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Published on: Sep 26, 2021
3 minute read
By: Second Medic Expert

What Is The Meaning Of Pre-diabetic?

What is the meaning of pre-diabetic?

Pre-diabetes is the stage that comes before type 2 diabetes. If blood sugar levels are high but not yet high enough to be classified as type 2 diabetes, then you are pre-diabetic.

A person may have pre-diabetes if they find it hard to control their blood glucose levels.

It is important to note how long you have had this condition and what your other risk factors are like such as age, history of gestational diabetes, history of cardiovascular disease, family history (genetic heritability), obesity (BMI > 30), physical inactivity.

Pre-diabetic people tend to be insulin resistant or sensitive when they're not eating anything, and the fasting level is high at 138 mg/dl and when they're drinking glucose their fasting level goes up even more and after a meal, their blood sugar goes up higher than 140 mg/dl at least two times in 225.

Someone affected by pre-diabetes has an impaired ability to produce insulin, which is necessary to regulate glucose levels. This could lead to high blood sugar over time. People who are pre-diabetic may suffer from polycystic ovary syndrome (PCOS), normal aging or another illness that causes the pancreas to fail to work properly. A person suffering from pre-diabetes is suffering from high blood sugar levels. A person suffering from diabetes not Type 1 is suffering from high blood sugar levels.

Sometimes people are diagnosed with pre-diabetes instead of Type II Diabetes because it's more common in the population. Pre-diabetes occurs when the body cannot produce enough insulin or process glucose properly to regulate blood sugar, but that can be managed through diet and exercise in most cases.

Type I Diabetes is when a person cannot make any insulin at all, whereas type II might be caused by, for example, an unfortunate metabolic issue or lifestyle change like eating too many sweets or quitting smoking.

Pre-diabetic refers to a person who has blood sugar levels that qualify him or her as "pre-high blood glucose" but not high enough to be considered diabetic yet. Pre-diabetes is a temporary condition in which the body starts to develop insulin resistance, and the cells of your pancreas start secreting more and more of their own insulin to avoid producing too much glucose. Eventually, this becomes counterproductive, the pancreas becomes so resistant it can't keep up with demand anymore, and type 2 diabetes occurs. However, pre-diabetes does not require any treatment because by avoiding junk food and excessive portions (and exercising) you will likely get off pre-diabetics without ever developing diabetes. Pre-diabetes is a term to describe high blood insulin levels that are on the cusp of developing type 2 diabetes but haven't yet.

Type 2 diabetes develops when cells lose their insulin receptors and cannot create enough sugar for themselves. This means the body has to produce more and more insulin in order to get glucose into any cells with remaining insulin receptors (such as muscle or fat cells). Over time, high levels of circulating hormones lead to damage in the small vessels that provide oxygen and nutrients — particularly to kidneys — putting them at risk of failure. This can happen over decades and is referred to as "insulin resistance".

The primary goal for people suffering from pre-diabetes should be lifestyle change: reduce weight. Pre-diabetic means that you are at high risk for developing type 2 diabetes. If you're overweight, have a family history of diabetes, develop gestational diabetes while pregnant, or if it runs in your household then pre-diabetes is more likely to progress into type 2 diabetes.

Pre-diabetic means that a patient has been diagnosed as prediabetic – that is, their blood sugar levels are higher than normal but not yet high enough to be classified as having diabetes. People with pre-diabetes have a greatly increased risk of developing type 2 diabetes and cardiovascular disease. One study found that adults who had one or more characteristics of the metabolic syndrome exhibited a 46% reduction in risk for the development of diabetes over 4 years following blinded diagnosis if they took metformin therapy alone or with other agents, compared to those on placebo therapy. In addition, people with pre-metabolic syndrome specifically were found to have 89?creased risks for this development

The term pre-diabetic is typically applied to patients who have impaired glucose tolerance or who are at risk for developing type 2 diabetes. A patient is considered a pre-diabetic when he or she has high blood sugar levels that may lead to progression into full-blown diabetes, called Type 2 Diabetes Mellitus, but doesn't meet the diagnostic criteria for T2DM. In other words, the cells of this patient's body aren't quite as dysfunctional as those of a diabetic, yet they show signs of dysfunction. This stage falls between normal and diabetic and is sometimes referred to as prediabetes because it puts an individual at "risk" for T2DM development.

A pre-diabetic person is one who exhibits signs that they may be diabetic. The symptoms include stomach pains, frequent urination, and sudden weight loss. Pre-diabetes used to be known as age-related diabetes and are common in adults who are overweight and have high blood pressure or abnormal cholesterol levels. Early-onset of pre-diabetes can lead to both short-term and long-term risks including heart disease, strokes, kidney failure, blindness caused by diabetic retinopathy (Eye) as well as early death for people with type 2 diabetes.

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How Artificial Intelligence Is Transforming Patient Care in India

As a clinician working closely with patients across urban clinics and remote teleconsultation setups, I have seen firsthand how delayed diagnosis, fragmented follow-up, and specialist shortages affect outcomes in India. Artificial intelligence is not a futuristic concept in Indian healthcare anymore. It is actively reshaping how we diagnose diseases, monitor patients, and prevent complications.

AI, when used responsibly under clinical supervision, is becoming a critical support system for doctors and a powerful safety net for patients navigating a complex healthcare ecosystem.

Why India’s Healthcare System Needs AI

India’s healthcare challenges are deeply structural. A large population burdened by lifestyle diseases, combined with uneven access to medical expertise, creates gaps that traditional systems struggle to bridge.

In daily practice, we increasingly see patients presenting late with diabetes, hypertension, heart disease, or cancer. Many ask a simple but important question: why was this not detected earlier? The answer often lies in limited screening, overloaded clinicians, and lack of continuous monitoring.

Chronic conditions dominating Indian clinics today include:

Diabetes affecting over 100 million individuals.
Hypertension rising even among young adults.
Cardiovascular disease driven by late detection.
Increasing cancer incidence with delayed diagnosis.

AI matters here because it supports earlier identification of risk patterns, reduces diagnostic delays, and allows clinicians to focus on decision-making rather than data overload.

How AI Is Changing Medical Diagnosis

One common concern patients raise during consultations is whether AI can truly diagnose diseases accurately. In practice, AI does not replace a doctor. It acts as a high-speed analytical assistant.

AI in Imaging and Diagnostics

AI systems can rapidly analyse:

X-rays and CT scans.
MRI images.
Mammograms.
Pathology slides.
Cardiac and neurological imaging.

These tools flag abnormalities within seconds, allowing doctors to prioritise critical findings. Clinical studies published in peer-reviewed journals have shown that AI models can match specialist-level accuracy for specific imaging tasks when used correctly.

From a physician’s perspective, the real benefit is not speed alone. It is consistency. AI reduces the risk of missed findings during high-volume diagnostic workflows, especially in resource-constrained settings.

Can AI Monitor Patients Outside Hospitals

Patients managing chronic illness often ask whether technology can help them avoid repeated hospital visits. AI-enabled remote monitoring is one of the most meaningful advances in this area.

AI-Supported Remote Patient Monitoring

AI continuously evaluates trends in:

Blood pressure.
Heart rate variability.
Blood glucose patterns.
Oxygen saturation.
Physical activity and sleep quality.

Rather than reacting to a single abnormal value, AI identifies worsening trends over time. Clinically, this allows early intervention before complications escalate.

Evidence from global health system studies shows that continuous monitoring can significantly reduce avoidable hospital admissions, particularly for diabetes, heart disease, and elderly patients.

Using AI to Predict and Prevent Chronic Diseases

Preventive healthcare remains underdeveloped in India. Most patients seek care after symptoms appear. AI helps shift this model.

By analysing medical history, lifestyle habits, vitals, and environmental factors, predictive models can estimate:

Future heart attack risk.
Progression of diabetes.
Decline in kidney function.
Stroke probability.
Asthma exacerbation triggers.

Patients often ask if AI can really prevent disease. Prevention here means early warnings. When risk patterns are detected early, doctors can adjust treatment plans, recommend lifestyle changes, and prevent irreversible damage.

Personalised Treatment in a Diverse Indian Population

Indian patients differ widely in genetics, diet, stress patterns, and cultural habits. Standardised treatment protocols often fall short.

AI supports personalised care by analysing:

Medication responses.
Dietary intake.
Blood markers.
Sleep and stress trends.
Coexisting medical conditions.

For example:

In diabetes care, AI helps personalise carbohydrate distribution and medication timing.
In hypertension, it identifies sodium sensitivity and stress-related spikes.
In hormonal conditions like PCOS, it aligns nutrition and activity with cycle patterns.

From a clinical standpoint, personalised insights improve adherence and reduce relapse rates.

AI-Enabled Telemedicine and Smarter Consultations

Telemedicine has become an essential part of care delivery in India. Patients frequently ask whether online consultations are as effective as in-person visits.

AI enhances telemedicine by:

Structuring symptom inputs before consultations.
Routing patients to the appropriate specialist.
Generating concise medical summaries for doctors.
Supporting follow-up reminders and medication adherence checks.

When used correctly, AI reduces diagnostic delays and improves consultation efficiency without compromising safety.

Expanding Healthcare Access Beyond Cities

A major question in public health is whether AI can truly improve rural healthcare access. In practice, it already is.

AI enables:

Remote diagnostics supported by portable devices.
Virtual specialist consultations for rural clinics.
Smartphone-based imaging and screening tools.
AI-guided triage in underserved regions.

By reducing dependence on physical proximity to specialists, AI helps bridge longstanding geographical barriers in India’s healthcare system.

Safety, Ethics, and the Role of Doctors in AI Care

Patients rightly express concern about safety, privacy, and over-reliance on technology. These concerns are valid.

Responsible AI use in healthcare requires:

Transparent algorithms.
Explicit patient consent.
High-quality, verified medical datasets.
Strict data privacy safeguards.
Continuous clinical supervision.

In ethical practice, AI outputs never replace medical judgment. Doctors remain accountable for decisions. Human-in-the-loop verification is essential to ensure patient safety and trust.

What This Transformation Means for Indian Patients

Artificial intelligence is fundamentally changing patient care in India by making healthcare more proactive, more precise, and more accessible. From early diagnosis to personalised treatment and continuous monitoring, AI empowers both patients and clinicians with data-backed clarity.

SecondMedic’s patient-first approach integrates AI as a clinical support system, not a replacement for doctors. By combining medical expertise with digital intelligence, the goal remains simple: better outcomes, earlier intervention, and care that adapts to each patient’s real-world needs.

As clinicians, our responsibility is to ensure that technology serves patients ethically and effectively. When used with care and oversight, AI has the potential to redefine healthcare delivery across India in a way that is inclusive, preventive, and sustainable.

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