Total Deviation Index Research Articles

Noninvasive Method Using Mechanical Extensometer for the Estimation of Intracranial Compliance by Repeated Measures Agreement Analysis.

Intracranial compliance refers to the relationship between changes in volume and the resultant changes in intracranial pressure (ICP). This study aimed to assess the agreement of a noninvasive ICP waveform device for the estimation of compliance compared with invasive ICP monitoring employing three distinct methods. We conducted a retrospective analysis of ICP waveform morphology recorded through both invasive (external ventricular drain) and noninvasive (mechanical extensometer) methods in adult patients with acute brain injury admitted to a neurointensive care unit between August 2021 and August 2022. Compliance was calculated as the amplitude of the fundamental component of cerebral arterial blood volume (estimated with concurrent Transcranial Doppler [TCD] recordings), divided by the amplitude of the fundamental component of the invasive and noninvasive ICP waveforms. Subsequently, we assessed the agreement between invasive and noninvasive intracranial compliance by repeated measures correlation coefficient analysis using three methods: TCD-derived, P2/P1 ratio, and time-to-peak (TTP). A linear mixed-effects model was used to compute the concordance correlation coefficient, total deviation index, and coefficient of individual agreement. Coverage probability plot was calculated to estimate the percent of observations within different cut points for each of the three methods. A total of 21 patients were identified for this study. Repeated measures correlation analysis showed a strong correlation (R = 0.982, 95% confidence interval [0.980-0.984], p < 0.0001) between log-transformed noninvasive and invasive compliance. Agreement statistics for TCD, P2/P1 ratio, and TTP indicated that although the concordance correlation coefficient was highest for log(TCD) values, TTP and P2:P1 ratio measures had better agreement with total deviation index and coverage probability plot analyses. Repeated measures correlations suggest that ICP waveform analyses may offer a more accurate estimate of compliance than TCD-derived methods for noninvasive ICP monitoring. Further validations studies are warranted to confidently establish this method as an indicator of intracranial compliance.

An improved particle swarm optimisation algorithm for optimum placement and sizing of biogas-fuelled distributed generators for seasonal loads in a radial distribution network

Optimal allocation is critical for effective planning and operation of grid connected distributed generator(s) (DGs) subject to efficient optimisation approach(es). In this paper, an improved particle swarm optimisation (IPSO) algorithm based on weighted randomised acceleration coefficients and adaptive inertia weight for dynamic movement of the particles towards an optimal solution is proposed. The technique is expected to determine optimal placement, sizing and power factor of biogas-fuelled distributed generators (B-DGs such as internal combustion engine (ICE) and fuel cells (FC)) in a radial distribution network. The proposed IPSO is applied to simultaneously optimise three technical objectives namely total active power loss (TAPL), voltage deviation (VD) and voltage stability index (VSI) considering load growth and seasonal voltage dependence. The proposed IPSO is validated using an IEEE 33 bus radial distribution network to evaluate its effectiveness through various combinations of B-DGs for different scenarios and cases with a maximum of 3 B-DGs. Some of the key findings indicate that operating 3 ICEs at optimal power factor reduces TAPL by 93.52 %, reduces VD by 99.62 % and improves VSI by 23.32 % compared to 61.80 % TAPL reduction, 94.77 % VD reduction and 17.89 % VSI improvement for 3 FCs operating at unity power factor. The proposed IPSO gives better results than the standard PSO in terms of solution quality, convergence speed and statistical results. It is also perceived to be better compared to most of the recent state-of-the-art optimization algorithms found in literature.

GFR measurement in patients with CKD: Performance and feasibility of simplified iohexol plasma clearance techniques.

Implementing shortened one-compartment iohexol plasma clearance models for GFR measurement is crucial since the gold standard inulin renal clearance technique and the reference two-compartment, 10-hour, 16-samplings iohexol plasma clearance method are clinically unfeasible. Inulin may precipitate anaphylactic shock. Four-hour and 8-hour one-compartment iohexol plasma clearance models with Bröchner-Mortensen correction provide accurate GFR measurements in patients with estimated GFR (eGFR) > or ≤40 mL/min/1.73m2, respectively. We compared the performance of the simplified 5-hour, 4-samplings, two-compartment population pharmacokinetic model (popPK) with the performance of the reference two-compartment 10-hour iohexol method in 16 patients with GFR 15.2 to 56.5 mL/min/1.73 m2. We also compared the performance of shortened (5, 6 and 7-hour) one-compartment models with the performance of the standard 8-hour one-compartment model in 101 patients with eGFR ≤40 mL/min/1.73 m2. The performance of popPK and shortened methods versus reference methods was evaluated by total deviation index (TDI), concordance correlation coefficient (CCC) and coverage probability (CP). TDI <10%, CCC ≥0.9 and CP >90% indicated adequate performance. TDI, CCC and CP of popPK were 11.11%, 0.809 and 54.10%, respectively. All shortened, one-compartment models overestimated the GFR (p <0.0001 for all) as compared to the 8-hour model. TDI, CCC and CP were 7.02%, 0.815, and 75.80% for the 7-hour model, 7.26%, 0.803, and 74.20% for the 6-hour model, and 8.85%, 0.729 and 64.70% for the 5-hour model. The agreement of popPK model was comparable to that obtained with the Chronic-Kidney-Disease-Collaboration-Epidemiology (CKD-Epi) and the Modification-of-Diet-in-Renal-Disease (MDRD) serum-creatinine based equations for GFR estimation. PopPK model is remarkably unreliable for GFR measurement in stage III-IV CKD patients. In patients with eGFR ≤40 mL/min/1.73m2, shortened one-compartment models, in particular the 5-hour model, are less performant than the reference 8-hour model. For accurate GFR measurements, the iohexol plasma clearance should be measured with appropriate protocols. Over-simplified procedures should be avoided.

Comprehensive benchmarking of CNN-based tumor segmentation methods using multimodal MRI data

Magnetic resonance imaging (MRI) has become an essential and a frontline technique in the detection of brain tumor. However, segmenting tumors manually from scans is laborious and time-consuming. This has led to an increasing trend towards fully automated methods for precise tumor segmentation in MRI scans. Accurate tumor segmentation is crucial for improved diagnosis, treatment, and prognosis. This study benchmarks and evaluates four widely used CNN-based methods for brain tumor segmentation CaPTk, 2DVNet, EnsembleUNets, and ResNet50. Using 1251 multimodal MRI scans from the BraTS2021 dataset, we compared the performance of these methods against a reference dataset of segmented images assisted by radiologists. This comparison was conducted using segmented images directly and further by radiomic features extracted from the segmented images using pyRadiomics. Performance was assessed using the Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD). EnsembleUNets excelled, achieving a DSC of 0.93 and an HD of 18, outperforming the other methods. Further comparative analysis of radiomic features confirmed EnsembleUNets as the most precise segmentation method, surpassing other methods. EnsembleUNets recorded a Concordance Correlation Coefficient (CCC) of 0.79, a Total Deviation Index (TDI) of 1.14, and a Root Mean Square Error (RMSE) of 0.53, underscoring its superior performance. We also performed validation on an independent dataset of 611 samples (UPENN-GBM), which further supported the accuracy of EnsembleUNets, with a DSC of 0.85 and an HD of 17.5. These findings provide valuable insight into the efficacy of EnsembleUNets, supporting informed decisions for accurate brain tumor segmentation.

Comparison of semi-automatic and manual segmentation methods for tumor delineation on head and neck squamous cell carcinoma (HNSCC) positron emission tomography (PET) images

Objective. Accurate and reproducible tumor delineation on positron emission tomography (PET) images is required to validate predictive and prognostic models based on PET radiomic features. Manual segmentation of tumors is time-consuming whereas semi-automatic methods are easily implementable and inexpensive. This study assessed the reliability of semi-automatic segmentation methods over manual segmentation for tumor delineation in head and neck squamous cell carcinoma (HNSCC) PET images. Approach. We employed manual and six semi-automatic segmentation methods (just enough interaction (JEI), watershed, grow from seeds (GfS), flood filling (FF), 30% SUVmax and 40%SUVmax threshold) using 3D slicer software to extract 128 radiomic features from FDG-PET images of 100 HNSCC patients independently by three operators. We assessed the distributional properties of all features and considered 92 log-transformed features for subsequent analysis. For each paired comparison of a feature, we fitted a separate linear mixed effect model using the method (two levels; manual versus one semi-automatic method) as a fixed effect and the subject and the operator as the random effects. We estimated different statistics—the intraclass correlation coefficient agreement (aICC), limits of agreement (LoA), total deviation index (TDI), coverage probability (CP) and coefficient of individual agreement (CIA)—to evaluate the agreement between the manual and semi-automatic methods. Main results. Accounting for all statistics across 92 features, the JEI method consistently demonstrated acceptable agreement with the manual method, with median values of aICC = 0.86, TDI = 0.94, CP = 0.66, and CIA = 0.91. Significance. This study demonstrated that JEI method is a reliable semi-automatic method for tumor delineation on HNSCC PET images.

Ectasia Detection by Anterior Segment Optical Coherence Tomography in Scheimpflug Tomographically Normal Keratoconus Fellow Eyes.

The purpose of this study was to determine whether the Scheimpflug tomographically normal fellow eyes of keratoconus patients are also classified as normal using an ectasia screening algorithm based on anterior segment optical coherence tomography (AS-OCT). This monocentric cross-sectional study included 22 very asymmetric ectasia patients with tomographically significant keratoconus in 1 eye and normal Scheimpflug tomography in the fellow eye. Twenty-two eyes of 22 healthy subjects served as a control group. We performed corneal tomography using Pentacam AXL (Oculus, Wetzlar, Germany) and used Belin/Ambrósio Enhanced Ectasia total deviation index as well as Belin ABCD keratoconus classification to identify Scheimpflug tomographically normal eyes. We also performed AS-OCT using Anterion (Heidelberg Engineering, Heidelberg, Germany) and analyzed for the presence of ectasia using the Screening Corneal Objective Risk of Ectasia (SCORE) algorithm, with positive values indicating ectasia suspect tomography. The SCORE value was positive in 9.1% (n = 2) of the healthy eyes, in 45.5% (n = 10) of the Scheimpflug tomographically normal eyes of keratoconus patients and in all eyes (n = 22) with tomographically significant keratoconus. The Scheimpflug tomographically normal eyes of keratoconus patients had higher SCORE values compared with healthy controls ( P < 0.001). The median (interquartile range) SCORE value was -1.7 (1.3) in healthy controls, -0.5 (2.2) in Scheimpflug tomographically normal eyes of keratoconus patients, and 11.1 (11.0) in tomographically significant keratoconus eyes. The Scheimpflug tomographically normal fellow eyes of keratoconus patients had higher AS-OCT-based SCORE values than healthy controls, with positive SCORE values found in 46% of the eyes, indicating early tomographic ectatic changes.

The error of estimated GFR in predialysis care

The error of estimated glomerular filtration rate (eGFR) and its consequences in predialysis are unknown. In this prospective multicentre study, 315 predialysis patients underwent measured GFR (mGFR) by the clearance of iohexol and eGFR by 52 formulas. Agreement between eGFR and mGFR was evaluated by concordance correlation coefficient (CCC), total deviation index (TDI) and coverage probability (CP). In a sub-analysis we assessed the impact of eGFR error on decision-making as (i) initiating dialysis, (ii) preparation for renal replacement therapy (RRT) and (iii) continuing clinical follow-up. For this sub-analysis, patients who started RRT due to clinical indications (uremia, fluid overload, etc.) were excluded. eGFR had scarce precision and accuracy in reflecting mGFR (average CCC 0.6, TDI 70% and cp 22%) both in creatinine- and cystatin-based formulas. Variations -larger than 10 ml/min- between mGFR and eGFR were frequent. The error of formulas would have suggested (a) premature preparation for RTT in 14% of stable patients evaluated by mGFR; (b) to continue clinical follow-up in 59% of subjects with indication for RTT preparation due to low GFRm and (c) to delay dialysis in all asymptomatic patients (n = 6) in whom RRT was indicated based on very low mGFR. The error of formulas in predialysis was frequent and large and may have consequences in clinical care.

Dynamic fuzzy learning based hybrid GWO-CSA for optimal planning of PV, BESS and DSTATCOM with network reconfiguration

The proposed approach is on the optimal planning issue of photovoltaic distributed generation (PV-DG) and DSTATCOM device with integrated battery energy storage systems (BESS) considering network reconfiguration by applying hybrid Grey-Wolf crow-search algorithm (GWO-CSA) encompassing dynamic fuzzy learning (DFL) optimization technique. Considering the stochastic nature of solar irradiance and variations, when solar energy is inadequate, BESS acts as backup energy storage device to meet essential load requirements. Network reconfiguration is to reduce power loss by changing the network tie switches using optimization algorithm. The principal objective of the proposed research work is to reduce the total power loss, enhance the voltage profile, improve the voltage stability index, and perform network reliability analysis. The beneficial effect of the proposed method is validated on Standard IEEE 69 and Standard 118 bus systems. It found that for the IEEE 69 bus system, the overall Real power loss values decreased to 12.82% and overall Reactive power loss increased to 78.18%. The total voltage deviation index (TTVDI), and total voltage stability index (TTVSI) values decreased to 17.94% and − 0.75% respectively. The reliability indices like SAIDI, SAIFI, CAIDI, CAIFI, and AENS values decreased by 56%, 3.54%, − 3.09%, 0.55% and 30% respectively. Similarly, for IEEE 118 bus system overall Real power loss, overall Reactive power loss, TTVDI, and TTVSI decreased to 9.53%, − 0.11%, 24.64%, and 3.87%. The reliability indices like SAIDI, SAIFI, CAIDI, CAIFI, and AENS values decreased by 2.4%, 1.0%, 1.54%, 0.94%, and 10.1% respectively. Further, the proposed approach of DFL-based hybrid GWO-CSA considers the reconfiguration with PV-DG, DSTATCOM and BESS enhances the overall performance compared to other scenarios.

Glomerular filtration rate measurement during platinum treatment for urothelial carcinoma: optimal methods for clinical practice

BackgroundWe assessed the accuracy of four estimated glomerular filtration rate (eGFR) methods: MDRD, Cockcroft–Gault, CKD-EPI, and Wright.MethodThe four methods were compared to measure GFR (mGFR) in patients with urothelial urinary tract cancer (T2-T4bNxMx) receiving platinum-based chemotherapy at Rigshospitalet, Copenhagen, from January 2019 to December 2021. Using standardized assays, creatinine values were measured, and mGFR was determined using Technetium-99 m diethylenetriaminepentaacetic acid (Tc-99 m-DTPA) or Cr-51-ethylenediaminetetraacetic acid (Cr-51-EDTA) plasma clearance. Patients (n = 146) with both mGFR and corresponding creatinine values available were included (n = 345 measurements).ResultsThe CKD-EPI method consistently demonstrated superior accuracy, with the lowest Total Deviation Index of 21.8% at baseline and 22.9% for all measurements compared to Wright (23.4% /24.1%), MDRD (26.2%/25.5%), and Cockcroft–Gault (25.x%/25.1%). Bland Altman Limits of agreement (LOA) ranged from − 32 ml/min (Cockcroft–Gault) to + 33 ml/min (MDRD), with CKD-EPI showing the narrowest LOA (− 27 ml/min to + 24 ml/min and lowest bias (0.3 ml/min). Establishing an eGFR threshold at 85 ml/min—considering both the lower limit of agreement (LOA) and the minimum cisplatin limit at 60 ml/min—allows for the safe omission of mGFR in 30% of patients in this cohort.ConclusionCKD-EPI equation emerged as the most suitable for estimating kidney function in this patient group although not meeting benchmark criteria. We recommend its use for initial assessment and ongoing monitoring, and suggest mGFR for patients with a CKD-EPI estimated GFR below 85 ml/min. This approach could reduce costs and decrease laboratory time for 30% of our UC patients.

Longitudinal Evaluation of Biomechanical Indices in Fellow Eyes of Patients With Keratoconus Classified as Having Very Asymmetric Ectasia With Normal Topography.

To evaluate the biomechanical longitudinal variability and progression of tomographically normal fellow eyes of patients with keratoconus. Of 513 patients with keratoconus, 30 patients with tomographically normal fellow eyes were included in this study. Tomographic and biomechanical parameters of the Pentacam and Corvis ST (Oculus Optikgeräte GmbH) were analyzed in multiple follow-up examinations, including the ABCD grading, Belin/Ambrósio Enhanced Ectasia total deviation index (BAD-D), Corvis Biomechanical Index (CBI), Corvis Biomechanical Factor (CBiF), and Tomographic and Biomechanical Index (TBI). A mixed regression model was applied. The results were compared to a healthy control group (n = 17) and a keratoconus group (n = 20). Within a maximum observation period of 3.3 years, no fellow eye (0%) showed a progression to tomographically evident keratoconus. No significant change in tomographic or biomechanical parameters was detected over the study period. The indices BAD-D, CBI, CbiF, and TBI exhibited a certain variability over time, whereas the tomographic ABC parameters and maximum keratometry barely changed. This was also shown in the control group and for all parameters in the keratoconus group, except the TBI. During the observation period none of the normal fellow eyes progressed to tomographically detectable keratoconus. However, biomechanical parameters CBI, CbiF, and TBI showed pathological values in 43.3% of eyes and certain variability. Subsequent studies with a longer observation period are warranted to confirm the biomechanical trends seen in this study and to rate the ability of single measurements to diagnose early keratoconus. [J Refract Surg. 2024;40(1):e48-e56.].

Interlaboratory comparison of Pseudomonas aeruginosa phage susceptibility testing.

Standardized approaches to phage susceptibility testing (PST) are essential to inform selection of phages for study in patients with bacterial infections. There is no reference standard for assessing bacterial susceptibility to phage. We compared agreement between PST performed at three centers: two centers using a liquid assay standardized between the sites with the third, a plaque assay. Four Pseudomonas aeruginosa phages: PaWRA01ø11 (EPa11), PaWRA01ø39 (EPa39), PaWRA02ø83 (EPa83), PaWRA02ø87 (EPa87), and a cocktail of all four phages were tested against 145 P. aeruginosa isolates. Comparisons were made within measurements at the two sites performing the liquid assay and between these two sites. Agreement was assessed based on coverage probability (CP8), total deviation index, concordance correlation coefficient (CCC), measurement accuracy, and precision. For the liquid assay, there was satisfactory agreement among triplicate measurements made on different days at site 1, and high agreement based on accuracy and precision between duplicate measurements made on the same run at site 2. There was fair accuracy between measurements of the two sites performing the liquid assay, with CCCs below 0.6 for all phages tested. When compared to the plaque assay (performed once at site 3), there was less agreement between results of the liquid and plaque assays than between the two sites performing the liquid assay. Similar findings to the larger group were noted in the subset of 46 P. aeruginosa isolates from cystic fibrosis. Results of this study suggest that reproducibility of PST methods needs further development.

Efficacy of Smoothing Algorithms to Enhance Detection of Visual Field Progression in Glaucoma

To evaluate and compare the effectiveness of nearest neighbor (NN)- and variational autoencoder (VAE)-smoothing algorithms to reduce variability and enhance the performance of glaucoma visual field (VF) progression models. Longitudinal cohort study. 7150 eyes (4232 patients), with ≥ 5 years of follow-up and ≥ 6 visits. Vsual fieldthresholds were smoothed with the NN and VAE algorithms. The mean total deviation (mTD) and VF index rates, pointwise linear regression (PLR), permutation of PLR (PoPLR), and the glaucoma rate index were applied to the unsmoothed and smoothed data. The proportion of progressing eyes and the conversion to progression were compared between the smoothed and unsmoothed data. A simulation series of noiseless VFs with various patterns of glaucoma damage was used to evaluate the specificity of the smoothing models. The mean values of age and follow-up time were 62.8 (standard deviation: 12.6) years and 10.4 (standard deviation: 4.7) years, respectively. The proportion of progression was significantly higher for the NN and VAE smoothed data compared with the unsmoothed data. VF progression occurred significantly earlier with both smoothed data compared with unsmoothed data based on mTD rates, PLR, and PoPLR methods. The ability to detect the progressing eyes was similar for the unsmoothed and smoothed data in the simulation data. Smoothing VF data with NN and VAE algorithms improves the signal-to-noise ratio for detection of change, results in earlier detection of VF progression, and could help monitor glaucoma progression more effectively in the clinical setting. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Keratometric Study of Cornea in Allergic Conjunctivitis Patients

Background: To explore corneal biomechanical changes, identify related factors and determine early indicators of keratoconus (KC) development risk in allergic conjunctivitis (AC) patients. Methods: A total of 50 patients, including 20 eyes without AC and 30 eyes with AC were enrolled in this study. All patients underwent a complete ocular examination, including evaluations of clinical manifestations of AC, corneal tomography and densitometry by Pentacam, corneal biomechanics by Corvis ST, and corneal and epithelial thickness mapping by RTvue optical coherence tomography (OCT). Results: The index of surface variance (ISV), index of vertical asymmetry (IVA), keratoconus index (KI), index of height decentration (IHD) and Belin/Ambrosio enhanced ectasia total deviation index (BAD-D) were significantly higher in the AC group than in the non-allergic conjunctivitis (NAC) group (P &lt; 0.05). The tomography and biomechanical index (TBI) was also significantly higher in the AC group (P =?0.04). The average epithelial thickness in the 2–7?mm annulus was significantly thinner in the AC group than in the NAC group (P &lt; 0.05). The average densitometry of the total cornea and the anterior layer were higher in the AC group than in the NAC group (P &lt; 0.001). The ISV, IVA, KI, IHD and BAD-D were significantly correlated with the TBI and changes in corneal epithelial thickness in AC patients (P &lt; 0.05). The changes in epithelial thickness were closely related to the eye rubbing frequency and allergic sign scores (P &lt; 0.05). CONCLUSIONS: AC patients should be advised to routinely undergo corneal tomographic and biochemical measurements and the TBI could be used an indicator of KC devolopment risk in AC patients.

A Proposed Predictive Equation for Energy Expenditure Estimation Among Noncritically Ill Patients With Acute Kidney Injury

The incidence of acute kidney injury (AKI) is identified more frequently in noncritical compared with intensive care settings. The prognosis of malnourished AKI patients is far worse than those with normal nutritional status. However, a method for estimating the optimal amount of energy required to guide nutritional support among noncritically ill AKI patients is yet to be determined. We evaluated the performance of weight-based formulas (20-30kcal/kg/day) with the reference values of energy expenditure (EE) measured by indirect calorimetry (IC) among noncritically ill AKI patients during hospitalization. The statistics for assessing agreement, including total deviation index and accuracy within 10% represent the percentage of estimations falling within the IC value range of ±10%, were tested. Parameters for predicting the EE equation were also developed using a regression analysis model. A total of 40 noncritically ill AKI patients were recruited. The mean age of participants was 62.5±16.5years with 50% being male. The average IC-derived EE was 1,124.6±278.9kcal/day with respiratory quotients 0.8-1.3, indicating good validity of the IC test. Receiving dialysis, protein catabolic rate, and age was not significantly associated with measured EE. Nearly all weight-based formulas overestimated measured EE. The magnitude of total deviation index values was broad with the proportion of patients achieving an accuracy of 10% being as low as 20%. The proposed equation to predict EE derived from this study was EE (kcal/day)=618.27+(8.98 x weight in kg)+137.0 if diabetes - 199.7 if female (r2=0.68, P<.001). In the validation study with an independent group of noncritically ill AKI patients, predicted EE using the newly derived equation was also significantly correlated with measured EE by IC (r=0.69, P=.004). Estimation of EE by weight-based formulas usually overestimated measured EE among noncritically ill AKI patients. In the absence of IC, the proposed predictive equation, specifically for noncritically ill AKI patients might be useful, in addition to weight-based formulas, for guiding caloric dosing in clinical practice.

Spherical Aberration of Astigmatic Corneas in a Cataract Population.

To study the distribution of spherical aberration (SA) in astigmatic corneas in a cataract population and the relationship between magnitude of corneal astigmatism and fourth-order corneal SA. Data routinely collected using a Scheimpflug camera (Pentacam; Oculus Optikgeräte GmbH) were retrospectively analyzed. Patients with a minimum age of 60 years were included. Total corneal SA (from anterior and posterior corneal surface) was obtained for a 6-mm cor-neal area aligned with the pupil center. Exclusion criteria were insufficient measurement quality, total deviation index (Belin/Ambrósio Deviation) greater than 1.60, and corneal thickness at the thinnest point of less than 490 μm. One eye per patient was chosen randomly. Eyes were divided into low (≤ 1.00 diopters [D]), moderate (> 1.00 to ≤ 2.00 D), and high (> 2.00 D) astigmatism groups according to the Scheimpflug measurements. A total of 528 eyes were included in this analysis. Low astigmatism was found in 129 patients, moderate astigmatism in 265 patients, and high astigmatism in 134 patients. Mean astigmatism was 0.68 ± 0.24, 1.45 ± 0.28, and 2.91 ± 0.95 D in the low, moderate, and high astigmatism groups, respectively. Mean corneal SA in patients with moderate and high astigmatism was higher than in the low astigmatism group. The difference reached the significance level for the comparison of low and high astigmatism groups (P = .023). The fourth-order SA increased gradually with the magnitude of astigmatism with a slope of 0.015. SA was significantly larger in the cataract population with high corneal astigmatism. The increase of positive sign SA with the magnitude of astigmatism suggests that patients with moderate to high astigmatism may benefit more from intraocular lenses with negative sign SA correction. [J Refract Surg. 2023;39(8):532-538.].

#3568 THE ERROR OF ESTIMATED GFR IN PREDIALYSIS CARE: IMPACT ON CLINICAL DECISION MAKING

Abstract Background and Aims The error of estimated glomerular filtration rate (eGFR) and its consequences in predialysis are unknown. Method We analysed 315 predialysis patients who underwent measured GFR (mGFR) by the clearance of iohexol and eGFR by 52 formulas. We evaluated the agreement between eGFR and mGFR by the concordance correlation coefficient (CCC), total deviation index (TDI) and coverage probability (CP). In a sub-analysis we investigated the impact of the error of eGFR in decisions like (i) starting dialysis, (ii) preparation for renal replacement therapy (RRT) and (iii) continuing with clinical follow-up. For this sub-analysis patients who started dialysis due to uremia or fluid overload were excluded (n = 18). Results Patients: 315 patients were included, 70% male and mean age was 66±13 years. 38% had diabetic nephropathy. Mean mGFRwas 22 ± 8 ml/min. Mean eGFR was 22 ± 8 ml/min (CKD-EPI), 22 ± 8 ml/min (MDRD) or 26 ±10 ml/min (24-h creatinine clearance). Cystatin C measurement was available in 266 patients (84%) and averaged 2.8 ± 1.08 mg/L. Over 70% of the patients had proteinuria 1588±2204 mg/24 h. Agreement between eGFR and mGFR eGFR had very low precision and accuracy in reflecting mGFR as reflected by average CCC, TDI and cp of 0.60, 70% and 22%, respectively. The error was comparable between creatinine- and cystatin-based formulas. Extreme variations -larger than 10 ml/min- between mGFR and eGFR were frequent. Differences in clinical decision making: Concerning clinical decisions, the error of formulas (mainly GFR overestimation) would have suggested (a) early unnecessary preparation for RTT in 14% of clinically stable patients evaluated by mGFR; (b) to continue with clinical follow-up in 59% of the subjects in whom RTT was indicated by low mGF and (c) to delay the starting of dialysis in all patients (n = 6) in whom RRT was indicated based on very low mGFR without uremic symptoms or fluid overload. Conclusion The error of formulas in predialysis care was frequent and large and may have consequences in clinical care.

Validation of a Non-Invasive Method Using Mechanical Extensometer for the Estimation of Intracranial Compliance Using Repeated Measures Agreement Analysis (P11-7.001)

<h3>Objective:</h3> To validate a non-invasive intracranial (ICP) waveform monitoring device against the gold standard invasive ICP monitoring device for comparison of three methodologies calculating estimated intracranial compliance. <h3>Background:</h3> Cerebral compliance is the brain’s ability to accommodate volumes increases without an increase in pressure. Several methods utilize surrogate cerebral compliance estimations, but these require invasive ICP monitoring. For this study, intracranial compliance was calculated by transcranial doppler (TCD), as well as ICP waveform analysis (P1:P2 ratio, Time to Peak [TTP]). <h3>Design/Methods:</h3> Adult brain-injured patients were monitored with both invasive (extraventricular drain) and noninvasive (mechanical extensometer). TCD and ICP waveform analysis was performed by ICM+ and Brain4Care analytics. To examine agreement, a linear mixed-effects model accounted for repeated measurements to compute the concordance correlation coefficient (CCC), total deviation index (TDI), and coefficient of individual agreement (CIA). TCD values were log-transformed to mitigate non-normality. A coverage probability plot (CPP) was computed for the percent of observations within different cut points for each method. Computations were performed in R. All tests were two-sided and statistical significance was established at 0.05. <h3>Results:</h3> 21 patients were monitored for median 36 minutes (IQR 27–42). Agreement statistics for TCD, P2/P1 ratio, and TTP were as follows: TTP: [CCC 0.33; CIA 0.25; TDI, 95% agreement 0.24 units], P2:P1: [CCC 0.42; CIA 0.05; TDI, 95% agreement 1.05], and log(TCD): [CCC: 0.50; CIA: 0.04; TDI, 95% agreement 2.94]. Although the CCC was highest for log(TCD) values, TTP and P2:1 ratio had better agreement with TDI and CIA analysis. This was further supported by the CPP, which showed TTP had the highest percent of cases within various cutoff difference values. <h3>Conclusions:</h3> Non-invasive and invasive evaluations of estimated intracranial compliance reveals discordance between the three methodologies. ICP waveform derived measurements may be a better estimate of compliance compared to TCD-derived methods; however, prospective validation studies are required. <b>Disclosure:</b> An immediate family member of Dr. Williams has stock in Jazz Pharmaceuticals. Dr. Uysal has nothing to disclose. Nicholas Thompson has nothing to disclose. Ms. Hassett has nothing to disclose. Dr. Gomes has nothing to disclose.

Comparing a Fitbit Wearable to an Electrocardiogram Gold Standard as a Measure of Heart Rate Under Psychological Stress: A Validation Study

Wearable devices collect physiological and behavioral data that have the potential to identify individuals at risk of declining mental health and well-being. Past research has mainly focused on assessing the accuracy and the agreement of heart rate (HR) measurement of wearables under different physical exercise conditions. However, the capacity of wearables to sense physiological changes, assessed by increasing HR, caused by a stressful event has not been thoroughly studied. This study followed 3 objectives: (1) to test the ability of a wearable device (Fitbit Versa 2) to sense an increase in HR upon induction of psychological stress in the laboratory; (2) to assess the accuracy of the wearable device to capture short-term HR variations caused by psychological stress compared to a gold-standard electrocardiogram (ECG) measure (Biopac); and (3) to quantify the degree of agreement between the wearable device and the gold-standard ECG measure across different experimental conditions. Participants underwent the Trier Social Stress Test protocol, which consists of an oral phase, an arithmetic stress phase, an anticipation phase, and 2 relaxation phases (at the beginning and the end). During the stress protocol, the participants wore a Fitbit Versa 2 and were also connected to a Biopac. A mixed-effect modeling approach was used (1) to assess the effect of experimental conditions on HR, (2) to estimate several metrics of accuracy, and (3) to assess the agreement: the Bland-Altman limits of agreement (LoA), the concordance correlation coefficient, the coverage probability, the total deviation index, and the coefficient of an individual agreement. Mean absolute error and mean absolute percent error were calculated as accuracy indices. A total of 34 university students were recruited for this study (64% of participants were female with a mean age of 26.8 years, SD 8.3). Overall, the results showed significant HR variations across experimental phases. Post hoc tests revealed significant pairwise differences for all phases. Accuracy analyses revealed acceptable accuracy according to the analyzed metrics of accuracy for the Fitbit Versa 2 to capture the short-term variations in psychological stress levels. However, poor indices of agreement between the Fitbit Versa 2 and the Biopac were found. Overall, the results support the use of the Fitbit Versa 2 to capture short-term stress variations. The Fitbit device showed acceptable levels of accuracy but poor agreement with an ECG gold standard. Greater inaccuracy and smaller agreement were found for stressful experimental conditions that induced a higher HR. Fitbit devices can be used in research to measure HR variations caused by stress, although they cannot replace an ECG instrument when precision is of utmost importance.

An Improved Measurement Error Model for Analyzing Unreplicated Method Comparison Data under Asymmetric Heavy-Tailed Distributions

Method comparison studies mainly focus on determining if the two methods of measuring a continuous variable are agreeable enough to be used interchangeably. Typically, a standard mixed-effects model uses to model the method comparison data that assume normality for both random effects and errors. However, these assumptions are frequently violated in practice due to the skewness and heavy tails. In particular, the biases of the methods may vary with the extent of measurement. Thus, we propose a methodology for method comparison data to deal with these issues in the context of the measurement error model (MEM) that assumes a skew- t (ST) distribution for the true covariates and centered Student’s t (cT) distribution for the errors with known error variances, named STcT-MEM. An expectation conditional maximization (ECM) algorithm is used to compute the maximum likelihood (ML) estimates. The simulation study is performed to validate the proposed methodology. This methodology is illustrated by analyzing gold particle data and then compared with the standard measurement error model (SMEM). The likelihood ratio (LR) test is used to identify the most appropriate model among the above models. In addition, the total deviation index (TDI) and concordance correlation coefficient (CCC) were used to check the agreement between the methods. The findings suggest that our proposed framework for analyzing unreplicated method comparison data with asymmetry and heavy tails works effectively for modest and large samples.

Combining Spectral-Domain OCT and Air-Puff Tonometry Analysis to Diagnose Keratoconus

PURPOSE: To investigate the diagnostic capacity of spectral-domain optical coherence tomography (SD-OCT) combined with air-puff tonometry using artificial intelligence (AI) in differentiating between normal and keratoconic eyes. METHODS: Patients who had either undergone uneventful laser vision correction with at least 3 years of stable follow-up or those who had forme fruste keratoconus (FFKC), early keratoconus (EKC), or advanced keratoconus (AKC) were included. SD-OCT and biomechanical information from air-puff tonometry was divided into training and validation sets. AI models based on random forest or neural networks were trained to distinguish eyes with FFKC from normal eyes. Model accuracy was independently tested in eyes with FFKC and normal eyes. Receiver operating characteristic (ROC) curves were generated to determine area under the curve (AUC), sensitivity, and specificity values. RESULTS: A total of 223 normal eyes from 223 patients, 69 FFKC eyes from 69 patients, 72 EKC eyes from 72 patients, and 258 AKC eyes from 258 patients were included. The top AUC ROC values (normal eyes compared with AKC and EKC) were Pentacam Random Forest Index (AUC = 0.985 and 0.958), Tomographic and Biomechanical Index (AUC = 0.983 and 0.925), and Belin-Ambrósio Enhanced Ectasia Total Deviation Index (AUC = 0.981 and 0.922). When SD-OCT and air-puff tonometry data were combined, the random forest AI model provided the highest accuracy with 99% AUC for FFKC (75% sensitivity; 94.74% specificity). CONCLUSIONS: Currently, AI parameters accurately diagnose AKC and EKC, but have a limited ability to diagnose FFKC. AI-assisted diagnostic technology that uses both SD-OCT and air-puff tonometry may overcome this limitation, leading to improved treatment of patients with keratoconus. [ J Refract Surg . 2022;38(6):374–380.]