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Published on: Apr 30, 2020
3 minute read
By: Dr Rajan Choudhary

COVID AND CLOTTING: A BRIEF LOOK

At the Mount Sinai hospital, a case series of five patients have been put together, ready to be published in the New England Journal of Medicine. It details patients aged 33, 37, 39, 44, and 49 who all began to experience a sudden onset of symptoms including slurred speech, confusion, drooping on one side of the face, and feeling dead in one arm. At the time of writing one has sadly died, two remain hospitalized and one is in rehab. Only the youngest is able to speak. All of them were found to be COVID positive.

This drastic case series highlights a growing problem of strokes and clotting disorders in COVID patients, one noted by medics across the world. This blog looks at whether this is a common occurrence and what may be causing it.

Before reading this blog it will be helpful to read our previous blog on why and how blood clots.

THE START

In mid-February Tang et al published a paper noting that patients with abnormal clotting parameters were associated with a poorer prognosis. In their study, 11% of their patients died, but out of these patients, 71% had these abnormal parameters, compared to just 0.6% of survivors. The patients who died also demonstrated DIC (disseminated intravascular coagulation), a condition in which clotting is triggered in the patients' blood across the body, not just at the site of injury.

There is one major issue with this study. In most European hospitals patients receive anticoagulant medications on a daily basis. This is because lying in a hospital bed when ill can promote the formation of clots in your legs. Most hospitals in China do not provide this anticoagulation, but even then the incidence of clotting is remarkably high.

After this, the evidence begins piling up. 9th April, Cui et al found 25% of patients with severe COVID had clots in their legs, of which just under half died. Looking at a specific clotting parameter (D-DIMER) was remarkably accurate at predicting high-risk patients.

Italian doctors found in 16 patients in critical care with severe Acute Respiratory Distress Syndrome (a severe inflammatory condition caused by COVID) also had deranged clotting parameters.

French studies had found these sickest patients often had large clots in their lungs, blocking blood flow in the lung and causing severe issues in keeping the patient's blood well oxygenated.

Some studies showed even patients hooked up to artificial lungs (known as ECMO) were not safe from the problems caused by excessive clotting.

WHY?

So why is this occurring? As with everything in medicine, the answer is complicated and usually multifactorial. So we will simplify it.

We must look at the platelets in our blood. These fragmented cells have an important role in triggering the clotting cascade and creating a clot. During an infection white blood cells (important immune cells responsible for finding and destroying invading organisms) release many chemical signals around an infection site. This triggers platelets, the formation of small protein meshes that can literally net the viral particles in the blood.

But it looks like they have an anti-viral role as well. Researchers have found specialist receptors on platelets that recognize viruses in the blood, leading to the release of specialist anti-viral molecules that target and destroy the viruses. This is an interesting finding because it is white blood cells that are known to destroy invading organisms.

So how does it go wrong? In severe infections, there is a very large viral load, and this can cause an excessive response. Too many white blood cells release too many chemical signals, causing too many platelets to activate. The same thing can occur with the virus directly activating too many platelets at once. This results in clots forming in the blood throughout the body, including the lung and the brain. It is another instance of the body falling victim to its own protective mechanism.

A second problem is that as these platelets are activated, they and the clotting proteins in the patient’s blood are “used up”. This is dangerous, because without these platelets and clotting proteins the body is unable to stop any bleeding sites. Profuse bleeding can occur from small injuries, further complicating the treatment of the patient.

So what can be done?

Hospitals have already started looking at giving patients with severe COVID anticoagulation therapy. And it seems in patients with deranged clotting, giving anticoagulation therapy can lower mortality. The International Society on Thrombosis and Haemostasis (Clotting) has recommended that patients with severe COVID receive high dose anticoagulation medication to thin their blood, because these patients are at such high risk of clots. This regime will be used for hospital patients and those in critical care.

And what about for the everyday public? Should we be worried? So far the data suggests this is only happening in people suffering from severe symptoms of COVID. But the incident in New York certainly raises some questions, and it will be interesting to read their report in NEMJ. Should you panic and start taking anti-coagulant medication at home? Definitely not. But what you should do is be educated in the symptoms of common diseases caused by clots. Diseases such as strokes and DVTs.

STROKE

Remember, act F.A.S.T

Facial Droop on one side
Arm or hand on one side feels numb or weak with reduced power (same in one leg)
Slurred speech making it difficult to understand
Time to phone an ambulance

Other symptoms can include sudden loss in balance, sudden loss in vision in one eye, problems swallowing, and more.

DVT

Look out for a swollen, painful calf on one side that is hot to touch.

PULMONARY EMBOLISM

If you have a swollen, painful calf and are also having trouble breathing, with some sharp stabbing pain in your chest, contact the emergency services as soon as possible.

Dr Rajan Choudhary, UK, Chief Product Officer, Second Medic Inc

www.secondmedic.com

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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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