External Validation of Toulouse-Rangueil eGFR12 Prediction Model After Living Donor Nephrectomy.
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ABSTRACT:
SUBMITTER: Patel SS
PROVIDER: S-EPMC10511758 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature
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External Validation of Toulouse-Rangueil eGFR12 Prediction Model After Living Donor Nephrectomy.
Patel Suhani S SS Lonze Bonnie E BE Chiang Teresa Po-Yu TP Al Ammary Fawaz F Segev Dorry L DL Massie Allan B AB
Transplant international : official journal of the European Society for Organ Transplantation 20230907
Decreased postdonation eGFR is associated with a higher risk of ESRD after living kidney donation, even when accounting for predonation characteristics. The Toulouse-Rangueil model (TRM) estimates 12 month postdonation eGFR (eGFR12) to inform counseling of candidates for living donation. The TRM was validated in several single-center European cohorts but has not been validated in US donors. We assessed the TRM in living kidney donors in the US using SRTR data 1/2000-6/2021. We compared the 2021 ...[more]
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Project description:BackgroundUse of administrative data for outcomes assessment in living kidney donors is increasing given the rarity of complications and challenges with loss to follow-up.ObjectiveTo assess the validity of living donor nephrectomy in health care administrative databases compared with the reference standard of manual chart review.DesignRetrospective cohort study.Setting5 major transplant centers in Ontario, Canada.PatientsLiving kidney donors between 2003 and 2010.MeasurementsSensitivity and positive predictive value (PPV).MethodsUsing administrative databases, we conducted a retrospective study to determine the validity of diagnostic and procedural codes for living donor nephrectomies. The reference standard was living donor nephrectomies identified through the province's tissue and organ procurement agency, with verification by manual chart review. Operating characteristics (sensitivity and PPV) of various algorithms using diagnostic, procedural, and physician billing codes were calculated.ResultsDuring the study period, there were a total of 1199 living donor nephrectomies. Overall, the best algorithm for identifying living kidney donors was the presence of 1 diagnostic code for kidney donor (ICD-10 Z52.4) and 1 procedural code for kidney procurement/excision (1PC58, 1PC89, 1PC91). Compared with the reference standard, this algorithm had a sensitivity of 97% and a PPV of 90%. The diagnostic and procedural codes performed better than the physician billing codes (sensitivity 60%, PPV 78%).LimitationsThe donor chart review and validation study was performed in Ontario and may not be generalizable to other regions.ConclusionsAn algorithm consisting of 1 diagnostic and 1 procedural code can be reliably used to conduct health services research that requires the accurate determination of living kidney donors at the population level.
| S-EPMC5896849 | biostudies-literature
Project description:BackgroundOver 5,000 living kidney donor nephrectomies are performed annually in the US. While the physiological changes that occur early after nephrectomy are well documented, less is known about the long-term glomerular dynamics in living donors.MethodsWe enrolled 21 adult living kidney donors to undergo detailed long-term clinical, physiological, and radiological evaluation pre-, early post- (median, 0.8 years), and late post- (median, 6.3 years) donation. A morphometric analysis of glomeruli obtained during nephrectomy was performed in 19 subjects.ResultsDonors showed parallel increases in single-kidney renal plasma flow (RPF), renocortical volume, and glomerular filtration rate (GFR) early after the procedure, and these changes were sustained through to the late post-donation period. We used mathematical modeling to estimate the glomerular ultrafiltration coefficient (Kf), which also increased early and then remained constant through the late post-donation study. Assuming that the filtration surface area (and hence, Kf) increased in proportion to renocortical volume after donation, we calculated that the 40% elevation in the single-kidney GFR observed after donation could be attributed exclusively to an increase in the Kf. The prevalence of hypertension in donors increased from 14% in the early post-donation period to 57% in the late post-donation period. No subjects exhibited elevated levels of albuminuria.ConclusionsAdaptive hyperfiltration after donor nephrectomy is attributable to hyperperfusion and hypertrophy of the remaining glomeruli. Our findings point away from the development of glomerular hypertension following kidney donation.Trial registrationNot applicable. FUNDING. NIH (R01DK064697 and K23DK087937); Astellas Pharma US; the John M. Sobrato Foundation; the Satellite Extramural Grant Foundation; and the American Society of Nephrology.
| S-EPMC4362245 | biostudies-literature
Project description:Glioblastoma (GBM) is the most common primary malignant intracranial tumor with a poor prognosis. Ferroptosis is a newly discovered, iron-dependent, regulated cell death, and recent studies suggest its close correlation to GBM. The transcriptome and clinical data were obtained for patients diagnosed with GBM from TCGA, GEO, and CGGA. Ferroptosis-related genes were identified, and a risk score model was constructed using Lasso regression analyses. Survival was evaluated by univariate or multivariate Cox regressions and Kaplan-Meier analyses, and further analyses were performed between the high- and low-risk groups. There were 45 ferroptosis-related different expressed genes between GBM and normal brain tissues. The prognostic risk score model was based on four favorable genes, CRYAB, ZEB1, ATP5MC3, and NCOA4, and four unfavorable genes, ALOX5, CHAC1, STEAP3, and MT1G. A significant difference in OS between high- and low-risk groups was observed in both the training cohort (p < 0.001) and the validation cohorts (p = 0.029 and 0.037). Enrichment analysis of pathways and immune cells and functioning was conducted between the two risk groups. A novel prognostic model for GBM patients was developed based on eight ferroptosis-related genes, suggesting a potential prediction effect of the risk score model in GBM.
| S-EPMC9960289 | biostudies-literature
Project description:Objective: To provide a step-by-step overview of the University of Florence technique for robotic living donor nephrectomy (LDN), focusing on its technical nuances and perioperative outcomes. Methods: A dedicated robotic LDN program at our Institution was codified in 2012. Data from patients undergoing robotic LDN from 2012 to 2019 were prospectively collected. All robotic LDNs were performed by a highly experienced surgeon, using the da Vinci Si robotic platform in a three-arm configuration. In this report we provide a detailed overview of our surgical technique for robotic LDN. The main objective of the study was to evaluate the technical feasibility and safety of the technique, including perioperative surgical complications rate and mid-term functional outcomes. Results: Overall, 36 patients undergoing robotic LDNs were included in the study. Of these, 28 (78%) were left LDNs. Median (IQR) donor pre-operative eGFR was 88 (75.6-90) ml/min/1.73 m2. In all cases, robotic LDN was completed without need of conversion. The median (IQR) overall operative time was 230 (195-258) min, while the median console time was 133 (IQR 117-166) min. The median (IQR) warm ischemia time was 175 (140-255) s. No intraoperative adverse events or 90-d major surgical complications were recorded. At a median (IQR) follow-up of 24 months (IQR 11-46), median (IQR) eGFR patients undergoing in living donor nephrectomy was 57.4 (47.9; 63.9) ml/min/1.73 m2. Conclusions: In our experience, robotic LDN is technically feasible and safe. The use of robotic surgery for LDN may provide distinct advantages for surgeons while ensuring optimal donors' perioperative and functional outcomes.
| S-EPMC7844329 | biostudies-literature
Project description:BackgroundWhile living kidney donation is considered safe in healthy individuals, perioperative complications can occur due to several factors.ObjectiveWe explored associations between the incidence of perioperative complications and donor characteristics, surgical technique, and surgeon's experience in a large contemporary cohort of living kidney donors.DesignLiving kidney donors enrolled prospectively in a multicenter cohort study with some data collected retrospectively after enrollment was complete (eg, surgeon characteristics).SettingLiving kidney donor centers in Canada (n = 12) and Australia (n = 5).PatientsLiving kidney donors who donated between 2004 and 2014 and the surgeons who performed the living kidney donor nephrectomies.MeasurementsOperative and hospital discharge medical notes were collected prospectively, with data on perioperative (intraoperative and postoperative) information abstracted from notes after enrollment was complete. Complications were graded using the Clavien-Dindo system and further classified into minor and major. In 2016, surgeons who performed the nephrectomies were invited to fill an online survey on their training and experience.MethodsMultivariable logistic regression models with generalized estimating equations were used to compare perioperative complication rates between different groups of donors. The effect of surgeon characteristics on the complication rate was explored using a similar approach. Poisson regression was used to test rates of overall perioperative complications between high- and low-volume centers.ResultsOf the 1421 living kidney donor candidates, 1042 individuals proceeded with donation, where 134 (13% [95% confidence interval (CI): 11%-15%]) experienced 142 perioperative complications (55 intraoperative; 87 postoperative). The most common intraoperative complication was organ injury and the most common postoperative complication was ileus. No donors died in the perioperative period. Most complications were minor (90% of 142 complications [95% CI: 86%-96%]); however, 12 donors (1% of 1042 [95% CI: 1%-2%]) experienced a major complication. No statistically significant differences were observed between donor groups and the rate of complications. A total of 43 of 48 eligible surgeons (90%) completed the online survey. Perioperative complication rates did not vary significantly by surgeon characteristics or by high- versus low-volume centers.LimitationsOperative and discharge reporting is not standardized and varies among surgeons. It is possible that some complications were missed. The online survey for surgeons was completed retrospectively, was based on self-report, and has not been validated. We had adequate statistical power only to detect large effects for factors associated with a higher risk of perioperative complications.ConclusionsThis study confirms the safety of living kidney donation as evidenced by the low rate of major perioperative complications. We did not identify any donor or surgeon characteristics associated with a higher risk of perioperative complications.Trial registrationsNCT00319579: A Prospective Study of Living Kidney Donation (https://clinicaltrials.gov/ct2/show/NCT00319579)NCT00936078: Living Kidney Donor Study (https://clinicaltrials.gov/ct2/show/NCT00936078).
| S-EPMC6643179 | biostudies-literature
Project description:During the past decade, volatile organic compounds (VOCs) in exhaled breath have emerged as promising biomarkers for malignant pleural mesothelioma (MPM). However, as these biomarkers lack external validation, no breath test for MPM has been implemented in clinical practice. To address this issue, we performed the first external validation of a VOC-based prediction model for MPM. The external validation cohort was prospectively recruited, consisting of 47 MPM patients and 76 asbestos-exposed (AEx) controls. The predictive performance of the previously developed model was assessed by determining the degree of agreement between the predicted and actual outcome of the participants (patient/control). Additionally, to optimise the performance, the model was updated by refitting it to the validation cohort. External validation revealed a poor performance of the original model as the accuracy was estimated at only 41%, indicating poor generalisability. However, subsequent updating of the model improved the differentiation between MPM patients and AEx controls significantly (73% accuracy, 92% sensitivity, and 92% negative predictive value), substantiating the validity of the original predictors. This updated model will be more generalisable to the target population and exhibits key characteristics of a potential screening test for MPM, which could significantly impact MPM management.
| S-EPMC9264774 | biostudies-literature
Project description:ImportanceThe Simple Postoperative AKI Risk (SPARK) index is a prediction model for postoperative acute kidney injury (PO-AKI) in patients undergoing noncardiac surgery. External validation has not been performed.ObjectiveTo externally validate the SPARK index.Design, setting, and participantsThis single-center retrospective cohort study included adults who underwent noncardiac surgery under general anesthesia from 2007 to 2011. Those with obstetric or urological surgery, estimated glomerular filtration rate (eGFR) of less than 15 mL/min/1.73 m2, preoperative dialysis, or an expected surgical duration of less than 1 hour were excluded. The study was conducted at Nara Medical University Hospital. Data analysis was conducted from January to July 2021.ExposuresRisk factors for AKI included in SPARK index.Main outcomes and measuresPO-AKI, defined as an increase in serum creatinine of at least 0.3 mg/dL within 48 hours or 150% compared with preoperative baseline value or urine output of less than 0.5 mL/kg/h for at least 6 hours within 1 week after surgery, and critical AKI, defined as either AKI stage 2 or greater and/or any AKI connected to postoperative death or requiring kidney replacement therapy before discharge. The discrimination and calibration of the SPARK index were examined with area under the receiver operating characteristic curves (AUC) and calibration plots, respectively.ResultsAmong 5135 participants (2410 [46.9%] men), 303 (5.9%) developed PO-AKI, and 137 (2.7%) developed critical AKI. Compared with the SPARK cohort, participants in our cohort were older (median [IQR] age, 56 [44-66] years vs 63 [50-73] years), had lower baseline eGFR (median [IQR], 82.1 [71.4-95.1] mL/min/1.73 m2 vs 78.2 [65.6-92.2] mL/min/1.73 m2), and had a higher prevalence of comorbidities (eg, diabetes: 3956 of 51 041 [7.8%] vs 802 [15.6%]). The incidence of PO-AKI and critical AKI increased as the scores on the SPARK index increased. For example, 10 of 593 participants (1.7%) in SPARK class A, indicating lowest risk, experienced PO-AKI, while 53 of 332 (16.0%) in SPARK class D, indicating highest risk, experienced PO-AKI. However, AUCs for PO-AKI and critical AKI were 0.67 (95% CI, 0.63-0.70) and 0.62 (95% CI, 0.57-0.67), respectively, and the calibration was poor (PO-AKI: y = 0.24x + 3.28; R2 = 0.86; critical AKI: y = 0.20x + 2.08; R2 = 0.51). Older age, diabetes, expected surgical duration, emergency surgery, renin-angiotensin-aldosterone system blockade use, and hyponatremia were not associated with PO-AKI in our cohort, resulting in overestimation of the predicted probability of AKI in our cohort.Conclusions and relevanceIn this study, the incidence of PO-AKI increased as the scores on the SPARK index increased. However, the predicted probability might not be accurate in cohorts with older patients with more comorbidities.
| S-EPMC8524308 | biostudies-literature
Project description:AimsAdequate risk prediction can optimize the clinical management in adult congenital heart disease (ACHD). We aimed to update and subsequently validate a previously developed ACHD risk prediction model.Methods and resultsA prediction model was developed in a prospective cohort study including 602 moderately or severely complex ACHD patients, enrolled as outpatients at a tertiary centre in the Netherlands (2011-2013). Multivariable Cox regression was used to develop a model for predicting the 1-year risks of death, heart failure (HF), or arrhythmia (primary endpoint). The Boston ACHD Biobank study, a prospectively enrolled cohort (n = 749) of outpatients who visited a referral centre in Boston (2012-2017), was used for external validation. The primary endpoint occurred in 153 (26%) and 191 (28%) patients in the derivation and validation cohorts over median follow-up of 5.6 and 2.3 years, respectively. The final model included 5 out of 14 pre-specified predictors with the following hazard ratios; New York Heart Association class ≥II: 1.92 [95% confidence interval (CI) 1.28-2.90], cardiac medication 2.52 (95% CI 1.72-3.69), ≥1 reintervention after initial repair: 1.56 (95% CI 1.09-2.22), body mass index: 1.04 (95% CI 1.01-1.07), log2 N-terminal pro B-type natriuretic peptide (pmol/L): 1.48 (95% CI 1.32-1.65). At external validation, the model showed good discrimination (C-statistic 0.79, 95% CI 0.74-0.83) and excellent calibration (calibration-in-the-large = -0.002; calibration slope = 0.99).ConclusionThese data support the validity and applicability of a parsimonious ACHD risk model based on five readily available clinical variables to accurately predict the 1-year risk of death, HF, or arrhythmia. This risk tool may help guide appropriate care for moderately or severely complex ACHD.
| S-EPMC8728026 | biostudies-literature
Project description:Background: Glioblastoma (GBM) is the most common primary malignant intracranial tumor and closely related to metabolic alteration. However, few accepted prognostic models are currently available, especially models based on metabolic genes. Methods: The transcriptome data were obtained for all of the patients diagnosed with GBM from the Gene Expression Omnibus (GEO) (training cohort, n=369) and The Cancer Genome Atlas (TCGA) (validation cohort, n=152) with the following variables: age at diagnosis, sex, follow-up and overall survival (OS). Metabolic genes according to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were contracted, and a Lasso regression model was constructed. Survival was assessed by univariate or multivariate Cox proportional hazards regression and Kaplan-Meier analysis, and an independent external validation was also conducted to examine the model. Results: There were 341 metabolic genes showed significant differences between normal brain and GBM tissues in both the training and validation cohorts, among which 56 genes were dramatically correlated to the OS of patients. Lasso regression revealed that the metabolic prognostic model was composed of 18 genes, including COX10, COMT, and GPX2 with protective effects, as well as OCRL and RRM2 with unfavorable effects. Patients classified as high-risk by the risk score from this model had markedly shorter OS than low-risk patients (P<0.0001), and this significant result was also observed in independent external validation (P<0.001). Conclusions: The prognosis of GBM was dramatically related to metabolic pathways, and our metabolic prognostic model had high accuracy and application value in predicting the OS of GBM patients.
| S-EPMC8176239 | biostudies-literature
Project description:ImportanceThe Epic Sepsis Model (ESM), a proprietary sepsis prediction model, is implemented at hundreds of US hospitals. The ESM's ability to identify patients with sepsis has not been adequately evaluated despite widespread use.ObjectiveTo externally validate the ESM in the prediction of sepsis and evaluate its potential clinical value compared with usual care.Design, setting, and participantsThis retrospective cohort study was conducted among 27 697 patients aged 18 years or older admitted to Michigan Medicine, the academic health system of the University of Michigan, Ann Arbor, with 38 455 hospitalizations between December 6, 2018, and October 20, 2019.ExposureThe ESM score, calculated every 15 minutes.Main outcomes and measuresSepsis, as defined by a composite of (1) the Centers for Disease Control and Prevention surveillance criteria and (2) International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnostic codes accompanied by 2 systemic inflammatory response syndrome criteria and 1 organ dysfunction criterion within 6 hours of one another. Model discrimination was assessed using the area under the receiver operating characteristic curve at the hospitalization level and with prediction horizons of 4, 8, 12, and 24 hours. Model calibration was evaluated with calibration plots. The potential clinical benefit associated with the ESM was assessed by evaluating the added benefit of the ESM score compared with contemporary clinical practice (based on timely administration of antibiotics). Alert fatigue was evaluated by comparing the clinical value of different alerting strategies.ResultsWe identified 27 697 patients who had 38 455 hospitalizations (21 904 women [57%]; median age, 56 years [interquartile range, 35-69 years]) meeting inclusion criteria, of whom sepsis occurred in 2552 (7%). The ESM had a hospitalization-level area under the receiver operating characteristic curve of 0.63 (95% CI, 0.62-0.64). The ESM identified 183 of 2552 patients with sepsis (7%) who did not receive timely administration of antibiotics, highlighting the low sensitivity of the ESM in comparison with contemporary clinical practice. The ESM also did not identify 1709 patients with sepsis (67%) despite generating alerts for an ESM score of 6 or higher for 6971 of all 38 455 hospitalized patients (18%), thus creating a large burden of alert fatigue.Conclusions and relevanceThis external validation cohort study suggests that the ESM has poor discrimination and calibration in predicting the onset of sepsis. The widespread adoption of the ESM despite its poor performance raises fundamental concerns about sepsis management on a national level.
| S-EPMC8218233 | biostudies-literature