Development and initial validation of a multivariable predictive Early Adversity Scale for Schizophrenia (EAS-Sz) using register data to quantify environmental risk for adult schizophrenia diagnosis after childhood exposure to adversity

BACKGROUND

Additional to a child's genetic inheritance, environmental exposures are associated with schizophrenia. Many are broadly described as childhood adversity; modelling the combined impact of these is complex. We aimed to develop and validate a scale on childhood adversity, independent of genetic and other environmental liabilities, for use in schizophrenia risk analysis models, using data from cross-linked electronic health and social services registers.

METHOD

A cohort of N = 428 970 Western Australian children born 1980-2001 was partitioned into three samples: scale development sample (N = 171 588), and two scale validation samples (each N = 128 691). Measures of adversity were defined before a child's 10th birthday from five domains: discontinuity in parenting, family functioning, family structure, area-level socioeconomic/demographic environment and family-level sociodemographic status. Using Cox proportional hazards modelling of follow-up time from 10th birthday to schizophrenia diagnosis or censorship, weighted combinations of measures were firstly developed into scales for each domain, then combined into a final global scale. Discrimination and calibration performance were validated using Harrell's C and graphical assessment respectively.

RESULTS

A weighted combination of 42 measures of childhood adversity was derived from the development sample. Independent application to identical measures in validation samples produced Harrell's Concordance statistics of 0.656 and 0.624. Average predicted time to diagnosis curves corresponded with 95% CI limits of observed Kaplan-Meier curves in five prognostic categories.

CONCLUSIONS

Our Early Adversity Scale for Schizophrenia (EAS-Sz), the first using routinely collected register data, predicts schizophrenia diagnosis above chance, and has potential to help untangle contributions of genetic and environmental liability to schizophrenia risk.

A systematic study of work function and electronic properties of MXenes from first principles

Functional 2D materials are interesting for a wide range of applications. The rapid growth of the MXene family is due to its compositional diversity, which, in turn, allows significant tuning of the properties, and hence their applicability. The properties are to a large extent dictated by surface terminations. In the present work, we demonstrate the influence of termination species (O, NH, N, S, F, Cl, Br, I) on the changes in electronic structure, work function, dynamical stability, and atomic charges and distances of MXenes (Ti₂C, Nb₂C, V₂C, Mo₂C, Ti₃C_2, and Nb₄C₃). Among these systems, the work function values were not previously reported for ∼60% of the systems, and most of the previously reported MXenes with semiconducting nature are here proven to be dynamically unstable. The results show that the work function generally decreases with a reduced electronegativity of the terminating species, which in turn is correlated to a reduced charge of both the metal and terminating species and an increased metal-termination distance. An exception to this trend is NH terminations, which display a significantly reduced work function due to an intrinsic dipole moment within the termination. Furthermore, the results suggest that halogen terminations improve the electrical conductivity of the materials.

Pulmonary embolism and deep venous thrombosis after COVID-19: long-term risk in a population-based cohort study

Background

Venous thromboembolism (VTE) (pulmonary embolism (PE) or deep venous thrombosis (DVT)) is common during acute COVID-19. Long-term excess risk has not yet been established.

Objective

To study long-term VTE risk after COVID-19.

Methods

Swedish citizens aged 18-84 years, hospitalized and/or testing positive for COVID-19 between January 1, 2020, and September 11, 2021 (exposed), stratified by initial hospitalization, were compared to matched (1:5) non-exposed population-derived subjects without COVID-19. Outcomes were incident VTE, PE or DVT recorded within 60, 60-<180, and ≥180 days. Cox regression was used for evaluation and a model adjusted for age, sex, comorbidities and socioeconomic markers developed to control for confounders.

Results

Among exposed patients, 48,861 were hospitalized for COVID-19 (mean age 60.6 years) and 894,121 were without hospitalization (mean age 41.4 years). Among patients hospitalized for COVID-19, fully adjusted hazard ratios (HRs) during 60-<180 days were 6.05 (95% confidence interval (CI) 4.80─7.62) for PE and 3.97 (CI 2.96─5.33) for DVT, compared to non-exposed with corresponding estimates among COVID-19 without hospitalization 1.17 (CI 1.01─1.35) and 0.99 (CI 0.86─1.15), based on 475 and 2,311 VTE events, respectively. Long-term (≥180 days) HRs in patients hospitalized for COVID-19 were 2.01 (CI 1.51─2.68) for PE and 1.46 (CI 1.05─2.01) for DVT while non-hospitalized had similar risk to non-exposed, based on 467 and 2,030 VTE events, respectively.

Conclusions

Patients hospitalized for COVID-19 retained an elevated excess risk of VTE, mainly PE, after 180 days, while long-term risk of VTE in individuals with COVID-19 without hospitalization was similar to the non-exposed.

A Masked Language Model for Multi-Source EHR Trajectories Contextual Representation Learning

Using electronic health records data and machine learning to guide future decisions needs to address challenges, including 1) long/short-term dependencies and 2) interactions between diseases and interventions. Bidirectional transformers have effectively addressed the first challenge. Here we tackled the latter challenge by masking one source (e.g., ICD10 codes) and training the transformer to predict it using other sources (e.g., ATC codes).

Vaccine-induced correlate of protection against fatal COVID-19 in older and frail adults during waves of neutralization-resistant variants of concern: an observational study

Background

To inform future preventive measures including repeated vaccinations, we have searched for a clinically useful immune correlate of protection against fatal COVID-19 among nursing homes residents.

Methods

We performed repeated capillary blood sampling with analysis of S-binding IgG in an open cohort of nursing home residents in Sweden. We analyzed immunological and registry data from 16 September 2021 to 31 August 2022 with follow-up of deaths to 30 September 2022. The study period included implementation of the 3rd and 4th mRNA monovalent vaccine doses and Omicron virus waves.

Findings

A total of 3012 nursing home residents with median age 86 were enrolled. The 3rd mRNA dose elicited a 99-fold relative increase of S-binding IgG in blood and corresponding increase of neutralizing antibodies. The 4th mRNA vaccine dose boosted levels 3.8-fold. Half-life of S-binding IgG was 72 days. A total 528 residents acquired their first SARS-CoV-2 infection after the 3rd or the 4th vaccine dose and the associated 30-day mortality was 9.1%. We found no indication that levels of vaccine-induced antibodies protected against infection with Omicron VOCs. In contrast, the risk of death was inversely correlated to levels of S-directed IgG below the 20th percentile. The death risk plateaued at population average above the lower 35th percentile of S-binding IgG.

Interpretation

In the absence of neutralizing antibodies that protect from infection, quantification of S-binding IgG post vaccination may be useful to identify the most vulnerable for fatal COVID-19 among the oldest and frailest. This information is of importance for future strategies to protect vulnerable populations against neutralization resistant variants of concern.

Funding

Swedish Research Council, SciLifeLab via Knut and Alice Wallenberg Foundation, VINNOVA. Swedish Healthcare Regions, and Erling Persson Foundation.

Healthcare utilization and psychiatric morbidity in violent offenders: findings from a prospective cohort study

PURPOSE

Although persistent offenders with histories of imprisonment and violence have disproportionate high rates of psychiatric disorders, little is known of their psychiatric healthcare utilization (HCU) and HCU-associated factors. This study aimed to explore psychiatric HCU, psychiatric morbidity, and psychotropic prescription drugs in violent offenders with a history of incarceration.

METHODS

Male offenders aged 18-25 (n = 266) imprisoned for violent and/or physical sexual offenses were clinically assessed in 2010-2012 and prospectively followed in Swedish national registries through 2017. Register-based information regarding HCU, psychiatric morbidity, and psychotropic drugs was tracked and compared with a general population group (n = 10,000) and across offending trajectory groups. Baseline risk factors were used to explain prospective psychiatric HCU in violent offenders.

RESULTS

Violent offenders used less general healthcare and psychiatric outpatient care, but more psychiatric inpatient care and were more often given psychiatric diagnoses and psychotropic drugs than the general population. Participants previously assigned to persisting offending trajectory groups had higher rates of psychiatric HCU than those assigned to a desisting trajectory. In multivariable regression models, psychiatric HCU was associated with anxiety disorders, prior psychiatric contact, placement in a foster home, psychopathic traits, low intellectual functioning, and persistent offending.

CONCLUSIONS

Violent offenders are burdened by extensive and serious psychiatric morbidity and typically interact with psychiatric healthcare as inpatients rather than outpatients. Knowledge about their backgrounds, criminal behaviors, and psychiatric statuses can aid the planning of psychiatric services for this troublesome group.

On-Surface Synthesis of Polyphenylene Wires Comprising Rigid Aliphatic Bicyclo[1.1.1]Pentane Isolator Units

Bicyclo[1.1.1]pentane (BCP) motifs are of growing importance to the pharmaceutical industry as sp3-rich bioisosteres of benzene rings and as molecular tectons in materials science. Herein we explore the behavior of 1,3-disubstituted BCP moieties on metal surfaces by combining low-temperature scanning tunneling microscopy / non-contact atomic force microscopy studies with density functional theory modeling. We examine the configuration of individual BCP-containing precursors on Au(111), their supramolecular assembly and thermally activated dehalogenative coupling reactions, affording polymeric chains with incorporated electronically isolating units. Our studies not only provide the first sub-molecular insights of the BCP scaffold behavior on surfaces, but also extend the potential application of BCP derivatives towards integration in custom-designed surface architectures.

Pyridinic Nitrogen Modification for Selective Acetylenic Homocoupling on Au(111)

On-surface acetylenic homocoupling has been proposed to construct carbon nanostructures featuring sp hybridization. However, the efficiency of linear acetylenic coupling is far from satisfactory, often resulting in undesired enyne products or cyclotrimerization products due to the lack of strategies to enhance chemical selectivity. Herein, we inspect the acetylenic homocoupling reaction of polarized terminal alkynes (TAs) on Au(111) with bond-resolved scanning probe microscopy. The replacement of benzene with pyridine moieties significantly prohibits the cyclotrimerization pathway and facilitates the linear coupling to produce well-aligned N-doped graphdiyne nanowires. Combined with density functional theory calculations, we reveal that the pyridinic nitrogen modification substantially differentiates the coupling motifs at the initial C-C coupling stage (head-to-head vs head-to-tail), which is decisive for the preference of linear coupling over cyclotrimerization.

The complexity of kidney disease and diagnosing it - cystatin C, selective glomerular hypofiltration syndromes and proteome regulation

Estimation of kidney function is often part of daily clinical practice, mostly done by using the endogenous glomerular filtration rate (GFR)-markers creatinine or cystatin C. A recommendation to use both markers in parallel in 2010 has resulted in new knowledge concerning the pathophysiology of kidney disorders by the identification of a new set of kidney disorders, selective glomerular hypofiltration syndromes. These syndromes, connected to strong increases in mortality and morbidity, are characterized by a selective reduction in the glomerular filtration of 5-30 kDa molecules, such as cystatin C, compared to the filtration of small molecules <1 kDa dominating the glomerular filtrate, for example water, urea and creatinine. At least two types of such disorders, shrunken or elongated pore syndrome, are possible according to the pore model for glomerular filtration. Selective glomerular hypofiltration syndromes are prevalent in investigated populations, and patients with these syndromes often display normal measured GFR or creatinine-based GFR-estimates. The syndromes are characterized by proteomic changes promoting the development of atherosclerosis, indicating antibodies and specific receptor-blocking substances as possible new treatment modalities. Presently, the KDIGO guidelines for diagnosing kidney disorders do not recommend cystatin C as a general marker of kidney function and will therefore not allow the identification of a considerable number of patients with selective glomerular hypofiltration syndromes. Furthermore, as cystatin C is uninfluenced by muscle mass, diet or variations in tubular secretion and cystatin C-based GFR-estimation equations do not require controversial race or sex terms, it is obvious that cystatin C should be a part of future KDIGO guidelines.

Unveiling the formation mechanism of the biphenylene network

We have computationally studied the formation mechanism of the biphenylene network via the intermolecular HF zipping, as well as identified key intermediates experimentally, on the Au(111) surface. We elucidate that the zipping process consists of a series of defluorinations, dehydrogenations, and C-C coupling reactions. The Au substrate not only serves as the active site for defluorination and dehydrogenation, but also forms C-Au bonds that stabilize the defluorinated and dehydrogenated phenylene radicals, leading to "standing" benzyne groups. Despite that the C-C coupling between the "standing" benzyne groups is identified as the rate-limiting step, the limiting barrier can be reduced by the adjacent chemisorbed benzyne groups. The theoretically proposed mechanism is further supported by scanning tunneling microscopy experiments, in which the key intermediate state containing chemisorbed benzyne groups can be observed. This study provides a comprehensive understanding towards the on-surface intermolecular HF zipping, anticipated to be instructive for its future applications.

Proxy Variables and the Generalizability of Study Results

When individuals self-select (or are selected) into a study based on factors that influence the outcome, conclusions may not generalize to the full population. To compensate for this, results may be adjusted, for example, by standardization on the set of common causes of participation and outcome. Although such standardization is useful in some contexts, the common causes of participation and outcome may in practice not be fully observed. Instead, the researcher may have access to one or several variables related to the common causes, that is, to proxies for the common causes. This article defines and examines different types of proxy variables and shows how these can be used to obtain generalizable study results. First of all, the researcher may exploit proxies that influence only participation or outcome but which still allow for perfect generalizability by rendering participation and outcome conditionally independent. Further, generalizability can be achieved by leveraging 2 proxies, one of which is allowed to influence participation and one of which is allowed to influence the outcome, even if participation and outcome do not become independent conditional on these. Finally, approximate generalizability may be obtained by exploiting a single proxy that does not itself influence participation or outcome.

Machine learning for early prediction of acute myocardial infarction or death in acute chest pain patients using electrocardiogram and blood tests at presentation

AIMS

In the present study, we aimed to evaluate the performance of machine learning (ML) models for identification of acute myocardial infarction (AMI) or death within 30 days among emergency department (ED) chest pain patients.

METHODS AND RESULTS

Using data from 9519 consecutive ED chest pain patients, we created ML models based on logistic regression or artificial neural networks. Model inputs included sex, age, ECG and the first blood tests at patient presentation: High sensitivity TnT (hs-cTnT), glucose, creatinine, and hemoglobin. For a safe rule-out, the models were adapted to achieve a sensitivity > 99% and a negative predictive value (NPV) > 99.5% for 30-day AMI/death. For rule-in, we set the models to achieve a specificity > 90% and a positive predictive value (PPV) of > 70%. The models were also compared with the 0 h arm of the European Society of Cardiology algorithm (ESC 0 h); An initial hs-cTnT < 5 ng/L for rule-out and ≥ 52 ng/L for rule-in. A convolutional neural network was the best model and identified 55% of the patients for rule-out and 5.3% for rule-in, while maintaining the required sensitivity, specificity, NPV and PPV levels. ESC 0 h failed to reach these performance levels.

DISCUSSION

An ML model based on age, sex, ECG and blood tests at ED arrival can identify six out of ten chest pain patients for safe early rule-out or rule-in with no need for serial blood tests. Future studies should attempt to improve these ML models further, e.g. by including additional input data.

Design and Manipulation of a Minimalistic Hydrocarbon Nanocar on Au(111)

Nanocars are carbon-based single-molecules with a precise design that facilitates their atomic-scale control on a surface. The rational design of these molecules is important in atomic and molecular-scale manipulation to advance the development of molecular machines, as well as for a better understanding of self-assembly, diffusion and desorption processes. Here, we introduce the molecular design and construction of a collection of minimalistic nanocars. They feature an anthracene chassis and four benzene derivatives as wheels. After sublimation and adsorption on an Au(111) surface, we show controlled and fast manipulation of the nanocars along the surface using the tip of a scanning tunneling microscope (STM). The mechanism behind the successful displacement is the induced dipole created over the nanocar by the STM tip. We utilized carbon monoxide functionalized tips both to avoid decomposition and accidentally picking the nanocars up during the manipulation. This strategy allowed thousands of maneuvers to successfully win the Nanocar Race II championship.

Offending Trajectories in Violent Offenders: Criminal History and Early Life Risk Factors

The understanding of offending, and thus its possible prevention, is expanded through longitudinal studies on criminal trajectories depicting early life risk factors. This longitudinal study aimed to explore criminal trajectories, criminal histories, and early life risk factors in a cohort of violent offenders. A Swedish nationally representative cohort of male violent offenders (n = 266), clinically assessed while imprisoned aged 18 to 25, was followed through national registers from age 15 to 25-34. Substantial differences in criminal histories between violent offenders and a matched comparison group (n = 10,000) were demonstrated. Five trajectory groups were identified: four persisting and one desisting. Although differences were observed between persisting trajectory groups, a higher prevalence of early life risk factors was generally displayed compared to the desisting, especially in conduct problems and experiences of out-of-home placements. Neurocognitive ability and prevalence of ADHD and autism were similar across trajectories. Severe early life risks highlight the population's need for early interventions.

Cystatin C-Based Equation to Estimate GFR without the Inclusion of Race and Sex

BACKGROUND

The accuracy of estimation of kidney function with the use of routine metabolic tests, such as measurement of the serum creatinine level, has been controversial. The European Kidney Function Consortium (EKFC) developed a creatinine-based equation (EKFC eGFRcr) to estimate the glomerular filtration rate (GFR) with a rescaled serum creatinine level (i.e., the serum creatinine level is divided by the median serum creatinine level among healthy persons to control for variation related to differences in age, sex, or race). Whether a cystatin C-based EKFC equation would increase the accuracy of estimated GFR is unknown.

METHODS

We used data from patients in Sweden to estimate the rescaling factor for the cystatin C level in adults. We then replaced rescaled serum creatinine in the EKFC eGFRcr equation with rescaled cystatin C, and we validated the resulting EKFC eGFRcys equation in cohorts of White patients and Black patients in Europe, the United States, and Africa, according to measured GFR, levels of serum creatinine and cystatin C, age, and sex.

RESULTS

On the basis of data from 227,643 patients in Sweden, the rescaling factor for cystatin C was estimated at 0.83 for men and women younger than 50 years of age and 0.83 + 0.005 × (age - 50) for those 50 years of age or older. The EKFC eGFRcys equation was unbiased, had accuracy that was similar to that of the EKFC eGFRcr equation in both White patients and Black patients (11,231 patients from Europe, 1093 from the United States, and 508 from Africa), and was more accurate than the Chronic Kidney Disease Epidemiology Collaboration eGFRcys equation recommended by Kidney Disease: Improving Global Outcomes. The arithmetic mean of EKFC eGFRcr and EKFC eGFRcys further improved the accuracy of estimated GFR over estimates from either biomarker equation alone.

CONCLUSIONS

The EKFC eGFRcys equation had the same mathematical form as the EKFC eGFRcr equation, but it had a scaling factor for cystatin C that did not differ according to race or sex. In cohorts from Europe, the United States, and Africa, this equation improved the accuracy of GFR assessment over that of commonly used equations. (Funded by the Swedish Research Council.).

Performance of creatinine-based equations to estimate glomerular filtration rate in White and Black populations in Europe, Brazil and Africa

BACKGROUND

A new Chronic Kidney Disease Epidemiology Collaboration equation without the race variable has been recently proposed (CKD-EPIAS). This equation has neither been validated outside USA nor compared with the new European Kidney Function Consortium (EKFC) and Lund-Malmö Revised (LMREV) equations, developed in European cohorts.

METHODS

Standardized creatinine and measured glomerular filtration rate (GFR) from the European EKFC cohorts (n = 13 856 including 6031 individuals in the external validation cohort), from France (n = 4429, including 964 Black Europeans), from Brazil (n = 100) and from Africa (n = 508) were used to test the performances of the equations. A matched analysis between White Europeans and Black Africans or Black Europeans was performed.

RESULTS

In White Europeans (n = 9496), both the EKFC and LMREV equations outperformed CKD-EPIAS (bias of -0.6 and -3.2, respectively versus 5.0 mL/min/1.73 m², and accuracy within 30% of 86.9 and 87.4, respectively, versus 80.9%). In Black Europeans and Black Africans, the best performance was observed with the EKFC equation using a specific Q-value (= concentration of serum creatinine in healthy males and females). These results were confirmed in matched analyses, which showed that serum creatinine concentrations were different in White Europeans, Black Europeans and Black Africans for the same measured GFR, age, sex and body mass index. Creatinine differences were more relevant in males.

CONCLUSION

In a European and African cohort, the performances of CKD-EPIAS remain suboptimal. The EKFC equation, using usual or dedicated population-specific Q-values, presents the best performance in the whole age range in the European and African populations included in this study.

Estimates of excess mortality for the five Nordic countries during the COVID-19 pandemic 2020-2021

BACKGROUND

Excess mortality during the COVID-19 pandemic is of major scientific and political interest.

METHODS

We critically reviewed different estimates of all-cause excess mortality for the five Nordic countries (Denmark, Finland, Iceland, Norway and Sweden), which have been much studied during the COVID-19 pandemic, using the latest register data to discuss uncertainties and implications.

RESULTS

We show using back-calculation of expected deaths from Nordic all-cause deaths that the Institute for Health Metrics and Evaluation model is a clear outlier in the compared estimates and likely substantially overestimates excess mortality of Finland and Denmark, and probably Sweden. Our review suggests a range of total Nordic excess deaths of perhaps 15 000-20 000, but results are sensitive to assumptions in the models as shown.

CONCLUSIONS

We document substantial heterogeneity and uncertainty in estimates of excess mortality. All estimates should be taken with caution in their interpretation as they miss detailed account of demographics, such as changes in the age group populations over the study period.

COVID-19 in people aged 18-64 in Sweden in the first year of the pandemic: Key factors for severe disease and death

Background

Studies on risk factors for severe COVID-19 in people of working age have generally not included non-working persons or established population attributable fractions (PAFs) for occupational and other factors.

Objectives

We describe the effect of job-related, sociodemographic, and other exposures on the incidence, relative risks and PAFs of severe COVID-19 in individuals aged 18-64.

Methods

We conducted a registry-based study in Swedish citizens aged 18-64 from 1 January 2020 to 1 February 2021 with respect to COVID-19-related hospitalizations and death.

Results

Of 6,205,459 persons, 272,043 (7.5%) were registered as infected, 3399 (0.05%) needed intensive care, and 620 (0.01%) died, with an estimated case fatality rate of 0.06% over the last 4-month period when testing was adequate. Non-Nordic origin was associated with a RR for need of intensive care of 3·13, 95%CI 2·91-3·36, and a PAF of 32·2% after adjustment for age, sex, work, region and comorbidities. In a second model with occupation as main exposure, and adjusted for age, sex, region, comorbidities and origin, essential workers had an RR of 1·51, 95%CI, 1·35-1·6, blue-collar workers 1·18, 95%CI 1·06-1·31, school staff 1·21, 95%CI 1·01-1·46, and health and social care workers 1·89, 95%CI 1·67-2·135) compared with people able to work from home, with altogether about 13% of the PAF associated with these occupations. Essential workers and blue-collar workers, but no other job categories had higher risk of death, adjusted RRs of 1·79, 95%CI 1·34-2·38 and 1·37, 95%CI 1·04-1·81, with adjusted PAFs of altogether 9%.

Conclusion

Among people of working age in Sweden, overall mortality and case fatality were low. Occupations that require physical presence at work were associated with elevated risk of needing intensive care for COVID-19, with 14% cases attributable to this factor, and 9% of deaths.

Standardization of serum creatinine is essential for accurate use of unbiased estimated GFR equations: evidence from three cohorts matched on renal function

BACKGROUND

Differences in the performance of estimated glomerular filtration rate (eGFR) equations have been attributed to the mathematical form of the equations and to differences between patient demographics and measurement methods. We evaluated differences in serum creatinine (SCr) and eGFR in cohorts matched for age, sex, body mass index (BMI) and measured GFR (mGFR).

METHODS

White North Americans from Minnesota (n = 1093) and the Chronic Renal Insufficiency Cohort (CRIC) (n = 1548) and White subjects from the European Kidney Function Consortium (EKFC) cohort (n = 7727) were matched for demographic patient characteristics (sex, age ± 3 years, BMI ± 2.5 kg/m2) and renal function (mGFR ± 3 ml/min/1.73 m2). SCr was measured with isotope dilution mass spectrometry (IDMS)-traceable assays in the Minnesota and EKFC cohorts and with non-standardized SCr assays recalculated to IDMS in the CRIC. The Minnesota cohort and CRIC shared a common method to measure GFR (renal clearance of iothalamate), while the EKFC cohort used a variety of exogenous markers and methods, all with recognized sufficient accuracy. We compared the SCr levels and eGFR predictions [for Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and EKFC equations] of patients fulfilling these matching criteria.

RESULTS

For 305 matched individuals, mean SCr (mg/dL) was not different between the Minnesota and EKFC cohorts (females 0.83 ± 0.20 versus 0.86 ± 0.23, males 1.06 ± 0.23 versus 1.12 ± 0.37; P > .05) but significantly different from the CRIC [females 1.13 ± 0.23 (P < .0001), males 1.42 ± 0.31 (P < .0001)]. The CKD-EPI equations performed better than the EKFC equation in the CRIC, while the opposite was true in the Minnesota and EKFC cohorts.

CONCLUSION

Significant differences in SCr concentrations between the Minnesota and EKFC cohorts versus CRIC were observed in subjects with the same level of mGFR and equal demographic characteristics and can be explained by the difference in SCr calibration.