Anaesthesia duration¶
Anaesthesia duration (derived table).
| Name in the dataset | ane_duration |
| Type | clinical |
| Stored in | derived |
| Unit | min |
Time¶
This variable carries no time of its own in the dataset.
Value¶
| Model kind | derived: computed from other variables' posteriors |
| Resolution | derived from anestart, aneend |
Derived from¶
Computed from Anesthesia start time and Anesthesia end time. Formula: (aneend - anestart) / 60. Uncertainty: difference of the two event posteriors, sampled independently given the device references.
In this release¶
How wide the true-value distribution is, record by record, over 6,254 of 6,388 records (all clinical rows) that have one. Computed with the pinned model, aggregates only.
| Median | p10 to p90 | |
|---|---|---|
| Standard deviation | 2.72 min | 1.49 to 4.88 min |
| 95% interval width | 9.59 min | 5.22 to 20.2 min |
| Mean minus recorded | -3.87 min | -6.56 to -2.3 min |
Worked examples¶
| Example | Side | Status | Summary |
|---|---|---|---|
| A regression that carries rounding uncertainty through | value | draft | Acute kidney injury after surgery against intraoperative urine output (mL/kg/h), fitted once on the recorded numbers and once per draw from the true-value distributions: the rounding moves 14% of cases across the oliguria threshold, but widens the confidence interval of the cohort's regression by at most 4%. |
| Oliguria labels for a prediction model | value | draft | One label per patient, oliguric or not, from three rounded numbers: 10% of labels are uncertain and 2.6% are expected to be wrong, which sets a floor under the error any model can be measured to have. A typical model is barely affected; a good one is. |
| Urine output in mL/kg/h as a distribution | value | draft | Intraoperative urine output per kilogram per hour, from three rounded inputs, as a probability distribution per case: one case in ten cannot be placed confidently on either side of 0.5 mL/kg/h. |
Tags: generated, vitaldb-resolution