Subscribe to our Newsletters !!
In the era of changing pharmaceutical innovation p
The pharmaceutical sector is on the cusp of a new
The Nobel Prize in Physiology or Medicine awarded
Shilpa Medicare – the full-service contract de
A few months b Pharma News
A few months b
Since it’s an ingredient in so many foods, you h
Dear Readers, Welcome to the latest issue of Micr
Both in the lab and in the clinic, thermometers are important tools. Their use in a laboratory differs greatly from its use in a clinical setting. Both types of instruments measuring temperature employ differing design features, requirements for accuracy, standards for calibration and application. In this article, we explain the differences between laboratory and clinical thermometers so that professionals may be appropriately guided.
Clinical Thermometers: Used in healthcare to check patients’ body temperature for diagnosis of fever, infections, and other issues.
Laboratory Thermometers: Used in experiments and processes to measure chemical or environmental temperatures.
Clinical: Typically 35°C to 42°C, with some showing Fahrenheit too.
Laboratory: Ranges from -10°C to 110°C or more depending on application.
Clinical: Often mercury or digital, with a narrow capillary and constriction for peak temperature reading.
Laboratory: Rugged and continuous monitoring types without constriction; may be mercury, alcohol, or digital.
Clinical: High sensitivity, ±0.1°C accuracy for diagnostics.
Laboratory: Often comply with NIST or ISO standards for precise calibration.
Clinical: Use of disposable covers or non-contact thermometers to avoid contamination.
Laboratory: Focus on chemical resistance and durability; mercury use is declining due to safety concerns.
Clinical: Bluetooth, memory features, and EHR integration. Laboratory: USB data logging, automation system integration.
No single thermometer fits all needs. Clinical types are patient-centric, emphasizing hygiene and speed. Laboratory thermometers support varied precision tasks in science and industry. A deeper understanding helps ensure compliance, safety, and reliable data in both contexts.