Glucose time in range and peripheral neuropathy in type 2 diabetes mellitus and chronic kidney disease
Open accessAbstract
Objective: Compared with hemoglobin A1c (HbA1c), continuous glucose monitoring (CGM) may better capture risk of diabetes complications in patients with chronic kidney disease (CKD), including diabetic peripheral neuropathy (DPN). We hypothesized that glucose time in range (TIR), measured by CGM, is associated with DPN symptoms among participants with type 2 diabetes mellitus (type 2 DM) and moderate-to-severe CKD. Research design and methods: We enrolled 105 people with type 2 DM treated with insulin or sulfonylurea, 81 participants with CKD (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m 2 ) and 24 matched control participants with eGFR ≥60 mL/min/1.73 m 2 . Each participant wore a CGM for two 6-day periods. Calculated glycemic measures included TIR (glucose 70–180 mg/dL) and glucose management indicator (GMI). DPN symptoms were assessed using the Michigan Neuropathy Screening Instrument (MNSI) questionnaire, with a positive MNSI score defined as ≥2 symptoms. Results: Participants with CKD had a mean age of 68 years, diabetes duration 20 years, eGFR 38 mL/min/1.73 m 2 and HbA1c 7.8%, 61 mmol/mol. Sixty-two participants reported ≥2 DPN symptoms, 51 (63%) with CKD and 11 (46%) controls. Less TIR and higher GMI were associated with higher risk of MNSI questionnaire score ≥2 (OR 1.25 (95% CI 1.02 to 1.52) per 10% lower TIR, and OR 1.79 (95% CI 1.05 to 3.04) per 1% higher GMI, adjusting for age, gender and race). Similar results were observed when analyses were restricted to participants with CKD. In contrast, there was no significant association of HbA1c with DPN symptoms. Conclusions: Symptoms of DPN were common among participants with long-standing type 2 DM and CKD. Lower TIR and higher GMI were associated with DPN symptoms.
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Written from the paper’s full text.
TL;DR
In a prospective observational cohort of 105 adults with type 2 diabetes, lower continuous glucose monitoring (CGM)-measured time in range (TIR) and higher glucose management indicator (GMI) were associated with prevalent diabetic peripheral neuropathy (DPN) symptoms, while HbA1c was not. DPN symptoms were common, especially among participants with chronic kidney disease (CKD).
Key findings
- DPN symptoms, defined as Michigan Neuropathy Screening Instrument (MNSI) questionnaire score ≥2, were present in 62 of 105 participants: 51 (63%) with CKD and 11 (46%) controls; adjusted OR for CKD was 2.29 (95% CI 0.88 to 6.00).
- Lower TIR was associated with higher odds of DPN symptoms: OR 1.25 (95% CI 1.02 to 1.52) per 10% lower TIR, adjusted for age, gender, and race. DPN prevalence was 74% among those with TIR <70% versus 43% among those with TIR >70%.
- Higher GMI was associated with higher odds of DPN symptoms: OR 1.79 (95% CI 1.05 to 3.04) per 1% higher GMI, adjusted for age, gender, and race; mean GMI was 7.48% in participants with DPN versus 7.06% without DPN.
- HbA1c was not significantly associated with DPN symptoms (adjusted OR 1.25, 95% CI 0.93 to 1.69), and glucose variability by % coefficient of variation was also not significantly associated.
Methods
- Prospective observational cohort (CANDY study) of 105 participants with type 2 diabetes treated with insulin and/or sulfonylurea: 81 with CKD (eGFR <60 mL/min/1.73 m²) and 24 controls (eGFR ≥60 mL/min/1.73 m²), matched on age, diabetes duration, HbA1c, and glucose-lowering medication use.
- Participants wore a Medtronic Enlite CGM for two 6-day periods; glycemic measures included TIR (70–180 mg/dL), time above range (>180 mg/dL), GMI, and % coefficient of variation. DPN symptoms were assessed with the MNSI questionnaire, with primary outcome MNSI score ≥2.
- Linear regression with robust SEs and logistic regression were used, adjusting for age, sex, and race; secondary models added BMI, eGFR, insulin use, and sulfonylurea use, and analyses were stratified by CKD status.
Limitations
- The paper states the study was limited by relatively small sample size and cross-sectional observational design, so temporal relationships between CKD or glycemia and DPN could not be assessed; CGM data over 12 days may not reflect long-term glycemic patterns over 20 years of diabetes; and DPN was defined by subjective MNSI questionnaire symptoms rather than physical examination.
- Evident from the text: the control group was small (n=24), the CKD-DPN adjusted association confidence interval crossed the null, and the cohort was predominantly white and insulin-treated, which may limit generalizability.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
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Cites
Statistics
Claims the paper makes
0 of 37 cited sources checked · 0 supported · 0 flagged
- Findingown data
Diabetes duration was not significantly associated with diabetic peripheral neuropathy.
“Conversely, there was no significant relationship of HbA1c, glucose variability as measured by %CV or diabetes duration with DPN.”
Quote in the paperNot a substantial claim - Findingown data
HbA1c was not significantly associated with diabetic peripheral neuropathy symptoms in this study population.
“In contrast, there was no significant association of HbA1c with DPN symptoms.”
- Also stated in: § TIR, glycemia and peripheral neuropathy · plain
“Conversely, there was no significant relationship of HbA1c, glucose variability as measured by %CV or diabetes duration with DPN.”
- Also stated in: § Conclusions · plain
“Laboratory value HbA1c in our CKD population was not found to be associated with DPN”
Quote in the paperSubstantial claim - Also stated in: § TIR, glycemia and peripheral neuropathy · plain
- Findingown data
Among participants with type 2 diabetes mellitus and moderate-to-severe chronic kidney disease, 62 of 105 reported at least 2 diabetic peripheral neuropathy symptoms on the Michigan Neuropathy Screening Instrument questionnaire, including 51 of 81 (63%) with CKD and 11 of 24 (46%) controls.
“Sixty-two participants reported ≥2 DPN symptoms, 51 (63%) with CKD and 11 (46%) controls.”
- Also stated in: § CKD and peripheral neuropathy · plain
“Sixty-two participants had DPN, as established by an MNSI questionnaire score ≥2, including 51 (63%) with CKD and 11 (46%) controls; adjusted OR 2.29 (95% CI 0.88 to 6.00).”
- Also stated in: § Conclusions · plain
“Symptoms of DPN were common among participants with long-standing type 2 DM and CKD.”
Quote in the paperNot a substantial claim - Also stated in: § CKD and peripheral neuropathy · plain
- Findingown data
Participants with CKD had a higher mean Michigan Neuropathy Screening Instrument questionnaire score than controls (3.36 vs 2.33; adjusted difference 1.35, 95% CI 0.03 to 2.67, p=0.025).
“The mean MNSI questionnaire score for participants with CKD was 3.36 (2.97) and 2.33 (2.41) for controls (p=0.046), with an adjusted difference of 1.35 (95% CI 0.03 to 2.67), p=0.025.”
- Also stated in: § Discussion · plain
“On average, participants with CKD reported one more neuropathy symptom than control subjects.”
Quote in the paperNot a substantial claim - Also stated in: § Discussion · plain
- Findingown data
For most questions in the Michigan Neuropathy Screening Instrument questionnaire, participants with CKD had a higher prevalence of symptoms compared with controls.
“For most questions in the MNSI questionnaire, participants with CKD had a higher prevalence of symptoms compared with controls (figure 1).”
Quote in the paperNot a substantial claim
- Findingown data
CKD was not significantly associated with diabetic peripheral neuropathy defined as Michigan Neuropathy Screening Instrument questionnaire score ≥2 after adjustment for age, gender and race (OR 2.29, 95% CI 0.88 to 6.00).
“Sixty-two participants had DPN, as established by an MNSI questionnaire score ≥2, including 51 (63%) with CKD and 11 (46%) controls; adjusted OR 2.29 (95% CI 0.88 to 6.00).”
Quote in the paperNot a substantial claim - Findingown data
Hyperglycemia was common, with glucose >180 mg/dL during approximately one-third of time monitored by continuous glucose monitoring.
“Hyperglycemia was also common, with glucose >180 mg/dL during approximately one-third of time monitored by CGM.”
Quote in the paperNot a substantial claim - Findingown data
Glucose variability as measured by percentage coefficient of variation was not significantly associated with diabetic peripheral neuropathy.
“Conversely, there was no significant relationship of HbA1c, glucose variability as measured by %CV or diabetes duration with DPN.”
Quote in the paperNot a substantial claim - Findingown data
Lower glucose time in range is associated with higher prevalence of diabetic peripheral neuropathy symptoms (Michigan Neuropathy Screening Instrument questionnaire score ≥2), adjusted for age, sex and race: OR 1.25 (95% CI 1.02 to 1.52) per 10% lower time in range.
“Less TIR and higher GMI were associated with higher risk of MNSI questionnaire score ≥2 (OR 1.25 (95% CI 1.02 to 1.52) per 10% lower TIR, and OR 1.79 (95% CI 1.05 to 3.04) per 1% higher GMI, adjusting for age, gender and race).”
- Also stated in: § TIR, glycemia and peripheral neuropathy · plain
“The prevalence of DPN was inversely correlated with TIR (figure 2) and significantly associated, adjusting for age, sex and race (OR 1.25 (95% CI 1.02 to 1.52) per 10% (144 min) lower TIR).”
- Also stated in: § Conclusions · plain
“We found that for every 10% lower TIR there is a 25% increased risk of DPN.”
Quote in the paperSubstantial claim - Also stated in: § TIR, glycemia and peripheral neuropathy · plain
- Findingown data
With further adjustment for body mass index, estimated glomerular filtration rate, use of insulin and use of sulfonylureas, estimates of association were similar, with wider confidence intervals.
“With further adjustment for body mass index, eGFR, use of insulin and use of sulfonylureas, estimates of association were similar, with wider CIs as expected for multiple covariates applied to a relatively small group of participants.”
Quote in the paperNot a substantial claim - Findingown data
Higher glucose management indicator is associated with higher prevalence of diabetic peripheral neuropathy symptoms (Michigan Neuropathy Screening Instrument questionnaire score ≥2), adjusted for age, sex and race: OR 1.79 (95% CI 1.05 to 3.04) per 1% higher glucose management indicator.
“Less TIR and higher GMI were associated with higher risk of MNSI questionnaire score ≥2 (OR 1.25 (95% CI 1.02 to 1.52) per 10% lower TIR, and OR 1.79 (95% CI 1.05 to 3.04) per 1% higher GMI, adjusting for age, gender and race).”
- Also stated in: § TIR, glycemia and peripheral neuropathy · plain
“GMI was significantly associated with the prevalence of DPN, adjusting for age, sex and race (OR 1.79 (95% CI 1.05 to 3.04) per 1% higher GMI).”
- Also stated in: § Conclusions · plain
“Lower TIR and higher GMI were associated with DPN symptoms.”
Quote in the paperSubstantial claim - Also stated in: § TIR, glycemia and peripheral neuropathy · plain
- Findingown data
Among all participants, mean time in range was 63% ± 23%.
“Among all participants, mean TIR was 63%±23%.”
Quote in the paperNot a substantial claim - Findingown data
Similar results were observed when secondary definitions of diabetic peripheral neuropathy were evaluated as outcomes.
“Similar results were observed when secondary definitions of DPN were evaluated as outcomes (online supplementary table 1).”
Quote in the paperNot a substantial claim - Findingown data
In analyses stratified by CKD status, estimates for associations of time in range, glucose management indicator and other glycemia metrics with diabetic peripheral neuropathy were similar to those in the whole population or further from the null.
“In analyses stratified by CKD status, estimates for associations of TIR, GMI and other glycemia metrics with DPN were similar to those in the whole population or further from the null (table 4).”
Quote in the paperSubstantial claim - Findingown data
Time above range was associated with prevalence of diabetic peripheral neuropathy.
“TAR was also associated with prevalence of DPN (table 3).”
Quote in the paperSubstantial claim - Interpretationown data
In this population with CKD, continuous glucose monitoring-derived measures of glycemia more closely reflect the risk of diabetic peripheral neuropathy due to hyperglycemia than HbA1c does.
“In contrast, HbA1c in this population with CKD was not associated with DPN, suggesting that CGM-derived measures of glycemia for these individuals more closely reflect the risk of DPN due to hyperglycemia than even well-measured biomarkers of mean glycemia which are known to underestimate in CKD.24 25”
Quote in the paperSubstantial claim - Premisecitation
Core glucose metrics determined by continuous glucose monitoring, including time in range and glucose management indicator, provide more precise real-time and retrospective information about glycemic control.
“Core glucose metrics determined by CGM, including TIR and GMI, provide more precise real-time and retrospective information about glycemic control.34”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [34] source
Not checked in the free run.
- Premisecitation
Time in range has been found to be strongly associated with the development or progression of diabetic retinopathy and microalbuminuria in type 1 and type 2 diabetes mellitus.
“TIR has been found to be strongly associated with the development or progression of diabetic retinopathy and microalbuminuria in type 1 and type 2 DM.16 17”
Quote in the paperSubstantial claim0 of 2 sources checked - Study design and conductnone given
The relatively small amount of continuous glucose monitoring data may not accurately reflect long-term glycemic patterns throughout 20 years of living with diabetes.
“Our relatively small amount of CGM data may not accurately reflect the long-term glycemic patterns throughout 20 years of living with diabetes.”
Quote in the paperNot a substantial claim - Interpretationown data
Continuous glucose monitoring measures may be more strongly associated with risk of developing diabetic peripheral neuropathy in this population.
“Our data suggest that CGM measures may be more strongly associated with risk of developing DPN in this population.”
Quote in the paperSubstantial claim - Study design and conductreasoning
The primary outcome was based on subjective report of symptoms because a physical examination-based definition for diabetic peripheral neuropathy was not used.
“We did not use a physical examination-based definition for DPN, which means that our primary outcome was based on subjective report of symptoms.”
Quote in the paperSubstantial claim - Premisecitation
There is inconsistency in the relationship between glucose variability and diabetic peripheral neuropathy in the literature.
“There is inconsistency in the relationship between glucose variability and DPN in the literature, and some research indicates that for type 2 DM, glucose variability may be regarded as a marker of beta-cell function rather than direct cause of DPN.37–39”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [37] Xu, 2014, The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c, Diabetol Metab Syndr source
Not checked in the free run.
- cites [38] Hu, 2018, Association of glycaemic variability evaluated by continuous glucose monitoring with diabetic peripheral neuropathy in type 2 diabetic patients, Endocrine source
Not checked in the free run.
- cites [39] Jin, 2016, The impact of glycemic variability on diabetic peripheral neuropathy, Endocrine source
Not checked in the free run.
- Interpretationreasoning
The diabetic peripheral neuropathy symptoms observed in this study were likely due to diabetes rather than uremia.
“This suggests that the DPN symptoms we observed were likely due to diabetes, which is further supported by the significant associations of TIR and GMI with DPN in our study population.”
Quote in the paperSubstantial claim- Rests on an assumption: Uremia has little effect specifically on the peripheral nervous system, as measured by nerve conduction studies, when estimated glomerular filtration rate is greater than 12 mL/min/1.73 m2.
- Interpretationown data
In demonstrating associations of time in range and glucose management indicator with diabetic peripheral neuropathy, this study is consistent with clinical trials reporting that glycemic control prevents or delays the development and progression of diabetic peripheral neuropathy.
“In demonstrating associations of TIR and GMI with DPN, our study is consistent with clinical trials reporting that glycemic control prevents or delays the development and progression of DPN.”
Quote in the paperNot a substantial claim - Premisecitation
In the ACCORD trial, the intensive glycemic therapy arm was associated with a lower prevalence of Michigan Neuropathy Screening Instrument score ≥2 at the end of the study (HR 0.92, 95% CI 0.86 to 0.99).
“For example, in the ACCORD trial, intensive glycemic therapy arm was associated with a lower prevalence of MNSI score ≥2 at the end of the study (HR 0.92 (95% CI 0.86 to 0.99)).15”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [15] source
Not checked in the free run.
- Premisecitation
In type 2 diabetes mellitus, enhanced glycemic control has been demonstrated to more modestly reduce the risk of developing diabetic peripheral neuropathy by 5%-9%.
“In type 2 DM, enhanced glycemic control has been demonstrated to more modestly reduce the risk of developing, by DPN 5%–9%.14 15 32”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
In the DCCT/EDIC trial of type 1 diabetes mellitus, intensive diabetes therapy led to a dramatic reduction in diabetic peripheral neuropathy and its progression (78% relative risk reduction).
“In the DCCT/EDIC trial of type 1 DM, intensive diabetes therapy led to a dramatic reduction in DPN and its progression (78% relative risk reduction).13”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [13] source
Not checked in the free run.
- May combine two claims. 13
- Classified as probably not a substantial claim. 8
May combine two claims.
Findingown dataGlucose management indicator was 7.48% for participants with diabetic peripheral neuropathy and 7.06% for participants without it.
“GMI was 7.48% for participants with DPN and 7.06% for participants without DPN.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataThe 81 participants with CKD had a mean age of 68 years, diabetes duration 20 years, estimated glomerular filtration rate 38 mL/min/1.73 m2 and HbA1c 7.8%.
“The 81 participants with CKD had a mean age of 68 years, diabetes duration 20 years, body mass index 33.8 kg/m2, eGFR 38 mL/min/1.73 m2 and HbA1c 7.8%; 74% were white, 89% used insulin (table 1).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataDiabetic peripheral neuropathy prevalence was 43% among participants with time in range >70% and 74% among those with time in range <70%.
“For those participants who were within the target range >70% of the time, DPN prevalence was 43%, and those who were within target range <70% of the time, DPN prevalence was 74%.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationImproved glycemic control dramatically reduces the risk of diabetic peripheral neuropathy in people with type 1 diabetes mellitus but only modestly reduces the incidence of diabetic peripheral neuropathy in type 2 diabetes mellitus.
“Improved glycemic control has been shown to dramatically reduce the risk of DPN in people with type 1 DM but only modestly reduce the incidence of DPN in type 2 DM.13–15”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
Study design and conductreasoningThe study was limited by relatively small sample size and cross-sectional observational design, so the temporal relationship between CKD or glycemia and diabetic peripheral neuropathy could not be assessed.
“This study was limited by the relatively small sample size and the cross-sectional observational study design; therefore, we were not able to assess the temporal relationship between CKD or glycemia and DPN.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationHyperglycemia is a known risk factor for the development and progression of both diabetic peripheral neuropathy and chronic kidney disease.
“Hyperglycemia is a known risk factor for the development and progression of both DPN and CKD.9–12”
Quote in the paperSubstantial claim0 of 4 sources checkedClassified as probably not a substantial claim. May combine two claims.
PremisecitationHbA1c is a fairly crude marker of glycemia, particularly in patients with chronic kidney disease, and continuous glucose monitoring is a powerful tool in the therapeutic management of diabetes.
“HbA1c is a fairly crude marker of glycemia, particularly in patients with CKD, and CGM is a powerful tool in the therapeutic management of diabetes.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [24] Hoshino, 2017, Unique hemoglobin A1c level distribution and its relationship with mortality in diabetic hemodialysis patients, Kidney Int source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationGlucose variability has been demonstrated to be an independent risk factor for free radical damage and diabetes complications.
“Glucose variability has been demonstrated to be an independent risk factor for free radical damage and diabetes complications, yet we did not find that glucose variability was associated with DPN.35 36”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationOther studies have demonstrated that the Michigan Neuropathy Screening Instrument questionnaire closely correlates with physical examination findings, with the MNSI score ≥4 threshold most consistent with physical examination.
“However, other studies have demonstrated the MNSI questionnaire closely correlates with physical examination findings, with MNSI score ≥4 threshold most consistent with the physical examiation.22”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [22] source
Not checked in the free run.
May combine two claims.
PremisecitationNo prior studies had identified an association of time in range or glucose management indicator with diabetic peripheral neuropathy; this is the first study to demonstrate such associations.
“no prior studies have identified an association of TIR or GMI with DPN.18”
- Also stated in: § Discussion · hedged
“To our knowledge, this is the first study to demonstrate associations of TIR and GMI with DPN.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [18] source
Not checked in the free run.
- Also stated in: § Discussion · hedged
Classified as probably not a substantial claim.
Study design and conductcitationMichigan Neuropathy Screening Instrument questionnaire score ≥2 was the primary outcome definition for diabetic peripheral neuropathy because it was also used in the ACCORD and BARI-2D studies.
“MNSI questionnaire score ≥2 was our primary outcome definition for DPN because it was also used in the ACCORD and BARI-2D studies.14 15”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSome research indicates that for type 2 diabetes mellitus, glucose variability may be regarded as a marker of beta-cell function rather than a direct cause of diabetic peripheral neuropathy.
“There is inconsistency in the relationship between glucose variability and DPN in the literature, and some research indicates that for type 2 DM, glucose variability may be regarded as a marker of beta-cell function rather than direct cause of DPN.37–39”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [37] Xu, 2014, The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c, Diabetol Metab Syndr source
Not checked in the free run.
- cites [38] Hu, 2018, Association of glycaemic variability evaluated by continuous glucose monitoring with diabetic peripheral neuropathy in type 2 diabetic patients, Endocrine source
Not checked in the free run.
- cites [39] Jin, 2016, The impact of glycemic variability on diabetic peripheral neuropathy, Endocrine source
Not checked in the free run.
May combine two claims.
PremisecitationFor any given mean glucose level, HbA1c tends to be lower in end-stage kidney disease, while glucose management indicator would remain unbiased.
“For example, for any given mean glucose level, HbA1c tends to be lower in end-stage kidney disease, while GMI would remain unbiased.24”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [24] Hoshino, 2017, Unique hemoglobin A1c level distribution and its relationship with mortality in diabetic hemodialysis patients, Kidney Int source
Not checked in the free run.
May combine two claims.
Study design and conductcitationThe Michigan Neuropathy Screening Instrument questionnaire has been validated to assess distal diabetic peripheral neuropathy compared with gold standard diagnostic testing and has been widely used in large clinical trials.
“The MNSI questionnaire has been validated to assess distal DPN compared with gold standard diagnostic testing and has been widely used in large clinical trials, including Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC), Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Bypass Angioplasty Revascularization Investigation 2”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationCKD and diabetic neuropathy have been widely studied, but the focus has been primarily on cardiac autonomic neuropathies, with few studies evaluating CKD and peripheral neuropathy.
“CKD and diabetic neuropathy have been widely studied, but the focus has been primarily on cardiac autonomic neuropathies, with few studies evaluating CKD and peripheral neuropathy.26–29”
Quote in the paperNot a substantial claim0 of 4 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAbout 60%-70% of patients with CKD have some type of uremic polyneuropathy.
“About 60%–70% of patients with CKD have some type of uremic polyneuropathy.30”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [30] Aggarwal, 2013, Evaluation of spectrum of peripheral neuropathy in predialysis patients with chronic kidney disease, Ren Fail source
Not checked in the free run.
May combine two claims.
Study design and conductnone givenThe study used continuous glucose monitoring for sufficient periods of time to characterize glycemic patterns, standardized across participants.
“In addition, we used CGM for sufficient periods of time to characterize glycemic patterns, standardized across participants.”
Quote in the paperSubstantial claimMay combine two claims.
Study design and conductnone givenThe study used a validated questionnaire to define the outcome of interest and a thorough inventory of neuropathy medications.
“Other strengths of the study include the use of a validated questionnaire to define our outcome of interest and a thorough inventory of neuropathy medications.”
Quote in the paperSubstantial claim
The paper relies on this without support.
Uremia has little effect specifically on the peripheral nervous system, as measured by nerve conduction studies, when estimated glomerular filtration rate is greater than 12 mL/min/1.73 m2.
“However, uremia appears to have little effect specifically on the peripheral nervous system, as measured by nerve conduction studies, when eGFR is >12 mL/min/1.73 m2.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The results align with existing literature emphasizing the clinical benefits of higher TIR, including reduced complications and improved overall health outcomes for individuals with diabetes.
“These results align with existing literature that emphasizes the clinical benefits of higher TIR, including reduced complications and improved overall health outcomes for individuals with diabetes19,22–24.”
From Impact of digital health interventions on glycemic control and weight management. (2025) · cites this paper as [24]
The Results section reports that higher time in range (TIR) was associated with lower prevalence of diabetic peripheral neuropathy in participants with type 2 diabetes and chronic kidney disease. The Introduction also reports associations with retinopathy and microalbuminuria. The paper does not establish that raising TIR reduces complications or improves overall health outcomes; its Discussion notes that the cross-sectional design cannot establish a temporal relationship. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Conflicting CKD neuropathy prevalence
MinorThe discussion reports that 67% of participants with CKD had an MNSI score ≥2, whereas the results report 51 of 81 participants, or 63%, meeting that threshold.
“In our study, 67% of participants with CKD reported an MNSI score ≥2”
“Sixty-two participants had DPN, as established by an MNSI questionnaire score ≥2, including 51 (63%) with CKD and 11 (46%) controls”
Conflicting mean HbA1c for the CKD group
MinorThe abstract gives the CKD group's mean HbA1c as 61 mmol/mol, while table 1 gives it as 62 mmol/mol.
“Participants with CKD had a mean age of 68 years, diabetes duration 20 years, eGFR 38 mL/min/1.73 m2 and HbA1c 7.8%, 61 mmol/mol.”
“| HbA1c (mmol/mol), mean (SD) | 62 (17) | 64 (16) |”
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6. Glycemic Targets: <i>Standards of Medical Care in Diabetes—2022</i>
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6. Glycemic Targets: <i>Standards of Medical Care in Diabetes—2021</i>
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6. Glycemic Targets: <i>Standards of Care in Diabetes—2023</i>
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Continuous glucose monitoring for the routine care of type 2 diabetes mellitus
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- Authors
- Mayeda, L., Katz, R., Ahmad, I., Bansal, N., Batacchi, Z., Hirsch, I. B., Robinson, N., Trence, D. L., Zelnick, L., & de Boer, I. H.
- Affiliations
- Virginia Mason Medical Center (US)
- University of Washington (US)
- Division of Endocrinology, Banner-MD Anderson Health System, Gilbert, Arizona, USA
- Kidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA
- Corresponding author
- Mayeda, Laura
- Venue
- BMJ Open Diabetes Research & Care
- Publisher
- BMJ
- Published
- 2020-01
- Volume
- 8
- Issue
- 1
- Pages
- e000991
- ISSN
- 2052-4897 (ISSN-L)
- PMC
- PMC7039577
- OpenAlex
- W3000563589
- Semantic Scholar
- f891c91b69445a17f33242832db0923d4de66d0f
- Cited by
- 162
- References
- 39
- Citations by year
- 2026: 14 · 2025: 29 · 2024: 23 · 2023: 25 · 2022: 32 · 2021: 29 · 2020: 10
- FWCI
- 18.10
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMJ Open Diabetes Research & Care (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (R01DK087726, R01DK088762, T32DK007247)
- American Diabetes Association (#4-15-CKD-20)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Keywords
- diabetic peripheral neuropathy, type 2 diabetes, chronic kidney disease, continuous glucose monitoring, glucose management indicator, HbA1c, Michigan Neuropathy Screening Instrument, glycemic variability, insulin-treated diabetes
- MeSH terms
- Aged, Blood Glucose, Diabetes Mellitus, Type 2, Female, Follow-Up Studies, Glomerular Filtration Rate, Glycated Hemoglobin, Humans, Male, Middle Aged, Peripheral Nervous System Diseases, Prognosis, Prospective Studies, Blood Glucose Self-Monitoring, Biomarkers, Case-Control Studies, Renal Insufficiency, Chronic
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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