthesia care unit (PACU) for 24 h. In addition to the assessment of vital signs, a protocol for the assessment of pain intensity according to the numerical scale (NRS) was performed every hour for 24 h and then every 8 h until discharge from the hospital, including the type, dose and route of administered drugs, the occurrence of side effects and complications. In the post-operative period, drugs were administered at regular intervals: paracetamol, metamizole, ibuprofen, magnesium sulphate, morphine and lignocaine infusions. Intravenous opioid infusion and transition to oral treatment were determined according to daily requirements.The described extent of preoperative preparation, the surgical technique, the type of analgesia used in the perioperative period and the parameters evaluated after surgery were the same in the “control” and “intervention” groups. In both groups, the hospitalisation plan was based on the principles of the enhanced recovery after surgery (ERAS) protocol. The current definition of ERAS programmes involves a multidisciplinary approach to improving surgical outcomes through the use of procedure-specific, evidence-based protocols in the care of surgical patients.Hypotension was defined as systolic blood pressure (SBP) less than 90 mmHg and MAP less than 60 mmHg for at least 1 min.2) < 90%.Adverse drug reactions were nausea, vomiting, pruritus, dyspnoea, constipation, urinary retention, dizziness, drowsiness preventing rehabilitation, apnoea, hypotension, bradycardia and decrease in peripheral capillary oxygen saturation  and duration of hospitalisation (days).Duration of the surgical procedure “skin to skin” (minutes)Duration of hospitalisation (days)Neurological complications (no)Cardiac complications (no)Red blood cells transfusion volume (mL)Fresh frozen plasma transfusion volume (mL)Intraoperative blood loss (mL)Crystalloids administered (mL/kg)Ephedrine total dose (mg)Haemoglobin level before surgery (g/dL)Haemoglobin level after surgery (g/dL)Change in haemoglobin level (g/dL)Haematocrit level before surgery (%)Haematocrit level after surgery (%)Change in haematocrit level (%)Time to extubation (min)The primary outcome was intraoperative hypotension time. The secondary outcomes were as follows:t-test was used as appropriate in regard to Shapiro–Wilk test. To analyse the link between qualitative variables, the chi2 test was used. The acceptable probability of error for the first type was assumed to be equal to 0.05. MedCalc statistical software version 20.110  was used. For controlling type I errors, the false discovery rate (FDR) approach was used. The calculations were performed using the p.adjust function of the stats package in R [The Shapiro–Wilk normality test was carried out to assess the distribution of continuous variables. Descriptive statistics were consequently presented as means and standard deviations or median and interquartile ranges (IQRs) as appropriate. Qualitative variables were presented as numbers and percentages. To compare the outcomes between the two groups, non-parametric Mann–Whitney or age in R . Statistage in R .Baseline characteristics of the study participants in terms of the tested procedure in p = 0.06) in regard to intraoperative diuresis.Exemplary There were four complications of neurological and cardiac nature in the control group alone (cardiorespiratory failure due to hypovolemic shock—three patients and transient limbs paresis—one patient). No such events occurred in subjects from the intervention group.The present study is the first report to evaluate the effectiveness of intraoperative haemodynamic monitoring, prediction of hypotension and targeted therapy on outcomes in adolescents undergoing posterior fusion for AIS.The study showed a significantly shorter duration of hypotension (MAP < 60 mmHg) in patients in the intervention group. There were no differences in the duration of surgery between the two groups, probably due to the same operators. The length of hospital stay was significantly shorter in the intervention group. In the control group, there were instances of cardiac and neurological complications, while no such complications were observed in the intervention group following the GDT protocol. Apart from these specific complications, no other adverse events were observed in either the control or intervention groups. The amount of crystalloids administered and the total dose of ephedrine were similar in both groups. Blood loss was similar in both groups, although fresh frozen plasma was transfused more frequently in the control group. There was a significantly smaller decrease in haemoglobin levels after surgery and a trend towards a smaller difference in haematocrit in the intervention group, despite higher baseline values in the control group. The time from the end of surgery to extubation was significantly shorter in the intervention group. Intraoperative diuresis was significantly higher in the intervention group.These positive results suggest that the intervention has the potential to improve post-operative recovery and overall patient outcomes.Spinal deformity surgery carries a risk of spinal cord injury of 0.3% to 0.6% according to surveys conducted by the Scoliosis Research Society . These nThe use of HPI monitoring, therefore, may offer a potential solution to this problem, as it has been shown to accurately predict hypotension in adults. In this study, the authors aim to evaluate the potential benefits of HPI monitoring in identifying patients at risk of hypotension during scoliosis surgery, with a particular focus on the prevention of intraoperative spinal cord ischaemia, the most common complication. The results of the present study indicate that invasive arterial pressure monitoring, together with the use of the HPI tool and the GDT protocol, allows a significant reduction in the duration of intraoperative hypotension. Moreover, it was observed that the amount of time during which the MAP remained below 55 mmHg was extremely brief. There is no existing research on the use of HPI monitoring in children, highlighting the need for further investigation into its potential benefits and applicability in this population.The Edwards Lifesciences HPI is a new technology that aims to predict the onset of hypotension before it occurs. The HPI is designed to identify potential hypotensive events in the next 5 to 15 min.Artificial intelligence (AI) is becoming an increasingly important part of medicine, with its use expanding every year. AI can be defined as the study of algorithms that give machines the ability to reason and perform functions such as problem-solving, object and word recognition, inference of world states and decision-making.The HPI is a supervised machine learning (ML) algorithm, a branch of AI based on the idea that a computer can be trained on specific input data and apply the knowledge gained from that data to newly presented data without being explicitly programmed to do so. This means that it has been trained to classify labelled outputs in order to predict a desired or undesired event. Supervised ML algorithms are trained on a set of labelled data , and then their predictive accuracy is tested on new data. The HPI algorithm went through internal and external validation sets, ultimately resulting in a highly accurate algorithm with an area under the receiver operating characteristic curve (AUC) of 0.95, 0.95 and 0.97 for 15, 10 and 5 min before a hypotensive event, respectively.The HPI algorithm uses several parameters derived from the arterial pressure waveform to predict the onset of hypotension. SV is the amount of blood pumped by the heart in one heartbeat. SVV is the percentage change in stroke volume during mechanical ventilation. These two parameters are derived from the arterial pressure waveform. Effective arterial elastance (Eadyn) is a measure of the ability of the arterial system to change size and shape in response to blood flow. It is calculated by dividing pulse pressure variation (PPV) by SVV. PPV is a measure of the variation in pulse pressure waveform during mechanical ventilation, while SVV is the variation in stroke volume during the same period. By analysing Eadyn, clinicians can determine whether the patient is likely to respond to additional fluids to raise blood pressure. In other words, Eadyn provides an indication of afterload responsiveness, or the ability of the arterial system to raise blood pressure by increasing the volume of blood pumped by the heart. dP/dt is a measure of the rate at which the arterial pressure waveform rises during systole. It is calculated by measuring the maximum slope of the arterial pressure waveform from a peripheral artery. The dP/dt values provide clinicians with information about the contractility of the heart. Using these parameters derived from the arterial pressure waveform, clinicians can predict the onset of hypotension and choose an appropriate intervention to prevent it. For example, if the HPI algorithm predicts that a patient is at risk of hypotension due to low stroke volume, clinicians can choose to administer fluids to increase preload and maintain blood pressure. Alternatively, if the patient’s afterload responsiveness is low, clinicians may choose to administer vasopressors to increase vascular resistance and maintain blood pressure. By using these parameters to guide decision-making, clinicians can take timely preventative action and avoid the potentially harmful consequences of hypotension.While the HPI is a useful tool for predicting the onset of hypotension, it has some limitations that clinicians should consider. The HPI algorithm has been developed and validated using data from specific patient populations and clinical settings. The algorithm was developed using records from operating theatre and intensive care unit patients and validated using a physiological dataset from surgical patients. While the HPI algorithm has shown promising results in these populations, its performance may vary in different patient populations or clinical contexts. In addition, clinicians must also consider the potential cardiodepressive effects of intravenous anaesthetic induction when assessing the risk of hypotension. Induction of anaesthesia can cause hypotension and bradycardia due to depression of cardiac contractility and peripheral vascular resistance. The index predicts hypotension but does not prevent hypotension in the absence of treatment. Without clinician awareness of the importance of hypotension prevention and immediate treatment, the protocol will fail. Education and confidence in new tools are very important parts of success in hypotension prevention.Although HPI monitoring has not been validated in the paediatric population and is not recommended by Edwards Lifesciences, the authors decided to use it in adolescents undergoing scoliosis surgery. This decision was based on the similar body surface area of the adolescents in our study to the patients in the HPI validation study . While tGDT protocols have become increasingly popular in the operating theatre as a way to optimise haemodynamic status and improve patient outcomes. There are several types of GDT protocols that can be used, including optimisation of stroke volume, cardiac output and oxygen delivery. These protocols involve the use of advanced monitoring techniques, such as arterial waveform analysis, echocardiography and pulse contour analysis, to guide fluid and vasopressor administration to achieve specific haemodynamic targets. Other protocols may be based on the use of dynamic variables such as SVV or PPV to guide fluid management. The use of GDT has been shown to improve outcomes in a range of surgical procedures, including high-risk surgery and major abdominal surgery. In the recently updated European Society of Cardiology (ESC) guidelines on cardiovascular assessment and management of patients undergoing non-cardiac surgery, perioperative goal-directed haemodynamic therapy in patients undergoing high-risk surgery received a Class IA recommendation. In addition, there is a strong recommendation (IB) to avoid an intraoperative decrease in MAP > 20% from baseline or below 60–70 mmHg to avoid perioperative complications .Although GDT protocols are well established in the adult population, there is a paucity of literature on their use in children. A study by Pereira de Souza Neto et al.  investigThe decision to use an arterial waveform analysis GDT protocol rather than pulse contour analysis or ultrasound analysis is based on several factors. First, arterial waveform analysis is a well-established and validated method for assessing fluid responsiveness and provides continuous and real-time feedback on haemodynamic changes. In contrast, echocardiographic analysis requires specialised training and may not be feasible in all clinical settings; it is typically performed at discrete time points and may not be able to detect acute changes in haemodynamic status. Non-invasive pulse contour analysis may be affected by factors such as hypothermia, vasoconstriction or centralisation of the circulation, which may alter the accuracy of the technique.The authors chose to implement a stroke-volume-based GDT protocol. Alternative SVV-based protocols can be problematic in clinical situations where there are changes in intrathoracic pressure, such as during scoliosis correction. This is because SVV is affected by changes in venous return and compliance, which can lead to misinterpretation and inappropriate fluid management decisions. Secondly, protocols based on cardiac output (CO) are more prone to variability due to changes in heart rate, which can lead to inaccurate measurements, making them less reliable.It is worth noting that the validation study of the HPI algorithm did not include hypotensive events caused by clinical interventions, such as laparoscopic insufflation, liver manipulation or vascular clamping .The algorithm requires a “clean” arterial waveform. A fast flush test should be performed at the beginning of each procedure to ensure that the waveform is acceptable.It is crucial to recognise that during scoliosis correction procedures, the anaesthetist should not blindly follow the conventional GDT protocol and should stay aware of its limitations during this type of surgery. This is due to the fact that there are moments during the procedure when the surgeon applies a significant amount of force, which can lead to thoracic compression and kinking of the arterial cannula. As a result, the arterial pressure waveform may change to a straight line, which the HPI software may interpret as hypotension. This can cause ambiguity as the typical response to hypotension is to initiate the GDT protocol. However, in the context of scoliosis correction procedures, it is essential to recognise that the appropriate action is to reduce the force exerted by the operator on the surgical instruments. By adjusting the level of force applied, it is possible to avoid hypotension and maintain haemodynamic stability in the patient. This approach is essential to ensure that patient outcomes are optimised and problems are avoided. Failure to adjust treatment plans in response to real-time physiological changes can lead to several adverse outcomes, including increased morbidity and mortality, prolonged hospital stays and increased procedural costs. Due to the complex and multifaceted nature of scoliosis correction, it is essential for the surgical team to remain vigilant and adaptable throughout the procedure. By closely monitoring the patient’s physiological responses and responding appropriately to changes in the haemodynamic profile, the surgical team can ensure that the patient receives the highest standard of care and achieves optimal outcomes.Despite the promising findings, there are several limitations to this study. Firstly, the study design was a prospective, single-centre, non-randomised, case–control study, which may limit the generalisability of the results. The lack of randomisation and inclusion of patients from a single centre introduce the possibility of selection bias and may not accurately represent the wider population of patients with adolescent idiopathic scoliosis undergoing posterior fusion. Also, the lack of blinding in the intervention group introduces the potential for performance bias, as clinicians were aware of the treatment they were giving. Finally, there is a concern that overfitted models will not replicate in future studies, which gives the impression of uncertainty about the scientific value of the discovery. Of course, this is also a possibility in this study, mainly due to the relatively small size of the study groups. However, the multiple comparisons made by the authors and the statistical power higher than acceptable in scientific research allow for the hope that the results will be reflected in groups of larger size and for other clinical diagnoses and, consequently, surgical procedures. Therefore, the authors recommend a degree of caution when interpreting the results of our study.Despite these limitations, this study provides valuable insights into the potential benefits of intraoperative haemodynamic monitoring and goal-directed therapy in patients with adolescent idiopathic scoliosis and warrants further investigation in larger, multicentre, randomised controlled trials.In conclusion, protocolised haemodynamic monitoring and fluid management have emerged as essential components of the paediatric ERAS protocol. Combined with intraoperative neuromonitoring, this approach has the potential to significantly reduce hospital stay, post-operative complications such as neurological injury, blood loss and wound infection. Recent studies have shown that the implementation of haemodynamic optimisation and ERAS protocols can lead to improved outcomes in high-risk surgical procedures, such as scoliosis surgery. The use of real-time haemodynamic monitoring and goal-directed therapy protocols can help ensure that patients receive individualised care tailored to their specific physiological needs.As research in this area continues, it is important to continue to evaluate and compare different haemodynamic monitoring and fluid management protocols to determine which approach is most effective in improving outcomes and reducing complications in paediatric surgical patients. Further studies are needed to refine the protocol and identify best practice guidelines for scoliosis surgery to optimise patient outcomes and reduce the healthcare burden associated with this complex procedure.In conclusion, the implementation of intraoperative haemodynamic monitoring, prediction of hypotension and goal-directed therapy in patients undergoing posterior fusion for adolescent idiopathic scoliosis confirmed shorter intraoperative hypotension time, reduced length of hospitalization and enhanced preservation of haemoglobin levels. Further studies and wider implementation of these strategies are warranted to fully assess their impact and establish their effectiveness as standard practice in this patient population.