Fever Curves - What Can They Tell Us?
COVID-19 has made humanity take note of their health like never before. This pandemic almost seems like yet another portentous reminder from nature that we are mortal creatures and our health is not to be taken for granted. One of the key symptoms of COVID-19 is a fever. Fever and sore throat are probably the earliest symptoms that you will notice if you are ill with the virus. So, what are fever curves? Could they somehow come in handy during this coronavirus crisis? In this article, we explain what fever curves are, talk about some typical fever patterns and explain how this could be relevant during this coronavirus pandemic.
Fever forms an integral part of the human body’s adaptive response against infectious diseases, traumas etc. Fevers involve a complex array of processes that involve cellular messengers (cytokines), pyrogens, the hypothalamus and various other peripheral agents involved in temperature change (Read more about the processes/mechanisms behind fevers). Because fevers are such a widespread and common manifestation of disease, understanding the intricacies and nuances associated with fevers became very important to the science of medicine. As modern medicine came into its own and instruments of thermometry became more and more sophisticated, we started identifying various types and patterns of febrile illness.
Types of Fever
Based on duration, fevers are sub-divided into acute, sub-acute and chronic fevers. Acute fevers are those that last for less than 7 days. They are characteristic of infections like URTIs (Upper Respiratory Tract Infections) and influenza. Sub-acute fevers last for no longer than 2 weeks. Examples of conditions that present with sub-acute fever include typhoid fever and abdominal abscesses. Fevers that last longer than 2 weeks are termed chronic fevers or persistent fevers and are seen in chronic infections such as HIV, tuberculosis, etc. However, it is important to understand that although these categories do serve a purpose in helping us classify febrile illness, they are arbitrary and don’t have hard lines of separation - i.e if left untreated, an acute fever can turn into a persistent one.
Based on the extent of temperature increase, fevers are classified into low-grade fever, moderate grade fever, high-grade fever and hyperpyrexia. The height of fever has significant diagnostic value and is therefore highly relevant in a clinical setting. High fevers often point to more severe illness but this is not always the case. The complete clinical picture is a better predictor of the severity of the illness and the prognosis.
|Low grade fever||38.1–39||100.5–102.2|
|Moderate grade fever||39.1–40||102.2–104.0|
|High grade fever||40.1–41.1||104.1–106.0|
When a physician is unable to identify the cause of fever in a patient, it is termed as an FUO (Fever of Unknown Origin).
(Read our article about some rare fevers that are extremely challenging to diagnose)
What are Fever Patterns/Temperature Curves?
When we take regular temperature readings and plot our readings on a graph over time, we get patterns that indicate the pattern of a fever. These graphs are called temperature curves and based on their progression over time, there are seven fever patterns.
Sometimes, fever patterns are highly specific to a certain disease and are therefore, extremely useful in diagnosis. This is especially true in cases like malaria, in which case the mechanism underlying the fever pattern is directly linked to the lifecycle of the causative organism (Plasmodium).
Febris continua or continuous fever refers to a fever curve which is characterised by sustained increase in temperature. The person has a temperature above 38°C [100.4°F] over a few days, with fluctuation of 1°C or less from morning to evening (over a period of 24 hours). However, during this period, the temperature doesn’t come down to normal.
Some examples of diseases that present with a continuous fever pattern are lobar pneumonia, typhoid, acute bacterial meningitis and UTIs (Urinary Tract Infections). A slow rise and high plateau are particularly characteristic of typhoid fever.
Febris remittens or remittent fever refers to a fever where there are daily fluctuations of 2°C or more, without the temperature ever touching normal. Such a curve can be observed in rickettsial infections, infective endocarditis, brucellosis etc.
Febris intermittens or intermittent fever refers to a fever pattern characterised by intervals - there is an interval wherein the temperature is elevated for several hours followed by a period where the temperature falls back to normal.
Malaria, Borrelia, Schistosomiasis and Kala Azar are a few examples of diseases where an intermittent fever curve can be observed. Malarial infections are especially recognisable for their distinct fever curves. Depending on the species of Plasmodium causing the infection, the periodicity of the intermittent fever can be every 24 hours (quotidian pattern - P.falciparum), 48 hours (tertian pattern - P.ovale and P.vivax) or 72 hours (quartan - P.malariae).
Febris recurrens or recurrent fever refers to a fever pattern characterised by three or more episodes of febrile illness (fever) in a six-month period, each occurring at least 1 week apart, with no obvious underlying illness. This fever pattern is largely seen in children.
Febris recurrens is most commonly associated with PFAPA syndrome (Periodic fever, Aphthous ulcers, Pharyngitis, Adenopathy).
Febris undulans or undulating fever refers to a temperature curve characterised by gradual rises in temperature followed by gradual decreases, subsequently followed by an afebrile period until the fever begins again.
This type of curve is characteristic of infections caused by some species of Brucella (Brucellosis).
Febris irregularis or irregular fever refers to a fever pattern that has an irregularly fluctuating curve. There are no regular patterns in such curves. Such fever curves are extremely common among children and can be seen in diseases such as chronic bronchitis and rheumatism.
Febris hectica or hectic fever refers to a pattern characterised by sharp swings in temperature - dramatic spikes of up to 3°C followed by periods of chills and profuse sweating. Most commonly seen in active pulmonary tuberculosis and sepsis.
How are Temperature Curves Significant?
Medical students often find that practising medicine in the real world is very different from the simulations that they went through in medical school. Much in the same way, in real-life medical practice, the fever patterns that are described above are not often observed, as they are. This is because, there can be a number of confounding variables such as patients ingesting antipyretic drugs even before they seek medical treatment, multiple infections occurring at the same time, diminished febrile response etc.
Therefore, although it is vital for any aspiring physician to acquaint himself/herself with these curves, they seldom ever appear as cleanly as described above, in patients.
Nevertheless, this is not to say that they do not have any clinical utility. With diseases such as malaria and typhoid, the fever patterns are extremely unique and immediately recognisable. Moreover, fever curves offer important diagnostic clues, especially in low-resource settings where more sophisticated forms of testing and diagnosis are often not available.
Temperature curves can be especially useful in terms of their negative diagnostic value; i.e. they can be used to eliminate improbable diagnostic options and therefore help streamline the process of diagnosis towards options that are more likely.
During this coronavirus pandemic, one of the biggest problems faced by the medical establishment is being able to perform effective triage - i.e separating patients based on the severity of their clinical picture.
Continuous Fever Monitoring
In the past, fever patterns/temperature curves either existed in the purely theoretical/academic realms of medical textbooks and examinations or were limited to hospitals where diligent nursing staff would take several temperature readings every day and painstakingly plot fever trends, on the off chance that the curve could help clinch an elusive diagnosis.
However, in today’s world of super-processors and big data, temperature trends are no longer going to be confined to the arcane world of hospitals and healthcare professionals.ONiO gives you perpetual access to accurate and reliable time-series data on your core body temperature. It makes it possible for you to view trends in your body temperature, over periods of time. Whether you want to track your temperature trends to hack your workout and take it to the next level or you want to stand a chance at knowing more about what you’re going to come down with just as you’re starting to feel unwell - the future is here!
Fever curves or temperature curves can be an effective diagnostic tool in the hands of a competent physician. Owing to the vastness of the health sciences, physicians have to employ a wide range of skills and tools to make sure that their diagnoses are spot-on.
Fever curves are very useful, especially, in terms of negative diagnostic value. It can help a doctor rule out certain conditions during his/her early assessment of a febrile patient. Moreover, some infectious diseases such as malaria come with their own classical fever pattern, which then can even have positive diagnostic value.
So, how is all this relevant to the present COVID-19 situation? Temperature patterns could potentially and doctors and healthcare professionals to differentiate COVID-19 patients from patients who present with similar symptoms but have contracted a different/less serious pathogen.
This could be a handy diagnostic tool especially if continuous temperature monitoring technology such as ONiO.temp is used, wherein detailed time-series temperature data is available to the physician. Right now, triage is a huge pain point for medical establishments all over the world. Sorting and prioritising of patients who are most in need of care is proving to be a major problem for medical institutions all over the world. Fever curves could be a reasonably effective tool for this.