> For the complete documentation index, see [llms.txt](https://ourfuturehealth.gitbook.io/our-future-health/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ourfuturehealth.gitbook.io/our-future-health/data-types/clinic-measurements-data/poct-lipid-profile-data.md).

# POCT Lipid Profile data

## POCT Lipid Profile data

From July 2022 to December 2024, POCT lipid profiles (total cholesterol, HDL-C, LDL-C and triglycerides) were measured during participant clinic appointments. Participants attending clinic appointments within this period may therefore have associated POCT Lipid Data available.

For information on the main Clinic Measurements dataset and the appointment process see [Clinic Measurements data](/our-future-health/data-types/clinic-measurements-data.md). 

### What is POCT?  <a href="#what-is-poct" id="what-is-poct"></a>

Point-of-Care Testing (POCT) refers to sample collection and analysis performed at or near the participant rather than in a central laboratory. This enables rapid generation of results without laboratory processing.&#x20;

In lipid profiling, POCT uses capillary blood collected via finger-prick and applied to a test strip containing reagents that react with lipid components. These reactions generate signals that are converted into quantitative measurements of key lipid parameters:

* Total cholesterol (TC): the overall concentration of cholesterol in the blood, representing the combined levels of all cholesterol-containing lipoproteins.
* High-density lipoprotein cholesterol (HDL-C): a lipoprotein fraction involved in reverse cholesterol transport, carrying cholesterol from peripheral tissues to the liver; higher levels are associated with reduced cardiovascular risk.
* Triglycerides (TG): a type of circulating lipid that serves as an energy source; elevated levels are associated with increased cardiovascular and metabolic risk, particularly when combined with abnormal cholesterol levels.

Low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C) and the TC:HDL-C ratio were derived from POCT measurements of TC, HDL-C and TG using established calculations, either directly by the device or through post hoc calculation:

* Low-density lipoprotein cholesterol (LDL-C): a lipoprotein fraction responsible for transporting cholesterol to peripheral tissues; higher levels are associated with increased risk of atherosclerosis and cardiovascular disease.
* Non-high-density lipoprotein cholesterol (non-HDL-C): calculated as total cholesterol minus HDL, representing all atherogenic lipoproteins (including LDL); commonly used as a marker of overall cardiovascular risk.
* Total cholesterol to HDL cholesterol ratio (TC:HDL-C ratio): calculated as total cholesterol divided by HDL-C. This ratio reflects the balance between atherogenic and protective lipoproteins and is commonly used as an indicator of overall cardiovascular risk, with higher values associated with increased risk.

### Why use POCT for lipid profiling&#x20;

POCT enables rapid collection of lipid data during clinic appointments, providing immediate results for the participant and for the research platform. This makes it particularly useful for large-scale data collection in programmes such as Our Future Health. Furthermore, it has been shown to provide sufficiently accurate, reliable, and standardised measurements at scale, and can support the classification of individuals into broad cardiovascular risk categories.<sup>1</sup>

Compared with laboratory-based testing, POCT uses portable devices that operate within more limited analytical ranges and are more sensitive to environmental conditions, test strip quality, and device calibration. Consequently, strict quality control procedures were applied to ensure data integrity and suitability for research (see [#how-did-we-process-the-data-for-each-release-3](#how-did-we-process-the-data-for-each-release-3 "mention")).

POCT is primarily intended for screening and monitoring rather than diagnostic confirmation. Laboratory-based measurements remain the gold standard for definitive biochemical analysis. At present, some diagnostic data for cardiometabolic conditions related to cholesterol may be available through linked datasets (e.g. Hospital Episode Statistics), but this is typically limited to individuals who have had contact with secondary care services. Linkage to other sources of clinical and diagnostic records are planned for future releases<mark style="color:$danger;">.</mark>

### Why POCT lipid profiling matters for health research&#x20;

Blood lipids are key biomarkers in cardiovascular and metabolic health research. Lipid measurements are widely used to assess cardiovascular risk and to study the development and progression of cardiometabolic disease. Research uses include identification of early patterns of elevated cholesterol, detection of high-risk subgroups, stratification of cardiovascular risk within populations, and assessing trends and associations of lipid levels with other factors. Lipids data is also commonly used to investigate associations with conditions such as coronary artery disease, stroke, and atherosclerosis, and clustering with metabolic conditions such as hypertension, obesity and diabetes.

POCT measurements of lipids, in particular, enable large-scale, minimally-invasive data collection within clinical and community settings. This extends lipid profiling beyond traditional healthcare environments, improving the representativeness of population-level data by capturing individuals who may not otherwise undergo cholesterol testing. POCT is therefore well suited to studies examining population trends and risk distributions.

***

### How was our POCT data collected? <a href="#data-collection-procedures" id="data-collection-procedures"></a>

POCT lipid profiles were collected during routine participant clinic visits as part of the Our Future Health programme from July 2022 until December 2024.

At each appointment, lipid measurements were obtained using the Mission® Cholesterol POCT device and recorded contemporaneously within the data capture system.

Measurement metadata, including timestamps, indicators of repeat testing, and measurement status, were captured alongside the lipid values.

See the [Procedure for Clinic Measurements](/our-future-health/data-types/clinic-measurements-data/procedure-for-clinic-measurements.md)for full details of the POCT lipid profiling procedure.

#### The Mission® device

The Mission® Cholesterol device (ACON Laboratories, Inc., San Diego, USA) was selected as it was one of four devices that met the National Cholesterol Education Program (NCEP) required standard of evidence for bias and precision (bias ≤3%).<sup>2</sup> The device is a hand-held, battery-operated, software-driven reflectance spectrophotometer which gives clinically accurate results in about 45 seconds. The device uses the 'reflection photometry' technique, which is recognised as the most accurate method of analysing cholesterol components at point-of-care, including the introduction of repeat measurements and updates to input ranges.

#### What types of measurements did we collect?

The following lipids are obtained directly from the Mission® Cholesterol device:

* Total cholesterol (TC)
* High-density lipoprotein cholesterol (HDL-C)
* Triglycerides (TG)

Low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), and the total cholesterol to HDL-C ratio (TC:HDL-C) were subsequently derived using established calculations, as described below.

Measurements are reported in millimoles per litre (mmol/L), a unit of concentration representing the amount of a substance present per litre of blood.

**Device minimum and maximum measurement ranges**

The Mission® Cholesterol device has manufacturer-specified analytical limits describing the measurement capabilities of the system for each of the primary (non-derived) analytes. These are given in Table 1.

*Analytical measurement ranges in mmol/L for the Mission® Cholesterol POCT device*

| Field             | Min, mmol/L | Max, mmol/L |
| ----------------- | ----------- | ----------- |
| Total cholesterol | 2.59        | 12.93       |
| HDL-C             | 0.39        | 2.59        |
| Triglycerides     | 0.51        | 7.34        |

The Mission® Cholesterol device also has published clinical measurement ranges in its [U.S. Food and Drug Administration (FDA) approval documents](https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K163406) which are identical to the manufacturer-specified analytical ranges except for total cholesterol, for which the FDA-approved upper bound is slightly lower, at 10.36 mmol/L (400 mg/dL). Researchers should consider this information in the context of the requirements of their own study. We expect that measurements of total cholesterol between the FDA-approved upper bound and the maximum reportable by the device (12.93 mmol/L) are likely to reflect elevated total cholesterol levels.

For almost all POCT measurements, clinic staff were able to record values for the full analytical measurement ranges given in the table above. However, a very small proportion of appointments were conducted using early versions of the data capture system (referred to as the Clinical Staff Application or CSA) which had narrower input range limits. This affects approximately 0.8% of measurements. Further details are described under "Changes to data capture parameters" in the section [#how-did-we-process-the-data-for-each-release](#how-did-we-process-the-data-for-each-release "mention").&#x20;

#### Do all participants provide every measurement? <a href="#do-all-participants-provide-every-measurement" id="do-all-participants-provide-every-measurement"></a>

Not all participants book and attend an in-person appointment, and those who do may choose to skip some or all measurements. Data fields for measurements which may be skipped are referred to here as dynamic fields.

A second set of lipid measurements were obtained for participants whose initial TC values exceeded predefined clinical thresholds:

* ≥ 7.5 mmol/L if the participant was < 30 years of age or&#x20;
* ≥ 9.0 mmol/L if the participant was ≥ 30 years of age&#x20;

These repeat measurements were conducted during the same appointment to verify elevated readings and support risk stratification. A total of approximately 8,510 participants had two sets of measurements recorded.

Records for measurements that were not presented to a participant are recorded as NULL.

For comprehensive details on each dynamic field please download the POCT Lipid Profile logic file provided below. This file outlines the logic using pseudocode, including the relevant field names and measurement values.&#x20;

{% file src="/files/T98WW8m0tKOXB6YGHZ9G" %}
POCT lipid profile logic information
{% endfile %}

#### What additional variables are derived from the POCT lipid profile?

**Low-density lipoprotein cholesterol (LDL-C)**

Low-density lipoprotein cholesterol (LDL-C) is often referred to as “bad cholesterol” because elevated levels can contribute to the build-up of fatty deposits in the walls of arteries. Elevated LDL-C is associated with an increased risk of cardiovascular disease, including coronary artery disease and stroke. LDL-C is therefore an important metric in cardiovascular and metabolic health research, as it provides a key indicator of atherogenic risk and disease development.

Device-calculated LDL-C values were excluded due to several methodological limitations. The device uses the Friedewald equation,<sup>3</sup> which is valid only under specific conditions, including fasting status and appropriate triglyceride ranges. In this dataset, LDL-C values were recorded for non-fasting participants as well as in cases where triglyceride range assumptions were violated. Additionally, [internal validation](/our-future-health/data-types/clinic-measurements-data/poct-lipid-profile-data.md) identified higher systematic and proportional bias in device-calculated LDL-C.&#x20;

To address these limitations, LDL-C was recalculated using the updated Sampson NIH equation,<sup>4</sup> which provides improved accuracy across a wider range of lipid values and is less sensitive to triglyceride levels.

Recalculated LDL-C values were only generated for participants who met the inclusion criteria described above, meaning all available lipid measurements (first and, where applicable, repeat readings) were *within* the manufacturer-specified analytical boundaries. Any calculated LDL-C values below zero have been set to null.&#x20;

**Other derived variables**

Two additional lipid variables were derived for the dataset: non-HDL cholesterol and the total cholesterol to HDL-C ratio (TC:HDL-C).

Non-HDL cholesterol represents the total concentration of atherogenic cholesterol in the blood, while the TC:HDL-C ratio provides an overall indicator of lipid balance and cardiovascular risk.

The derived variables were calculated as follows:

* Non-HDL cholesterol: TC − HDL-C
* TC:HDL-C ratio: TC / HDL-C

As with LDL-C, derived variables were only calculated for participants with all lipid measurements within the manufacturer-specified analytical ranges.

#### How can I use POCT lipid profile with other clinic measurements?

For researchers wishing to use these variables in conjunction with the POCT lipid profile data, the POCT lipid profile table can be joined to the Clinic measurements table using the `PID` field.

We collect several health-related measurements including during the Our Future Health appointment (see [Clinic measurements data](/our-future-health/data-types/clinic-measurements-data.md) for more information):

* height (1 measurement)
* weight (1 measurement)
* waist circumference (1 measurement)
* blood pressure, heart rate and rhythm (2 to 3 readings)
* blood samples (2 x 6 ml EDTA tubes)

For details on other data collected during the appointment, including meta-data see [Clinic Measurements data](/our-future-health/data-types/clinic-measurements-data.md#what-other-data-is-collected-during-the-appointment)

A set of three clinic-level variables have also been derived and added to the Clinic Measurements table to enable grouping of appointments occurring within the same clinic, and under similar operational conditions. All variables are pseudo-coded and have been de-identified to remove any direct, geographically identifiable information.

***

### Version changes and developments <a href="#version-changes-and-developments" id="version-changes-and-developments"></a>

#### How has the appointment process changed over time? <a href="#how-did-we-process-the-data-for-each-release" id="how-did-we-process-the-data-for-each-release"></a>

For general information on how the clinic appointments have changed over time see [#version-changes-and-developments](#version-changes-and-developments "mention")

The POCT Lipid Profile data is a component of the Clinic Measurements dataset and uses the same appointment version indicator to describe substantive differences in the appointment process over time. Currently, there are two appointment versions, v1 and v2, which are recorded in the `APPOINTMENT_VERSION` field. See here for more details on how data are versioned in the release: [Clinic Measurements data](/our-future-health/data-types/clinic-measurements-data.md#how-do-we-use-major-and-minor-versioning)

**Operational mitigations and SOP updates**

Data collection was conducted across multiple sites and over several phases of the programme. During this period, updates were made to standard operating procedures (SOPs), staff training protocols, and device handling processes to improve measurement consistency.&#x20;

Operational mitigations included enhanced staff training on repeat measurement protocols and participant communication, updates to device optic check procedures, and improvements to environmental controls, such as temperature monitoring and test strip storage. In addition, logging of device identifiers and test strip batch numbers was introduced to improve traceability of measurements.

**Changes to the data capture parameters**

Input range limits within the data capture system that is used to record measurements (referred to as the Clinical Staff Application or CSA) have changed over time. A very small proportion (approximately 0.8%) of measurements were recorded on early versions of the Clinical Staff Application, which had input range limits that were, in some cases, narrower than the manufacturer-specified analytical limits of the POCT device (see below table).&#x20;

*Input range limits for data capture of POCT measurements in the CSA before 9 November 2022*

| Field             | Min, mmol/L | Max, mmol/L |
| ----------------- | ----------- | ----------- |
| Total Cholesterol | 2.59        | 10.36       |
| HDL               | 0.3         | 2.59        |
| Triglycerides     | 0.56        | 5.65        |

From 9 November 2022 (inclusive), the input range limits for POCT measurements were revised to improve consistency with device capabilities and data quality (see below table). Over 99% of appointments at which POCT measurements were recorded occurred after this change. Note that these revised input range limits are wider than the operational range of the device, but any values outside the device’s measurable range are excluded from data releases. See "Handling boundary values" [#are-there-any-other-quality-issues-i-should-be-aware-of-when-using-this-data](#are-there-any-other-quality-issues-i-should-be-aware-of-when-using-this-data "mention")

The changes to the POCT measurement input ranges occurred at a different time to other appointment version changes, and are *not* reflected in the values of the `APPOINTMENT_VERSION` field accompanying the data. Researchers can distinguish the pre- and post-change periods using the date **9 November 2022**, with all appointments on or after that date using the wider input ranges.

*Input range limits for data capture of POCT measurements in the CSA from 9 November 2022 onwards*

| Field             | Min, mmol/L | Max, mmol/L |
| ----------------- | ----------- | ----------- |
| Total Cholesterol | 0.1         | 19.9        |
| HDL               | 0.1         | 9.9         |
| Triglycerides     | 0.1         | 9.9         |

For more general details on how the appointment process has changed over time see the [Change log for Clinic Measurements appointment processes](/our-future-health/data-types/clinic-measurements-data/change-log-for-clinic-measurements-appointment-processes.md).&#x20;

#### How do we use major and minor versioning? <a href="#how-did-we-process-the-data-for-each-release" id="how-did-we-process-the-data-for-each-release"></a>

The POCT lipid profile data are versioned in the same manner as the existing Clinic Measurements dataset as described in [Clinic Measurements data](/our-future-health/data-types/clinic-measurements-data.md#how-do-we-use-major-and-minor-versioning). There is no indicator variable specifying when boundary changes occurred. Therefore, if subsetting the data based on these changes is required, the appointment date must be used.

***

### POCT Lipid Profile data processing and release <a href="#how-did-we-process-the-data-for-each-release" id="how-did-we-process-the-data-for-each-release"></a>

#### How do we process the data for each release?  <a href="#how-did-we-process-the-data-for-each-release" id="how-did-we-process-the-data-for-each-release"></a>

We process the raw data from all participants who were in the programme on or before the cut-off date for each release. Data for participants who have fully withdrawn from Our Future Health is deleted after they request to withdraw. Any participants who have fully withdrawn from the programme since the last data release will not be included in the current data release.&#x20;

To prepare the current data release, we performed minimal additional data processing. This included the following steps:

* migrating data from the CSA (Clinical Staff Application) into our platform and matching the required format and specifications for the final tables released to the TRE
* validation against predetermined criteria for data characteristics such as data type, length, measurement units, value ranges, and minimum and maximum thresholds, and consistency with the version of the appointment attended
* adding a version indicator for each record

Additional strict data cleaning protocols were also applied to this dataset. Several additional variables were derived. This is described below in full.

#### How do we de-identify the POCT Lipid Profile data?

The data de-identified as described in [Clinic Measurements data](/our-future-health/data-types/clinic-measurements-data.md#how-did-we-de-identify-the-questionnaire-data-to-minimise-risks-of-identifying-participants)

#### What exclusions were applied to the POCT Lipid Profile data?&#x20;

Prior to release, the POCT Lipid Profile data underwent structured data processing and quality checks to improve reliability, consistency, and suitability for research use. Processing steps were designed to address known limitations of the device, data entry errors, and inconsistencies in underlying data capture systems.

**Exclusion of records with values outside the analytical range**

A small subset of records contained lipid values outside the supported analytical range of the Mission® POCT device (Table 1). The manufacturer-specified analytical ranges are:

* Total cholesterol (TC): 2.59 - 12.93 mmol/L
* HDL-C: 0.39 - 2.59 mmol/L
* Triglycerides (TG): 0.51 - 7.34 mmol/L

Values outside these ranges are considered unreliable and may arise from device limitations at extreme concentrations, data entry errors, or mismatches between device calibration and test strip batches.

Participant POCT lipid profile records were excluded in full if any lipid measurement fell outside these ranges. This was assessed across all available readings (first and, where applicable, repeat measurements) for TC, HDL-C, and TG. Boundary values were treated as inclusive.&#x20;

This affected a very small proportion of records (<0.05%)

**Exclusion of records where HDL-C is more than TC**

Records were excluded where high-density lipoprotein cholesterol (HDL-C) exceeded total cholesterol (TC), as this is not physiologically plausible and is indicative of potential data capture, data entry, or processing errors. This was assessed across all available readings (first and, where applicable, repeat measurements). Where this occurred, the entire participant record was excluded from the dataset.&#x20;

This affected a very small proportion of records (<0.05%).

#### Are there any other quality issues I should be aware of when using this data?

**Handling of boundary values**

Boundary values are defined as lipid measurements recorded at exactly the minimum or maximum analytical limits of the Mission® POCT device for total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG).

When a measurement falls outside the measurable range of the device (e.g., 2.59 - 12.93 mmol/L for TC), the result is displayed on the device as the minimum or maximum boundary value together with a 'less than' (<) or 'greater than' (>) indicator, respectively, rather than as a precise numeric value. For example, a measurement of total cholesterol that is above the analytical range maximum of 12.93 mmol/L would be displayed as ">12.93". We observed an excess of these boundary values in the POCT data, likely due to out-of-range measurements being recorded as the boundary value alone. Consequently, although boundary values may sometimes be specific measurements, they will more often correspond to values outside the measurable range.

Overall, 4.8% of participants had at least one lipid measurement at a boundary in first or repeat readings, with a smaller proportion observed in repeat measurements (0.7%). Boundary values were more common in first readings and varied by analyte, with HDL-C showing the greatest clustering at the upper limit and TG and TC more often clustering at lower limits.

Boundary values should therefore be interpreted with caution as they may not reflect precise lipid concentrations.

**Inclusion criteria for calculating derived variables**

In light of the issues described above, derived lipid variables (including LDL-C, non-HDL-C, and the TC:HDL-C ratio) are not calculated for participants with any lipid measurement recorded exactly at the minimum or maximum analytical boundary. This exclusion is applied where any available reading (first and, where applicable, repeat measurements) falls at a boundary value.

In doing so, we have excluded derived variables for approximately 4.8% of participants (as described above). This approach is used to reduce the risk of incorporating potentially misclassified boundary entries into derived calculations. Where required, users may recalculate derived variables independently using the raw lipid measurements.

#### How are the POCT lipid profile data organised in the Trusted Research Environment (TRE)? <a href="#how-is-the-questionnaire-data-organised-in-the-trusted-research-environment-tre" id="how-is-the-questionnaire-data-organised-in-the-trusted-research-environment-tre"></a>

The POCT Lipid Profile data are stored as a separate table, released alongside the Clinic measurements dataset. The dataset contains 19 variables, with one row per participant. Participant identifiers are consistent across both datasets; therefore, as expected, many participants will appear in both datasets. The appointment version and time variables are identical across both datasets.

Each table can be linked using a unique identifier (Participant Identifier, `PID`). Aside from the `PID`, all variable names are unique within and across datasets.

#### How do I interpret the structured field names? <a href="#how-do-i-interpret-the-structured-field-names" id="how-do-i-interpret-the-structured-field-names"></a>

The field names can be interpreted as described in [Clinic Measurements data](/our-future-health/data-types/clinic-measurements-data.md#how-do-i-interpret-the-structured-field-names)&#x20;

#### What metadata is available to help document the POCT lipid profile release?

We provide the following data files on our [Data and cohort page (external link)](https://research.ourfuturehealth.org.uk/data-and-cohort/):&#x20;

* Data dictionary - which defines the raw data fields and metadata information, such as labels, descriptions, and units of measurements&#x20;
* Coding file - which contains the granular details of categorical or raw coded values

If using Microsoft Excel to browse these files, for an optimal viewing experience, ensure the encoding settings are set to UTF-8.

***

#### References

1. Karmali KN, Brown T, Sanchez T, Long T, Persell SD. *Point-of-care testing to promote cardiovascular disease risk assessment: A proof of concept study.* Prev Med Rep. 2017 Jun 15;7:136-139. doi: [10.1016/j.pmedr.2017.05.016](https://doi.org/10.1016/j.pmedr.2017.05.016). PMID: 28660121.
2. National Institute for Health and Care Research, Newcastle In Vitro Diagnostics Cooperative. *Point of care testing for cholesterol measuring: a rapid review and presentation of the scientific evidence.* 18 May 2022. <https://newcastle.mic.nihr.ac.uk/wp-content/uploads/2022/09/NIHRNewcastleMIC_AHSNLipidPOCT_Report_vFinal.pdf>.
3. Friedewald WT, Levy RI, Fredrickson DS. *Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.* Clin Chem. 1972 Jun;18(6):499-502. doi: [10.1093/clinchem/18.6.499](https://doi.org/10.1093/clinchem/18.6.499). PMID: 4337382.&#x20;
4. Sampson M, Zubiran R, Wolska A, Meeusen JW, Donato LJ, Jaffe AS, Melloni GEM, Giugliano RP, Sabatine MS, Marston NA, Remaley AT. *A Modified Sampson-NIH Equation with Improved Accuracy for Estimating Low Levels of Low-Density Lipoprotein-Cholesterol.* Clin Chem. 2025 Nov 4;71(11):1125-1137. doi: [10.1093/clinchem/hvaf073](https://doi.org/10.1093/clinchem/hvaf073). PMID: 40629956.


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