This study aimed to explore possible risk profiles within the population of patients undergoing a LSF and if these risk profiles were associated with short-term postoperative outcomes. This study was performed with an explorative intention to investigate whether measuring deconditioning preoperatively is worthwhile and if risk profiles should be investigated further. Two risk profiles could be established; a fit and deconditioned risk profile, showing differences in smoking status, RAND36-PCS, TUG, DEMMI, finger floor distance, motor control and the steep ramp test. The fit risk profile had a shorter LOS and a shorter time to functional recovery. Risk profile allocation was associated with time to functional recovery, but not with LOS or complications.
To the best of our knowledge, no preoperative risk profiles in this population have been established. Establishing such risk profiles is valuable as heterogeneity in the patients eligible for LSF is well recognised . In patients with low back pain, risk profile approaches have already been proposed and give patients together with their health professionals the opportunity to make treatment choices according to these profiles. In other surgical populations, risk profiles are also defined to help in the decision-making process, for example, in patients undergoing total knee arthroplasty, a persistent pain class and poor function class could be identified, similar to our deconditioned risk profile .
Evidence shows the importance of deconditioning for establishing risk profiles and estimating surgical outcomes for major surgery. Snowden et al.  showed that patients with a higher anaerobic threshold were defined as low-risk population and showed successful surgical outcomes and lowered hospital stay and costs in hepatobiliary surgery. Physical fitness is an important predictive variable in major surgery like cardiac, oncological and abdominal surgery, which likely also holds true for LSF [18,19,20]. This seems logical, as good physical fitness or cardiorespiratory capacity is an important aspect of high physiological reserve necessary to adequately deal with surgery-induced stress . Moreover, this hypothesis strongly corresponds with the views of our orthopaedic surgeons, as they also recognize that fitter patients generally recover faster after surgery.
Surprisingly, the fit risk profile comprised more active smokers than the deconditioned risk profile. However, we consider it unlikely that fit patients smoke more frequently, as it would contradict evidence on both lifestyle epidemiology and associations of smoking with outcomes after (spinal) surgery [10, 11, 22, 23]. Moreover, no difference in complication rates could be found between the risk profiles. Due to the relatively small sample size, the low number of smokers and complications within 30 days after LSF, these findings may be coincidental.
Only 25% of the patients performed the Sorensen test. The reason for missingness in the Sorensen test was mainly unwillingness or being unable to perform the test. Patients who did not perform the Sorensen test, mostly originated from the deconditioned group, according to their other characteristics. Due to their deconditioning, they may not have had enough muscle strength to perform this test. Physiotherapists supervising the screening confirmed that patients could mostly not perform the test due to lack of strength or for fear of pain when performing the test. Therefore, a more accessible alternative to measuring muscle strength in these patients is advocated. Based on the literature, we would recommend hand grip strength or sarcopenia measures, as these were related to postoperative outcomes in other types of major surgery [24, 25].
Strengths and limitations
Several strengths and limitations were apparent in our study. A strength of our study is the use of a wide variety of preoperative measurements to identify relevant risk profiles, with the aid of clinical judgement to interpret the risk profiles. By doing so, we were able to identify clinically relevant risk profiles based on characteristics, such as physical fitness, previously often left out of scope. The sample represents a true population of patients eligible for LSF seen in clinical practice, due to the minimal exclusion criteria. This is especially important when we want to identify clinically relevant risk profiles in a heterogeneous population. Limitation of this study is the sample size. Due to COVID-19, our inclusion was limited. Unfortunately during this period, preoperative risk screening had to be cancelled, which led to exclusion of these patients from our analysis. The literature is not uniform in its recommendation on sample size calculation for LCA and is dependent on the complexity and correlation between classes. Nylund–Gibson suggests that n = 300 is desirable, however, for less complex models, a smaller sample size may be sufficient. For a follow-up study, we would suggest a sample approximating n = 300 . Due to the explorative nature and the relatively small sample of this study, our study may not be generalizable, but should be viewed as an explorative study guiding a research topic worthy of validation in future studies.
Until now perioperative care for patients is often still one-size-fits all. Implementing risk profiles into clinical practice can help frame a more preventive patient-specific approach to perioperative care for patients opting for LSF. If these risk profiles are validated, the next step could be identifying specific perioperative treatment plans matched to these risk profiles to better manage hospital resources and of course fit patient’s needs. The fit cluster could be scheduled for short stay surgery procedures, whilst the deconditioned risk profiles may benefit from prehabilitation strategies, such as exercise therapy, reducing their risk of prolonged functional recovery and hospital length of stay. In turn, we should explore if these optimized perioperative pathways could improve postoperative outcomes.