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Record W4296807760 · doi:10.1097/cm9.0000000000002254

Corneal confocal microscopy meets continuous glucose monitoring: a tale of two technologies

2022· editorial· en· W4296807760 on OpenAlexaboutno aff
Rayaz A. Malik

Bibliographic record

VenueChinese Medical Journal · 2022
Typeeditorial
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsnot available
Fundersnot available
KeywordsConfocal microscopyContinuous glucose monitoringConfocalMicroscopyOphthalmologyNanotechnologyOptometryChemistryOpticsMaterials scienceMedicineDiabetes mellitusPhysicsEndocrinologyType 1 diabetes

Abstract

fetched live from OpenAlex

Zhao et al[1] from Shanghai, China, have undertaken a detailed clinical study in a cohort of 206 asymptomatic patients with type 2 diabetes utilizing advanced in vivo nerve imaging with corneal confocal microscopy (CCM-Heidelberg HRT III RCM) and continuous glucose monitoring (CGM-iPro2 system) over 7 days. The study provides important insights into the relationship between relatively short-term glucose perturbation over 7 days and corneal nerve loss in diabetic neuropathy. Furthermore, it reinforces the role of CCM in detecting early sub-clinical nerve loss, as almost one-third of asymptomatic patients had corneal nerve fiber loss, which was independently associated with glucose time in range (TIR) (percentage of time within the glucose range of 3.9–10.0 mmol/L) but not with quartiles of hemoglobin A1c (HbA1c), an established measure of long-term glycemic control. Indeed, each 10% increase in TIR was associated with a 28.2% (95% CI: 0.595–0.866, P = 0.001) decrease in the risk of abnormal corneal nerve fiber length (CNFL). This supports recent studies showing that TIR is associated with other long-term complications of diabetes, including symptomatic diabetic neuropathy in patients with nephropathy[2] and diabetic retinopathy.[3] In 2003, we pioneered the use of CCM to objectively quantify neurodegeneration in sub-clinical and more advanced diabetic neuropathy[4] and dared to suggest that CCM could act as an objective surrogate marker for diabetic neuropathy in longitudinal studies, especially as an end-point in clinical trials.[5] This was based on our initial study, which showed a significant reduction in all three corneal nerve parameters in patients with moderate and severe neuropathy, and especially a significant reduction in corneal nerve branch density in those with mild neuropathy.[4] This was followed by the demonstration of corneal nerve regeneration within 6 months of simultaneous pancreas and kidney transplantation in patients with type 1 diabetes and severe baseline diabetic neuropathy.[6] Twenty years later, with over 500 published studies from Europe, Canada, Australia, and latterly Japan and China, CCM is a firmly established measure of nerve fiber damage and repair in diabetic neuropathy,[7] and shows promise in other peripheral neuropathies and central neurodegenerative diseases.[8] A Web of Science search on 1 March 2022, with “corneal confocal microscopy” and “nerves” as the primary search terms, returned 1382 publications which have been cited 35,489 times and have a H-index of 90. Indeed, we have shown that corneal nerve loss is comparable to intraepidermal nerve fiber (IENF) loss,[9,10] the gold standard for assessing small fiber damage. It has excellent diagnostic[11,12] and prognostic[13] value in patients with diabetic neuropathy. Stem et al[14] observed corneal nerve loss in patients with type 2 diabetes and diabetic peripheral neuropathy (DPN), as well as patients with type 1 diabetes without DPN, based on symptoms/signs and nerve conduction velocity (NCV), and they suggested that the type of diabetes may influence the extent of corneal nerve loss. However, evidence of corneal nerve loss in children with type 1 diabetes[15] and subjects with impaired glucose tolerance[16] and recently diagnosed type 2 diabetes[17] suggests that CCM can identify early sub-clinical neuropathy in both types of diabetes, and that minor glycemic perturbations and other factors such as obesity, hypertension, and hyperlipidemia may drive early neurodegeneration. Interestingly, in a Canadian study of 64 healthy volunteers, there was a strong independent association between CNFL and HbA1c in the normal range, suggesting that even minimal glycemic exposure may lead to sub-clinical nerve injury.[18] Additionally, we have published normative values from 343 healthy volunteers and showed a small age dependent decrease in corneal nerve fiber density (CNFD) and CNFL, but no impact of height, weight, or body mass index.[19] In our recent study of a cohort of 490 participants, corneal nerve loss was associated with low-density lipoprotein (LDL)-cholesterol and triglycerides, as opposed to hyperglycemia, in type 1 diabetes, and with age, weight, and HbA1c in type 2 diabetes.[20] In a study from Norway, 144 participants with screen detected type 2 diabetes with and without diabetic neuropathy showed a lower CNFD, which was associated with age, height, and total and LDL-cholesterol.[21] Furthermore, reduced CNFL predicts 4-year incident DPN,[22] and a more rapid decline in CNFL is associated with the development of clinical diabetic neuropathy.[23] Indeed, in a large longitudinal study of 261 patients without DPN, we have recently shown that a CNFL of <14.1 mm/mm2 was associated with 67% sensitivity, 71% specificity, and a hazard ratio of 2.95 (95% CI 1.70–5.11; P < 0.001) for new-onset DPN over a mean follow up of 5.8 years.[13] In a Japanese study of patients with type 1 diabetes, the mean annual HbA1c level 7 to 10 years prior to CCM was an independent predictor of reduced CNFL and CNFD.[24] In a study from Australia of 231 individuals with type 1 and type 2 diabetes and mild neuropathy, HbA1c showed a significant correlation with CNFL.[25] To further understand the relationship between glucose perturbation and corneal nerve loss and repair, it is important to consider whether improved glycemia is associated with corneal nerve regeneration. We initially showed that simultaneous pancreas and kidney (SPK) transplantation and normalization of HbA1c in patients with type 1 diabetes was associated with corneal nerve regeneration after 6 months.[6] We extended this study and showed continued corneal nerve fiber repair 12 months after SPK, but with no impact on conventional neuropathy end points, for example, symptoms, nerve conduction, and IENF repair.[26] Furthermore, SPK was associated with continued regeneration of corneal nerve fibers, followed by an improvement in neuropathic symptoms after 24 months, and nerve conduction after 36 months.[27] Previously we showed that an improvement in HbA1c, blood pressure, and total cholesterol over 24 months was associated with corneal nerve regeneration.[28] In relation to the link between CNFL and glucose variability observed by Zhao et al[1], we have previously shown that continuous subcutaneous insulin infusion with lower glucose variability, as compared to basal bolus insulin, was associated with corneal nerve regeneration, despite a comparable HbA1c.[29] In a recent longitudinal study of patients with type 1 diabetes over 6.5 years, those with the highest HbA1c (68.1–86.7 mmol/mol) showed corneal nerve loss, while those in the optimally controlled tertile (HbA1c, 35.0–54.0 mmol/mol) showed corneal nerve regeneration.[30] Recently, however, we have shown progressive corneal nerve fiber degeneration despite an improvement in HbA1c and total cholesterol.[31] Corneal nerve regeneration has been demonstrated after bariatric surgery in obese subjects with[32] and without[33] diabetes, and was independently associated with an improvement in triglycerides, but not HbA1c. In a randomized clinical trial of once weekly glucagon-like peptide-1 or basal bolus insulin over 12 months, a marked improvement in HbA1c by ∼3% was associated with corneal nerve regeneration, but with no change in vibration perception or sudomotor function.[34] Two separate trials with omega-3 fatty acid in patients with type 1 diabetes have independently shown corneal nerve regeneration, with no change in NCV and sensory and autonomic nerve function.[35,36] In conclusion, Zhao et al[1] confirm that CCM identifies sub-clinical and established neuropathy, and shows the dynamic and responsive nature of corneal nerves in relation to even minor glucose perturbations detected using CGM. This further emphasizes the key role of CCM as an end-point in clinical trials of diabetic neuropathy, and perhaps other neurodegenerative diseases. Conflicts of interest None.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.310
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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