Deciphering the explanatory potential of blood pressure variables on post-operative length of stay through hierarchical clustering: A retrospective monocentric study
Data files
Jul 02, 2024 version files 21.81 MB
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Measurements.csv
21.81 MB
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README.md
5.76 KB
Abstract
Objective: Mean arterial pressure is widely used as the variable to monitor during anesthesia. But there are many other variables proposed to define intraoperative arterial hypotension. The goal of the present study was to search arterial pressure variables linked with prolonged postoperative length of stay (pLOS).
Design: Retrospective cohort study of adult patients having received general for a scheduled non cardiac surgical procedure between 15th July 2017 and 31st December 2019.
Methods: pLOS was defined as a stay longer than the median (main outcome), adjusted for surgery type and duration. 330 arterial pressure variables were analyzed and organized through a clustering approach. An unsupervised hierarchical aggregation method for optimal cluster determination, employing Kendall’s tau coefficients and a penalized Bayes information criterion was used. Variables were ranked using the absolute standardized mean distance (aSMD) to measure their effect on pLOS. Finally, after multivariate independence analysis, the number of variables was reduced to three.
Results: Our study examined 9,516 patients. When LOS is defined as strictly greater than the median, 34% of patients experienced pLOS. Key arterial pressure variables linked with this definition of pLOS included the difference between the highest and lowest pulse pressure values computed throughout the surgery (aSMD[95%CI] =0.39[0.31-0.40], p<0.001), the accumulated time pulse pressure above 61mmHg (aSMD = 0.21[0.17-0.25], p<0.001), and the lowest MAP during surgery (aSMD= 0.20[0.16-0.24], p<0.001).
Conclusions: By applying a clustering approach, three arterial pressure variables were associated with pLOS. This scalable method can be applied to various dichotomized outcomes.
https://doi.org/10.5061/dryad.12jm63z5r
Demography.csv (on Zenodo)
Demography table contains main patients' characteristics. 10 variables
| id_data | Patient number |
|---|---|
| surgery | 1: general; 2: lung; 3:neurosurgery; 4: urology; 5: vascular; 6: gynecology; 7: ENT |
| age | 1: below 65 years; 2: 65 years and more |
| sex | 1:M; 2: F |
| los | Length of post-operative stay (days) |
| time_quartile | Quartile of surgery duration (absolute number) |
| median_Stay | Median length of stay (days) |
| Q3_Stay | Third quartile of length of stay (days) |
| Q90_Stay | 90th percentile of length of stay (days) |
| Short_IQR | Interquartile range of length of stay <=1 (Q3-Q1) (days) |
Measurements.csv (on Dryad)
Measurements table contains all variables related to arterial pressure and used for statistical analysis. 330 variables
| Min_MAP | minimal value of mean arterial pressure (mmHg) |
|---|---|
| Max_MAP | maximal value of mean arterial pressure (mmHg) |
| Delta_MAP | Largest Drop in MAP during surgery (mmHg) |
| Mean_MAP | Mean MAP (mmHg) |
| Median_MAP | Median MAP (mmHg) |
| std_MAP | standard deviation of MAP (mmHg) |
| Var_MAP | MAP variability (absolute number) |
| Cum_time_MAP_[XX] | cumulative time of mean arterial pressure below [XX] mmHg (minutes) |
| Area_time_MAP_[XX] | cumulative area of mean arterial pressure below [XX] mmHg (absolute number) |
| Min_PP | minimal value of pulse pressure (mmHg) |
| Max_PP | maximal value of pulse pressure (mmHg) |
| Delta_PP | Largest Drop in PP during surgery (mmHg) |
| Mean_PP | Mean PP (mmHg) |
| Median_PP | Median PP (mmHg) |
| std_PP | standard deviation of PP (mmHg) |
| Var_PP | PP variability (absolute number) |
| Cum_time_PP_[XX] | cumulative time of pulse pressure below [XX] mmHg (minutes) |
| Cum_area_PP_[XX] | cumulative area of pulse pressure below [XX] mmHg (absolute number) |
| Min_S | minimal value of systolic arterial pressure (mmHg) |
| Max_S | maximal value of systolic arterial pressure (mmHg) |
| Delta_S | Largest Drop in S during surgery (mmHg) |
| Mean_S | Mean S (mmHg) |
| Median_S | Median S (mmHg) |
| std_S | standard deviation of S (mmHg) |
| Var_S | S variability (absolute number) |
| Cum_time_S_[XX] | cumulative time of systolic arterial pressure below [XX] mmHg (minutes) |
| Area_time_S_[XX] | cumulative area of systolic arterial pressure below [XX] mmHg (absolute number) |
| Min_D | minimal value of diastolic arterial pressure (mmHg) |
| Max_D | maximal value of diastolic arterial pressure (mmHg) |
| Delta_D | Largest Drop in diastolic arterial during surgery (mmHg) |
| Mean_D | Mean diastolic arterial (mmHg) |
| Median_D | Median diastolic arterial (mmHg) |
| std_D | standard deviation of diastolic arterial (mmHg) |
| Var_D | diastolic arterial variability (absolute number) |
| Cum_time_D_[XX] | cumulative time of diastolic pressure below [XX] mmHg (minutes) |
| Area_time_D_[XX] | cumulative area of diastolic pressure below [XX] mmHg (absolute number) |
Patient characteristics and preoperative medications were collected from Cesare™, a computerized software for preoperative anesthetic evaluation (Bow Médical, 80440 Boves, France). Centricity Anesthesia software was used to collect intraoperative variables (GE Healthcare, 78 530 Buc, France). lenght of stay and in-hospital mortality were obtained by questioning the health data warehouse.
- Cartailler, Jérôme; Beaucote, Victor; Trillat, Bernard et al. (2024). Deciphering the explanatory potential of blood pressure variables on post-operative length of stay through hierarchical clustering: A retrospective monocentric study. PLOS ONE. https://doi.org/10.1371/journal.pone.0308910