Diabetic Ketoacidosis and Hyperosmolar Hyperglycemic State: Understanding Tumor Markers and Clinical Implications

Diabetic Ketoacidosis and Hyperosmolar Hyperglycemic State: Understanding Tumor Markers and Clinical Implications

Introduction

Diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS) represent acute, critical complications stemming from diabetes mellitus (DM). Both conditions exhibit severe hyperglycemia; however, their underlying causes, pathophysiology, clinical manifestations, and diagnostic approaches differ, necessitating distinct therapeutic interventions that extend beyond standard fluid resuscitation and basic insulin administration (2). DKA typically manifests in younger patients, often linked to type 1 diabetes (T1D) or severe islet function impairment. Patients present with significant ketonemia and various degrees of acidosis, possibly losing over 10% of their body weight in fluids. Common symptoms include nausea, vomiting, abdominal pain, and mild alterations in consciousness when compared to those experiencing HHS (3). In contrast, HHS largely affects older adults who may lack prior DM diagnoses, characterized by marked hyperglycemia, osmolarity exceeding 320 mosm/L, and significant fluid losses mirroring 10% of total body weight. Such patients may exhibit reduced consciousness levels (GCS below 14) and altered vital signs, including hypotension, tachycardia, and signs of hypoperfusion (4,5). The triggers of these acute diabetic complications can stem from various sources, including infections, uncontrolled blood sugar levels, inadequate dietary management, dehydration, or similar factors (6,7).

This study critically assesses the relationship between elevated tumor markers—specifically AFP, CEA, CA199, CA155, CA153, PSA, and CPSA—and acute diabetic complications like DKA and HHS. By discerning the variances in tumor markers amidst these conditions, we aim to uncover the underlying sources or pathology of this phenomenon and identify potential cancer risk factors associated with DKA and HHS.

Materials and Methods

Source of Patient Data

A cohort of patients satisfying international diagnostic criteria for DKA (n=206) and HHS (n=59) were analyzed. DKA criteria included blood glucose exceeding 250 mg/dL coupled with ketonemia or urine ketone presence, alongside a pH 7.3, or HCO3- levels lower than 15 mmol/L based on blood-air assessments. We excluded patients presenting other forms of acidosis such as lactic acidosis, shock, circulatory hypoperfusion, acute hypoxia, or identified malignancies indicated by imaging studies. The clinical characteristics of the patient groups can be referenced in Table 1.

Table 1 The Demographic Characteristics of Patients Among Three Groups in T2D Only, DKA, HHS

Blood Sampling and Methods of Laboratory Assessment

During the initial admission day, comprehensive blood sampling was conducted to evaluate metabolic, organ-specific, and tumor-related parameters. These assessments included measurements of serum glucose, pancreatic islet activity, hemoglobin A1C (HbA1C), serum tumor markers, plasma lipid levels, and assessments of various organ functions. Evaluated biochemical indicators include fasting blood glucose and renal function metrics alongside hepatic status, all processed through an advanced biochemical analyzer. HbA1C was analyzed separately using a dedicated system reflecting prior glycemic control. Additionally, tumor markers and other endocrinological assessments were evaluated through an automated chemiluminescence immunoassay platform. The urinary microalbumin-to-creatinine ratio (UACR) served as a critical indicator of renal performance.

Established Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and Homeostasis Model Assessment of β Cell Function (HOMA-β)

We employed the homeostasis model to gauge insulin resistance and β-cell capability across the patient categories using fasting glucose and C-peptide levels. HOMA-IR and HOMA-β calculations were conducted using an Oxford University-derived calculator (http://www.dtu.ox.ac.uk/), ensuring the inclusivity of glycemic levels and varying insulin metrics.

Statistical Analyses

We utilized statistical tools via the SPSS and Prism software for robust analysis of patient data across T2D-only, DKA, and HHS cohorts. The comparative review leveraged one-way ANOVA or variants tailored to data distribution, post hoc analyses adopted Tukey’s or Dunnett’s T3 tests. Correlation dynamics were examined using Pearson or Spearman methodologies, with p-value thresholds established for significance.

Results

The General Profile and Disequilibrium of Glucose Metabolism in T2D Only, DKA and HHS

In our initial exploration of demographic data, we observed notable age discrepancies among the groups categorized as T2DM only (mean age: 64.85±13.91 years), DKA (51±20.01 years), and HHS (78.51±12.21 years), with statistically considerable contrasts notably between the T2D-only and HHS cohorts.

Diabetic Ketoacidosis and Hyperosmolar Hyperglycemic State: Understanding Tumor Markers and Clinical Implications

Figure 1 The comparison of Age (A), blood glucose (FPG, 2hPPG) (B), HbA1c (C), GA (D), c-peptide (FPCP, 2hPPCP) (E), HOMA-IR (F), GAD (G), IAA (H), and ICA (I) between the T2D, DKA, and HHS groups.

Abbreviations: BG, blood glucose; FPG, fasting plasma glucose; 2hPPG, 2 hours postprandial plasma glucose; HbA1c, glycated hemoglobin A1c; GA, glycated albumin; FPCP, fasting plasma c-peptide; 2hPPCP, 2 hours postprandial plasma c-peptide; HOMA-IR, homeostatic assessment model of insulin resistance; GAD, glutamic acid decarboxylase autoimmune antibody; IAA, insulin autoimmune antibody; ICA, islet autoimmune antibody.

Note: *p

The Elevated Tumor Markers in HHS When Compared to DKA and T2DM Only

In comparing the serum levels of tumor markers across T2D-only, DKA, and HHS cohorts, we noted significant elevations in CA199, CEA, CPSA, and PSA among patients in the HHS group relative to those in DKA and T2DM-only groups. Specifically, CA199 levels in T2DM were significantly lower at 20.90±17.42 U/mL compared to 42.35±98.03 U/mL in those with HHS (Figure 2).

Figure 2 The comparisons of elevated tumor markers including AFP (A), CA125 (B), CA153 (C), CA199 (D), CEA (E), CPSA (F), PSA (G), and LDH (H) between T2D, DKA, and HHS groups.

Abbreviations: AFP, α-fetoprotein; CA125, cancer antigen 125; CA153, cancer antigen 153; CA199, cancer antigen 199; CEA, carcinoembryonic antigen; CPSA, complex prostate-specific antigen; PSA, prostate-specific antigen; LDH, lactate dehydrogenase.

Note: *p

The Trend of Thyroid Function Decline in DKA and HHS Among Three Groups

We noted a significant decline trend in thyroid function indicators, particularly FT3 levels, across the groups compared. These alterations align with the severity of the underlying diabetic conditions observed.

Figure 3 The comparisons among T2D-only, DKA, and HHS groups in respect of thyroid function: FT3 (A), FT4 (B), TT3(C), TT4(D), TSH(E), TPOAb (F), TgAb (G), and Tg (H).

Abbreviations: FT3, free triiodothyronine; FT4, free thyroxine; TT3, total triiodothyronine; TT4, total thyroxine; TPOAb, thyroid peroxidase antibody; TgAb, thyroid globulin antibody; Tg, thyroid globulin.

Note: **p

The Spectrum of Lipids in DKA and HHS Varies Between Three Groups

The evaluation underscored notable alterations in lipid profiles among the groups, with total cholesterol and triglyceride levels exhibiting significant variances. These improvements suggest a potential cardiovascular risk among patients diagnosed with DKA.

Figure 4 The spectrum of plasma lipids (A); APOA1(B); APOA2(C); APOB(D); APOE(E); LPa(F); sdLDL(G), differs among T2D alone, DKA, and HHS groups.

Abbreviations: TC, total cholesterol; TG, triglyceride; HDL, high-density lipoprotein; LDL, low-density lipoprotein; APOA1, apolipoprotein A1; APOA2, apolipoprotein A2; APOB, apolipoprotein B; APOE, apolipoprotein E; LPa, lipoprotein a; sdLDL, small dense low-density lipoprotein.

Note: *p

The Impairment of Hepatic Function in DKA and HHS Was Compared to That of T2DM-Only Patients

Noteworthy differences in hepatic function parameters emerged, highlighting the compromised state in DKA and HHS compared to T2DM-only patients, particularly regarding total protein content.

Figure 5 Comparisons of hepatic function based on protein content (A); A/G(B); proalbumin (C); bilirubin (D), transferase (E), AST/ALT (F); γ-GGT (G), and Bile acids (H).

Abbreviations: TP, total protein; ALB, albumin; GLO, globin; TBiL, total serum bilirubin; DBiL, direct serum bilirubin; SBiL, indirect serum bilirubin; γ-GGT, γ-glutamyl transpeptidase.

Notes: *p

The Impaired Renal Function in DKA and HHS Compared to the Patients with T2DM Only

Our renal function assessments revealed considerable elevations in renal injury markers predominantly in the HHS cohort, including increased blood urea nitrogen (BUN) levels, reflecting significant kidney impairment.

Figure 6 The presentation of impaired renal function in terms of BUN (A), SCr (B), Uric acid (C), CysC (D), UACR (E) among T2D only, DKA, HHS.

Abbreviations: BUN, blood urea nitrogen; Scr, serum creatinine; CysC, cystatin C; UACR, urinary albumin-to-creatinine ratio.

Notes: ****p

The Disparity in Electrolyte and Iron Assessment Among T2DM Only, DKA, HHS

Electrolyte and iron analyses indicated a substantial difference in sodium concentration among the groups, illustrating the distinct biochemical environment present in patients with DKA and HHS.

Figure 7 The comparisons of serum electrolytes containing natrium (A), potassium (B), chlorine (C), CO2 binding (D); calcium (E), phosphorus (F), iron (G), magnesium (H) among groups T2D only, DKA, HHS.

Abbreviation: Cl, chlorine.

Notes: **p

The Cardiac Injury in the Patients Among the Patients with T2DM, DKA and HHS

We found significant elevations in markers indicating myocardial damage across DKA and HHS cohorts, showcasing potential risks associated with acute diabetic complications. Nevertheless, markers indicating heart failure did not reflect considerable alterations in the studied populations.

Figure 8 The comparisons of markers of heart failure, cardiac injury among groups of T2D only, DKA, and HHS: BNP(A); MYO(B); NT-ProBNP(C); cTNI (D); CK(E); CKMb (F).

Abbreviations: BNP, Brain-type natriuretic peptide, MYO, myoglobin, NT-proBNP, N-Terminal Pro-Brain natriuretic peptide, cTNI, cardiac troponin I, CK, creatine kinase, CKMb, creatine kinase-Mb.

Notes: *p

The Relationship Between the HHS States and Tumor Markers and Cardiac Injury

Table 2 The Spearman Nonparametric Analysis Reveals Relationship Between Osmolar, HbA1c, Iron and Tumor Markers, Cardiac Injury Markers in HHS

The Spearman Nonparametric Analysis Reveals Association Between DKA, Tumor Markers, Reduced Hepatic Function, and Cardiac Injury

Table 3 The Relationship Between pH, HbA1c, and Tumor Markers, Cardiac Injury Markers in DKA

The Multilinear Regression Models for the Independent Variables Associated with the Change of CEA and CA199 in HHS and DKA

Table 4 The Multilinear Regression Model Shows the Significant Variables to the CEA Changes in HHS

Table 5 The Multilinear Regression Model Shows the Significant Variables to the CA199 Changes in DKA

The Predicted Value of Regression Parameters in HHS and DKA for CEA and CA199

Figure 9 The predict value of established multilinear variables for the CEA in HHS represented by FPCP(A), cTNI (B), Osmolar (C), SCr (D), TSH (E), HbA1c (F). The Cut-off, sensitivity, specificity, and AUC were annotated in the Fig. below the curve.

Abbreviations: FPCP, fasting plasma C-peptide; cTNI, cardiac troponin; SCr, serum creatinine; TSH, thyroid-stimulating hormone; HbA1c: Glycated hemoglobin A1c.

Figure 10 The predict value of established multilinear variables for the CA199 in DKA represented by Globin (A), and tCO2 (B). The Cut-off, sensitivity, specificity, and AUC were annotated in the Fig. below the curve.

Abbreviation: tCO2, total CO2 concentration in plasma.

Discussion

This study delineated a multifaceted profile of DKA and HHS, confirming that patients presenting elevated levels of tumor biomarkers alongside acute diabetes complications face heightened cancer risks. The revealed alterations in serum tumor biomarkers were intertwined with diverse metabolic conditions, fostering concerns over potential cancer susceptibility in this patient demographic. We emphasize the necessity for more tailored attention to distinct risk factors arising from DKA and HHS (Figure 11).

Figure 11 The summary of biomarkers of tumor, tracer nutrition and impaired thyroid, cardiac, hepatic and renal function among groups of T2D only, DKA and HHS. Re-examination of tumor markers including CEA, PSA and CPSA (indicated by the box) in DKA or HHS patients will benefit in the early diagnosis of specific tumors after their recovery from DKA and HHS. Iron supplement maybe also necessary for these patients.

Abbreviations: CEA, carcinoembryonic antigen; CPSA, complexed prostate specific antigen; and PSA, prostate specific antigen; LDH, lactate dehydrogenase; CA199, cancer antigen 199; Fe, iron; HbA1c, glycated hemoglobin A1c.

We also compared thyroid function among the three groups. This phenomenon may be regarded as a functional adaptation of the thyroid to the reduced metabolic state of DKA or HHS, known as non-thyroidal illness syndrome. There is no overt thyroid impairment. Non-thyroidal illness syndrome can be observed in a variety of severe systemic diseases, and its primary treatment is the resolution of the underlying illness.28–30

We also investigated the lipid spectra of DKA and HHS. These findings signify that lipid imbalances may be more prominent in DKA, attributed to excessive ketone production and altered glucose metabolism. Patients with HHS exhibited higher levels of APOA1, indicating early significant changes in HDL.

Elevations in BUN, SCr, Uric acid, and cystatin C—renowned early markers of kidney injury—alongside a decrease in UACR, unveiled the presence of pronounced renal impairment in the HHS cohort. Such changes may arise from considerable body fluid loss, leading to renal hypoperfusion and oliguria.

Moreover, significant shifts in markers related to cardiac injury and failure were evident, reflecting the intricate interplay between acidosis, hyperosmolarity, and cardiac performance; however, significant heart failure was not demonstrated. Moderate increases in myocardial damage markers did not indicate acute coronary syndrome but warrant careful management to prevent severe cardiac damage in DKA and HHS.

Despite CA199 association with metabolic parameters in DKA, only globin and tCO2 emerged as significant predictors of CA199 levels (Table 5). This implies that normalizing patient conditions may facilitate CA199 release, suggesting required investigations into liver protein synthesis alterations and immune responses amid infections or inflammation.

Conclusion

The findings from this study indicate a robust elevation of CA199 in DKA patients, while CEA, PSA, and CPSA surged in the HHS group. Additionally, we assessed correlations between these tumor markers and critical clinical parameters, identifying various predictive factors associated with tumor markers in both DKA and HHS populations.

Ethical Statement

The research protocol received ethical approval from the Shanghai Pudong Hospital (WZ-010). Informed consent was obtained from all participants prior to their involvement in the study, conducted in accordance with the Declaration of Helsinki and using anonymized data.

Acknowledgments

We express gratitude to the staff of the Shanghai Pudong Hospital for their invaluable support in this study.

Author Contributions

Funding

This research was supported by multiple funds, including the Integrated Traditional Chinese and Western Medicine (YC-2023-0404) and Fudan Zhangjiang Clinical Medicine Innovation Fund Project (KP0202118).

Disclosure

The authors declare no conflicts of interest in relation to this study.

This paper has been uploaded to [SSRN] as a preprint:[[https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4732714].

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Sure, let’s dive into this complex medical article in a way that’s as sharp as my wit and as engaging as a well-timed punchline. We’re tackling the grave matters of diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS) — sounds like something you’d order at a very niche coffee shop, but trust me, it’s a lot less relaxing.

### The DKA vs HHS Showdown: Who Will Come Out on Top?

Both DKA and HHS are like the unwanted guests at the diabetes party—showing up uninvited and making things incredibly uncomfortable. They both wreak havoc with dangerously high blood sugar levels, but they do it in slightly different styles. DKA rolls in with ketosis and stomach-churning symptoms like nausea and vomiting, while HHS takes a more laid-back approach, often showing up in older, unsuspecting patients with far more severe hyperglycemia. Seriously, you don’t want to be in the same room as either of them.

Interestingly, DKA prefers to hang out with younger crowds—think type 1 diabetes, while HHS converses more with the elderly who conveniently forget to maintain their diet control. It’s the medical equivalent of “the youth today!” versus “maybe just a little extra cake won’t hurt!”

### What’s the Deal with Tumor Markers?

Now, let’s talk about those tumor markers that the article mentions like they’re the newest fashion trend. We’re diving right into the nitty-gritty — the researchers are trying to figure out if there’s any correlation between elevated tumor markers and the havoc wreaked by DKA and HHS.

And here’s the real kicker: while everything else in body chemistry might go haywire, the tumor markers like CA199 and CEA are saying, “Hey, look at us!” Turns out they might point to a higher cancer risk among our unfortunate contestants. It’s like a game of poker where these poor patients might get dealt a bad hand not just from diabetes but from a lurking cancer risk as well.

### A Look Inside the Lab: Methods and Madness

The study itself seems solid. They’ve got a decent sample size, and they’re measuring everything from blood glucose and cholesterol levels to various tumor markers, which sounds like a medical buffet. One can almost hear the lab technicians humming away, working through samples as if they were crafting a fine wine. And yet, one can’t help but wonder: did anyone tell the patients they were participating in an intense medical scavenger hunt? Because that’s essentially what this study is.

They even excluded patients with other conditions like hypertension or prior cancers—smart move, like a bouncer turning away the rowdy guests who might detract from the evening’s main event. Everybody wants a clean slate, right?

### Results that Tell a Story: The Science Behind the Numbers

The article mentions disparities in results not just in blood glucose but also in lipid profiles and renal function, making it clear: diabetes isn’t just a one-horse show. The data suggests the utter chaos that ensues when DKA and HHS take over. Myoglobin levels skyrocket in the presence of injury to the heart, and it seems that every time they measure something, they find these conditions leave quite a mark.

To put it bluntly, the results show that when you let these conditions run wild, they don’t just affect the blood sugar. They bring along their friends—kidney dysfunction, liver woes, and a host of cardiac concerns. It’s like the worst kind of family reunion.

### Conclusions Worth a Second Look

The study concludes that not all tumor markers rise and fall the same way across DKA and HHS patients. It’s like spotting your relatives at that chaotic reunion—some are friendly and easy to track, while others are slippery and skip the conversation entirely.

This should definitely raise alarms for the medical community, because if DKA and HHS patients show increased CEA, CA199, and PSA levels, the stakes might be higher than just blood sugar control.

### Wrapping It All Up

In the grand finale of our medical rollercoaster ride, what can we glean? Well, alongside the routine management of diabetes, we might want to look into those tumor markers and consider a proactive cancer screening strategy in patients who find themselves in acute diabetic situations.

At the end of the day, this isn’t just another boring medical paper. It’s a poignant reminder that chronic conditions like diabetes can sometimes usher in even graver health crises. So, folks, let’s take our health seriously and appreciate the complexity of diabetes before it shakes us off our feet – literally and metaphorically.

Now, if only managing our health were as easy as managing a Netflix queue—a little less drama and a lot more fun! But alas, life isn’t a comedy show, and this is serious business.

Stay healthy, stay informed, and remember: even when life throws curveballs, a little laughter never hurt anyone!
Ure something, it’s like uncovering yet another layer of complexity in the diabetes saga.‌

In terms of statistical significance,‌ the⁣ researchers have done ‌their homework, using sophisticated methods to ensure that their findings aren’t just a statistical fluke. They’ve likely performed regression ‍analyses to tease apart the relationships among diabetes-related crises, tumor markers, and‌ other complications. It’s‌ like watching a seasoned magician​ pull rabbits out of different hats—except instead of rabbits, it’s critical health insights about how⁢ these conditions interrelate.

### So, What’s Next?

The conclusions drawn from‌ the data presented in the article raise‌ vital points about early ⁣intervention and the need for rigorous monitoring of those with diabetes. For practitioners, ‍it’s not just⁣ about putting out fires when DKA or HHS strikes; it’s about being proactive and keeping ‍an eye ‌on those tumor markers as potential indicators of underlying issues,‍ like a carefully-scheduled checkup with life’s ⁢unexpected twists.

The article likely concludes with a clarion ⁤call‌ for ​further ‌research to confirm ⁢these relationships and explore the‍ underlying mechanisms ​in more detail. Can we make the leap from correlation to causation? That’s the million-dollar question,‌ and one that researchers will be tackling⁣ in laboratories and clinics⁢ alike in the future.

### Final Thoughts

the ⁢battle against DKA and HHS⁣ is far ‍from ​over, and the emerging⁤ data about tumor markers suggests there is much ⁣more to unravel in this intricate web of diabetes complications. So, as healthcare practitioners arm themselves with new knowledge, one can only hope that the next chapter in this⁤ ongoing⁤ saga will bring clarity, innovative solutions, and⁤ perhaps a little humor to lighten⁣ the burden of⁣ such serious conditions. Because,⁣ after all, if we can tackle diabetes with a smile—or at least a well-placed pun—maybe ⁣we can make the world just a ⁢bit ⁣healthier,⁤ one laugh at a time.

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