Lactate Kinetics Research Articles

Resolving Differences between MLSS and CP by Considering Rates of Change of Blood Lactate during Endurance Exercise.

To develop a new method that more closely represents the heavy-to-severe exercise domain boundary by evaluating the rates of blood lactate accumulation during the constant power output exercise bouts that are employed in the assessment of the maximal lactate steady state (MLSS). Eight well-trained male cyclists completed five exercise tests of up to 30 min for determination of the traditional MLSS (MLSSTRAD) and a further four maximal tests for determination of critical power (CP). The rates of change of blood [lactate] between 10 min and the end of exercise in the MLSS tests were plotted against the corresponding power outputs and a two-segment linear regression model was used to identify individualised breakpoints in lactate accumulation vs. power output (MLSSMOD). MLSSMOD was significantly higher than MLSSTRAD (297 ± 41 vs. 278 ± 41 W; P < 0.001) but was not significantly different from CP (297 ± 41 W; P > 0.05); MLSSMOD and CP were closely aligned (r: 0.97; Bias: -0.52 W; SEE: 10 W; Limits of Agreement: -20 to 19 W). The rates of change of both blood [lactate] and V̇O2 were significantly greater, and exercise intolerance occurred before 30 min, at a power output slightly above MLSSMOD. A novel method for evaluating blood lactate kinetics during a traditional MLSS protocol produces a modified MLSS that is not different from CP and better represents the heavy-to-severe exercise domain boundary.

Modeling Glucose, Insulin, C-Peptide, and Lactate Interplay in Adolescents During an Oral Glucose Tolerance Test.

Lactate is not considered just a "waste product" of anaerobic glycolysis anymore. It has been proved to play a key role in several metabolic diseases, such as in the metabolic dysfunction-associated steatotic liver disease, obesity, and diabetes. The capability of simulating glucose-insulin-lactate interaction would be useful to design and test drugs targeting lactate metabolism in such pathological conditions. Minimal models are available, which describe and quantify glucose-lactate interaction but models to simulate postprandial glucose-insulin-C-peptide-lactate time courses are missing. The aim of this study is to fill this gap. Starting from the Padova Type 2 Diabetes Simulator (T2DS), we first added a description of glucose-lactate kinetics and then created a population of 100 in silico subjects to match glucose-insulin-C-peptide-lactate data of 44 adolescents with/without obesity who underwent a standard oral glucose tolerance test (OGTT) of 75 g. The developed model accurately predicts all molecules time courses, guaranteeing precise model parameter estimates (percent coefficient of variation [CV%] median [25th-75th percentile] = 19 [9-29]%). The generated in silico population shows good agreement with the clinical data in terms of area under the curve (AUC) (P = .6, .6, .9, .6 for glucose, insulin, C-peptide, and lactate, respectively) and parameter distributions (P > .1). We have developed a simulator to describe glucose, insulin, C-peptide, and lactate kinetics during an OGTT, which captures the behavior of a real population of adolescents with/without obesity both in terms of average and intersubject variability. Such simulator can be used to investigate the pharmacodynamics of drugs targeting lactate metabolic pathway in various pathological conditions.

Identifying physiological determinants of 800 m running performance using post-exercise blood lactate kinetics

PurposeThe aims of the present study were to investigate blood lactate kinetics following high intensity exercise and identify the physiological determinants of 800 m running performance.MethodsFourteen competitive 800 m runners performed two running tests. First, participants performed a multistage graded exercise test to determine physiological indicators related to endurance performance. Second, participants performed four to six 30-s high intensity running bouts to determine post-exercise blood lactate kinetics. Using a biexponential time function, lactate exchange ability (γ1), lactate removal ability (γ2), and the quantity of lactate accumulated (QLaA) were calculated from individual blood lactate recovery data.Results800 m running performance was significantly correlated with peak oxygen consumption (r = −0.794), γ1 and γ2 at 800 m race pace (r = −0.604 and −0.845, respectively), and QLaA at maximal running speed (r = −0.657). V˙\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\dot{\ ext{V}}}$$\\end{document}O2peak and γ2 at 800 m race pace explained 83% of the variance in 800 m running performance.ConclusionOur results indicate that (1) a high capacity to exchange and remove lactate, (2) a high capacity for short-term lactate accumulation and, (3) peak oxygen consumption, are critical elements of 800 m running performance. Accordingly, while lactate has primarily been utilized as a performance indicator for long-distance running, post-exercise lactate kinetics may also prove valuable as a performance determinant in middle-distance running.

Modelling and assessment of glucose-lactate kinetics in youth withoverweight, obesityand metabolic dysfunction-associated steatotic liver disease: A pilot study.

In this study, we investigated glucose and lactate kinetics during a 75 g oral glucose tolerance test (OGTT) in 23 overweight and obese adolescents and assessed putative differences among participants with and without metabolic dysfunction-associated steatotic liver disease (MASLD). We enrolled 23 young people (six girls) with obesity [body mass index 33 (29-37)]. Glucose-lactate kinetics parameters (disposal glucose insulin sensitivity, SID; fraction of glucose converted into lactate, fr; fractional lactate clearance rate, kL) and lactate production rate (LPR) were estimated using the oral glucose-lactate minimal model. MASLD presence was assessed using the proton density fat fraction. We analysed glucose, lactate and LPR time to peak, peak values and area under the curve and evaluated differences using the Wilcoxon test. MASLD and no-MASLD participants were compared using the Mann-Whitney test. Correlations between parameters were assessed using the Spearman correlation coefficient (ρ). We also tested the performance of two (4 or 3 h OGTT) protocols in estimating oral glucose-lactate minimal model and LPR parameters. Glucose peaks 30 min earlier than lactate (p = .0019). This pattern was present in the no-MASLD group (p < .001). LPR peaks 30 min later in the MASLD group (p = .02). LPR and kL were higher in MASLD, suggesting higher glycolysis and lactate utilization. SID and fr correlate significantly (ρ = -0.55, p = .008). SID and fr were also correlated with the body mass index, (ρ = -0.45, p = .04; and ρ = 0.45; p = .03). The protocol duration did not influence the estimates of the parameters. Youth with MASLD showed a delayed glucose metabolism, possibly because of greater utilization of the underlying substrates. A 3-h OGTT may be used to assess lactate metabolism effectively.

Association between early lactate-related variables and 6-month neurological outcome in out-of-hospital cardiac arrest patients

IntroductionThe role of lactate measurement in out-of-hospital cardiac arrest (OHCA) survivors remains controversial. We assessed the association between early lactate-related variables, OHCA characteristics, and long-term neurological outcome. MethodsIn OHCA patients who received targeted temperature management, lactate levels were measured at 0, 12, and 24 h after the return of spontaneous circulation. We calculated lactate clearance and time-weighted cumulative lactate (TWCL), which represent the area under the time-lactate curve. The area under the receiver operating characteristic curve (AUC) and the adjusted odds ratios (AORs) of lactate-related variables for predicting 6-month poor outcome (Cerebral Performance Category 3–5) were evaluated. Interactions between lactate variables and characteristics of OHCA were evaluated by a multivariable logistic model with interaction terms and subgroup analysis. ResultsA total of 347 OHCA patients were included. After adjustment, higher lactate levels at the three time points were associated with a poor outcome (AOR 1.10 [95% CI, 1.03–1.18], AOR 1.15 [95% CI, 1.02–1.29], and AOR 1.36 [95% CI, 1.15–1.60], respectively), while TWCL was the only lactate kinetics variable associated with a poor outcome (AOR 1.29 [95% CI, 1.12–1.49]). We identified several interactions between lactate-related variables and OHCA characteristics. In particular, the AUC of TWCL was excellent in cases of noncardiac etiology (AUC 0.92 [95% CI, 0.86–0.96] but only moderate in cardiac etiology (AUC 0.69 [95% CI, 0.62–0.75]). ConclusionsEarly lactate levels, especially at 24 h, and TWCL were independent predictors of neurologic outcome in these patients, whereas lactate clearance was not. The prognostic ability of lactate-related variables varied depending on the OHCA characteristics.

On a singular mathematical model for brain lactate kinetics

In this paper, we consider a singular nonlinear differential system that characterizes the intricate dynamics of brain lactate kinetics between cells and capillaries, as described by System (1.1) below. We begin by establishing the existence and uniqueness of nonnegative solutions for our system through the application of Schauder's fixed‐point theorem. Subsequently, we explore the behavior of these solutions as the viscosity term approaches zero, shedding light on the system's dynamic evolution in such scenarios. To provide empirical validation for our theoretical findings, we offer a series of numerical simulations. These simulations not only confirm the results we have obtained but also reinforce prior research, underscoring the model's efficiency in capturing the complexities of the brain's lactate kinetics. Our work contributes not only to the theoretical underpinning of this field but also to its practical implications, making it a valuable resource for both researchers and practitioners seeking to comprehend and manipulate these vital biological processes.

Hyperglycemia Suppresses Lactate Clearance During Exercise in Type 1 Diabetes.

Circulating lactate concentration is an important determinant of exercise tolerance. This work aimed to determine the role of hyperglycemia on lactate metabolism during exercise in individuals with type 1 diabetes (T1D). The protocol at the University of Virginia compared 7 T1D participants and 7 participants without diabetes (ND) at euglycemia (5.5 mM) or hyperglycemia (9.2 mM) in random order in T1D and at euglycemia in ND. Intervention included [1-13C] lactate infusion, exercise at 65% maximal oxygen uptake (VO2max), euglycemia, and hyperglycemia visits. The main outcome measure was lactate turnover before, during, and after 60 minutes of exercise at 65% VO2max. A 2-compartment model with loss only from the peripheral compartment described lactate kinetics. Volume of distribution of the accessible compartment was similar between T1D and ND individuals (P = .76) and concordant with plasma volume (∼40 mL/kg). Circulating lactate concentrations were higher (P < .001) in T1D participants during exercise at hyperglycemia than euglycemia. Exercise-induced lactate appearance did not differ (P = .13) between hyperglycemia and euglycemia. However, lactate clearance (CL) was lower (P = .03) during hyperglycemia than euglycemia in T1D participants. There were no differences in any of the aforementioned parameters between T1D and ND participants during euglycemia. Hyperglycemia modulates lactate metabolism during exercise by lowering CL, leading to higher circulating lactate concentrations in T1D individuals. This novel observation implies that exercise during hyperglycemia can lead to higher circulating lactate concentrations thus increasing the likelihood of reaching the lactate threshold sooner in T1D, and has high translational relevance both for providers and recreationally active people with T1D.

Using training impulse and monotony methods to monitor aerobic training load in rats.

This study is the first to apply training impulse (TRIMP) and Training Monotony (TM) methodologies, within the realm of sport science, in animal model studies. Rats were divided into Sedentary (SED, n=10) and Training (TR, n=13). TR performed a four-week moderate-intensity interval training with load progression. Lactate kinetics, lactate training impulse (TRIMPLac), maximal speed training impulse (TRIMPSmax) and TM were utilized to develop and monitor training protocol. TR showed an 11.9% increase in time to exhaustion at the second maximum incremental test and a 17.5% increase at the third test. External work was increased by 17.8% at the second test and 30.3% at the third. There was a 10.6% increase in external work at the third test compared to the second for TR. No difference in TRIMPLac between the 1st week (94±9 A.U) and 3rdweek (83±10 A.U) were seen. TRIMPSmax was 2400 A.U. in the 1st week, 2760 A.U. in the 2nd and 3rd weeks, and 3120 A.U. in the 4th week. The TM remained at 1.24 A.U throughout the protocol and there was no dropouts. TRIMPLac and TRIMPSmax contributed to the development and monitoring loads, demonstrating their potential to improve the accuracy of training protocols in animal model research.

Optimal control of therapies on a tumor growth model with brain lactate kinetics

Optimal control of therapies on a tumor growth model with brain lactate kinetics

The lactate response to a second bout of exercise is not reduced in a concurrent lower-limb exercise program

We aimed to evaluate the blood lactate level in response to two bouts of exercise. First, we hypothesized that blood lactate elevation in response to moderate-intensity aerobic exercise (MIAE) would be lower at the end of the second bout of MIAE than the first bout of MIAE. In this context, we also hypothesized that lactate accumulation at the end of resistance exercise (RE) would be reduced if MIAE is performed before RE (i.e., concurrent exercise; CE). If so, we hypothesized that the order of the CE (i.e., RE + MIAE vs. MIAE + RE) influences blood lactate kinetics. To test the hypotheses, forty-three healthy men participated in three studies. In study 1, 20 men (age 21 ± 2 years) performed two bouts of a 20-min MIAE separated by a 20-min rest interval. In study 2, 11 men (age 22 ± 1 years) performed RE only and CE (MIAE + RE; ARCE) with a 20-min rest interval in a crossover design. In study 3, 12 men (age 21 ± 2 years) performed both CEs, which were ARCE and RE + MIAE (RACE), with a 20-min rest interval in a crossover design. We measured blood lactate before and at the end of each exercise session. In study 1, the blood lactate response to the second bout of MIAE was lower than that of the first bout (P < 0.001, r = 0.68). However, the blood lactate response to the ARCE trial was not lower than the response to the RE trial in study 2 (P = 0.475, r = 0.22). The results of study 3 showed that the RACE and ARCE trials induced a similar lactate response (MIAE P = 0.423, r = 0.28; RE P = 0.766, d = 0.03). These observations indicate that whereas lactate accumulation might be diminished by a second bout of MIAE, a different type of exercise (i.e., aerobic/resistance) did not result in a diminished lactate accumulation in response to a second bout of exercise.

Optimal control of a model for brain lactate kinetics

The aim of this paper is to first study a Cahn-Hilliard model for brain lactate kinetics with a control function. This control allows for optimal treatment administered to ill patients suffering from glioma, in order to reduce their brain lactate concentrations, and thereby to slow down the tumor growth. We establish the well-posedness of the problem and the continuity of the control-to-state mapping, the existence of a minimizer of the objective functional, and its Fréchet differentiability in suitable Banach spaces with respect to the control and with respect to time. Moreover, we derive the first-order necessary conditions that an optimal control has to satisfy. In the second part of the paper, we illustrate our theoretical results with numerical simulations using MRI data from the University Hospital of Poitiers.

Moderate intensity active recovery improves performance in a second wingate test in cyclists

BackgroundThe aim of the present study was to compare the effects of active (AR) vs. passive recovery (PR) between two Wingate Anaerobic Tests (WAnT) on power output, blood lactate (BLa) and oxygen consumption (VO2) in a second WAnT. MethodsTwelve well-trained cyclists underwent three experimental sessions. In the first session, they completed an incremental test for maximum oxygen consumption (V O2max) and lactate threshold determination. In the second and third sessions, cyclists completed, in random order, two WAnT tests separated by 30-min recovery intervals, during which they performed an AR at 70% of the V O2 at lactate threshold (V O2LT) or a PR. The cardiorespiratory, metabolic, and mechanical responses in the two recovery conditions were compared. ResultsNo differences were found in the VO2-on kinetics between WAnT tests (p > 0.05). As expected, blood lactate kinetics showed a greater clearance (from the 7th to the 31st min, p < 0.001) during AR; however, no differences were found in peak BLa between conditions (p > 0.05). Mean and peak power, and total work were significantly higher in the second WAnT after AR (p < 0.001), while the power decline was also lower in this condition (p < 0.05). ConclusionThe submaximal active recovery strategy used in the present study can induce an improvement in mechanical power and total work during a second WAnT. This suggests that AR of submaximal intensity can induce a post-activation performance enhancement when used during the recovery phase between maximal anaerobic efforts.

585-P: Lactate Kinetics in Type 1 Diabetes—A 1-13C Lactate Study

Lactate kinetics in individuals with type 1 diabetes (T1D) has not been assessed quantitatively. Defining lactate kinetics in T1D under steady state condition is vital for estimating non-steady state lactate turnover. We studied 5 T1D and 7 nondiabetic (ND) anthropometrically matched participants during [1-13C]-sodium-lactate bolus injection in the resting, overnight fasted state. A two-compartment model with loss only from the peripheral compartment reliably described [1-13C]-lactate kinetics. Volume of distribution of the accessible compartment, V1, was similar between T1D and ND groups (40.32±21.08 vs. 47.64±33.32 mL/kg, p=0.76) thus concordant to plasma volume (~40 ml/kg). The irreversible loss from the peripheral compartment was impaired in T1D vs ND (0.08±0.03 vs. 0.13±0.03 min−1, p=0.03); rate of lactate appearance (12.4±5.2 vs. 18.5±9.6 µmol/kg/min, p=0.34), disappearance (12.7±5.2 vs. 18.8±9.7 µmol/kg/min, p=0.34) and lactate clearance (15.9±4.7 vs. 21.9±7.8 mL/kg/min, p=0.20) were numerically but not statistically lower in T1D vs. ND individuals. To conclude, we have defined lactate kinetics under resting, overnight fasted state in T1D and ND subjects. While the volume of distribution was similar in both groups, irreversible loss from the peripheral compartment was lower in T1D subjects. Further studies are needed to better define lactate kinetics during exercise in individuals with and without T1D. Disclosure D.Romeres: None. F.Ruchi: None. Y.Yadav: None. C.Cobelli: None. A.Basu: None. R.Basu: Consultant; Sparrow Pharmaceuticals Inc, Research Support; Abbott Diabetes, AstraZeneca. Funding National Institutes of Health (DK29953 to R.B.), (DK85516 to A.B.)

Can lactate levels and lactate kinetics predict mortality in patients with COVID-19 with using qCSI scoring system?

IntroductionIn this study, we aimed to investigate the relationship between blood lactate levels and lactate kinetics (lactate clearance and Δ lactate) for predicting mortality in patients with COVID-19 admitted to the emergency department. MethodsThis study was performed as a retrospective study that included patients admitted to the emergency department between March 1st, 2020, and January 1st, 2022. Lactate levels were recorded at the first admission (0 h lactate) and the highest blood lactate levels in the first 24 h of follow-up (2nd highest lactate). Lactate kinetics were calculated. Clinical severity was determined according to the quick COVID Severity Index (qCSI). Results300 patients were included in the study. Lactate levels at admission were similar in groups with or without mortality, but 2nd highest lactate levels were found to be significantly higher in the group with mortality (p < 0.001). Lactate clearance and ∆ lactate levels were also found to be lower in the mortality group (p < 0.001). Lactate kinetics in patients in the clinically low severity group were lower in the mortality group (p = 0.02 and p = 0.039, respectively). In the low-intermediate and high-intermediate groups, 0-h lactate and 2nd highest lactate levels were found to be higher in the mortality group, and lactate kinetics were similar in the groups with and without mortality. In the group with high clinical severity, 2nd highest lactate levels were found to be higher in the group with mortality (p = 0.010). Lactate kinetics were also found to be significantly lower in the mortality group (p < 0.001).In the high qCSI group, based on ROC analysis, the AUC for 2nd highest lactate levels predicting mortality was 0.642 (95% CI: 0.548–0.728). The optimal cut-off value for mortality was greater than >2.4 mmol/L (60.6% sensitivity, 67.4% specificity). The AUC for lactate clearance was 0.748 (95% CI: 0.659–0.824). The lactate clearance cut-off value was ≤ −177.78% (49.3% sensitivity, 100% specificity). The AUC for ∆ lactate was 0.707 (95% CI: 0.616–0.787). The optimal ∆ lactate cut-off was ≤ −2 mmol/L (45.1% sensitivity, 93.5% specificity). ConclusionIn COVID-19, 2nd highest blood lactate and lactate kinetics were found to be prognostic indicators of the disease. High 2nd highest lactate levels and low lactate kinetics in patients with high clinical severity were guiding physicians regarding the outcome of the disease.

The effect of acute heat exposure on the determination of exercise thresholds from ramp and step incremental exercise.

The aim of this study was to examine how respiratory (RT) and lactate thresholds (LT) are affected by acute heat exposure in the two most commonly used incremental exercise test protocols (RAMP and STEP) for functional evaluation of aerobic fitness, exercise prescription and monitoring training intensities. Eleven physically active male participants performed four incremental exercise tests, two RAMP (30W·min-1) and two STEP (40W·3min-1), both in 18°C (TEMP) and 36°C (HOT) with 40% relative humidity to determine 2 RT and 16 LT, respectively. Distinction was made within LT, taking into account the individual lactate kinetics (LTIND) and fixed value lactate concentrations (LTFIX). A decrease in mean power output (PO) was observed in HOT at LT (-6.2 ± 1.9%), more specific LTIND (-5.4 ± 1.4%) and LTFIX (-7.5 ± 2.4%), compared to TEMP, however not at RT (-1.0 ± 2.7%). The individual PO difference in HOT compared to TEMP over all threshold methods ranged from -53W to +26W. Mean heart rate (HR) did not differ in LT, while it was increased at RT in HOT (+10 ± 8bpm). This study showed that exercise thresholds were affected when ambient air temperature was increased. However, a considerable degree of variability in the sensitivity of the different threshold concepts to acute heat exposure was found and a large individual variation was noticed. Test design and procedures should be taken into account when interpreting exercise test outcomes.

Glucose-to-lactate ratio and neurodevelopment in infants with hypoxic-ischemic encephalopathy: an observational study

We aimed to assess the glucose and lactate kinetics during therapeutic hypothermia (TH) in infants with hypoxic-ischemic encephalopathy and its relationship with longitudinal neurodevelopment. We measured glucose and lactate concentrations before TH and on days 2 and 3 in infants with mild, moderate, and severe hypoxic-ischemic encephalopathy (HIE). Neurodevelopment was assessed at 2 years. Participants were grouped according to the neurodevelopmental outcome into favorable (FO) or unfavorable (UFO). Eighty-eight infants were evaluated at follow-up, 34 for the FO and 54 for the UFO group. Severe hypo- (< 2.6 mmol/L) and hyperglycemia (> 10 mmol/L) occurred in 18% and 36% from the FO and UFO groups, respectively. Glucose-to-lactate ratio on day 1 was the strongest predictor of unfavorable metabolic outcome (OR 3.27 pm 1.81, p = 0.032) when adjusted for other clinical and metabolic variables, including Sarnat score.Conclusion: Glucose-to-lactate ratio on day 1 may represent a new risk marker for infants with HIE undergoing TH.What is Known:• Glucose and lactate are key metabolic fuels during neonatal hypoglycemia. This suggests that their concentrations may influence the neurodevelopmental outcome of neonates experiencing hypoxic-hischemic encephalopathy (HIE).What is New:• We describe the relative availbility of glucose and lactate before and during theraputic hypothermia in neonates with HIE.

New potential for an old kid on the block: Impact of premorbid metformin use on lactate kinetics, kidney injury and mortality in sepsis and septic shock, an observational study.

Sepsis and septic shock cause significant mortality worldwide, with no targeted molecular therapies available. Metformin has pleomorphic effects that may be beneficial in sepsis, but at present, the impact of metformin exposure on sepsis remains controversial. Metformin might alter lactate metabolism, but little is known about its influence on lactate kinetics. We therefore investigated the impact of preadmission metformin use on lactate kinetics, acute kidney injury (AKI) and mortality in sepsis. We retrospectively analysed all ICU admissions with sepsis and septic shock between January 2013 and September 2020, identifying 77 users and 390 nonusers (subdivided in diabetics, n= 48 and nondiabetics, n= 342). (Sub)groups did not differ in illness severity or sepsis aetiology. Admission lactate levels were similar, but evolution in lactate over the first 24 h showed a larger decrease in users vs nonusers (median - 53% vs. -36%, p= .010). No difference in AKI or renal replacement therapy was found. Mortality was lower in users vs nonusers in case of septic shock (21.9% (n= 7) vs. 42.7% (n= 61) for 90d mortality, p= .029, OR 0.38 [95% CI: 0.15-0.93]), but showed no significant differences in the combined sepsis and septic shock population. In our data, preadmission metformin use is associated with a significantly larger decrease in lactate after admission with sepsis or septic shock and with reduced mortality in septic shock. This underscores the need for further studies investigating the interplay between metformin, lactate and sepsis, thereby exploring the potential use of metformin or its pathways in sepsis.

Comparison of Stroke Volume Variation-based goal-directed Therapy Versus Standard Fluid Therapy in Patients Undergoing Head and Neck Surgery: A Randomized Controlled Study

Background:Perioperative fluid therapy is used to avoid dehydration and hypovolemia. Optimum perioperative fluid administration may improve postoperative outcomes after major surgery, and the optimal strategy remains controversial and uncertain.Aims:The primary outcome was the total amount of intraoperative fluids given between perioperative goal-directed fluid therapy (GDFT) guided by a hemodynamic monitoring system and standard fluid therapy based on “mean arterial pressure-diuresis” data in patients undergoing head and neck surgery. The secondary outcomes were the hemodynamics and laboratory variables, postoperative complications, length of mechanical ventilation, intensive care unit and hospital stay.Study Design:A randomized controlled study.Methods:Sixty patients were scheduled and randomized into two groups of 30 patients each: in the study group, an arterial pressure catheter was inserted and connected to the FloTrac system, whereas in the control group, an arterial pressure catheter was inserted and integrated into the hemodynamic monitoring system with a special transducer. The control group had fluids administered at the discretion of the anesthesiologist according to the mean arterial pressure >65 mmHg and diuresis >0.5 ml/kg/h. In the study group, fluid management was administered to achieve a target value of ≤13% through the stroke volume variation.Results:The total amounts of fluid in the intraoperative period were different between the groups, with the study group receiving significantly more fluids (P = 0.0455). The length of hospital stay was significantly longer in the study group than in the control group (P = 0.012), but prolonged oxygen demand was significantly more frequent in the control group than in the study group (P = 0.017). No difference was found in hemodynamics, lactate kinetics, and vasoactive agent requirements.Conclusion:The standard fluid therapy guided by conventional circulatory parameters appears sufficient for patients with low-to-moderate risk during head and neck surgery.

On a tumor growth model with brain lactate kinetics.

Our aim in this paper is to study a mathematical model for high grade gliomas, taking into account lactates kinetics, as well as chemotherapy and antiangiogenic treatment. In particular, we prove the existence and uniqueness of biologically relevant solutions. We also perform numerical simulations based on different therapeutical situations that can be found in the literature. These simulations are consistent with what is expected in these situations.

Study of Significance of Serum Lactate Kinetics in Sepsis as Mortality Predictor.

IntroductionSepsis is one of the leading causes of death worldwide. Serum lactate is being used in sepsis for diagnostic and prognostic purposes for years now. In this study, we shed light over a novel use of lactate in form of various clearance parameters to determine mortality in septic patients at the 28th day.Materials and methodsIn our study, 200 patients with sepsis were included using quick sequential organ failure assessment (qSOFA) score and their lactate levels were measured at the time of admission (0 hour) and 24 hours after admission. Lactate clearance parameters (absolute and relative lactate clearance, lactate clearance rate) were calculated. All patients were followed up for a period of 28 days to determine the outcome, and data analysis was done accordingly.Results and conclusionOur study showed that higher SOFA score, qSOFA score, and serum lactate levels were associated with increased 28th-day mortality. Low absolute, relative lactate clearance and lactate clearance rate were also associated with poor outcomes. The best cutoffs to predict poor outcomes were serum lactate level at 24 hours ≥4 mmol/L and relative lactate clearance ≤40.3% with good sensitivity and specificity.How to cite this articleChaudhari M, Agarwal N. Study of Significance of Serum Lactate Kinetics in Sepsis as Mortality Predictor. Indian J Crit Care Med 2022;26(5):591–595.