Pre-hospital medications in total hip arthroplasty: risk factors for poor outcomes

Patient selection in ambulatory surgery

Patient selection is important for ambulatory surgical practices. Proper patient selection for ambulatory practices will optimize resources and lead to increased patient and provider satisfaction. As the number and complexity of procedures in ambulatory surgical centers increase, it is important to ensure that patients are best cared for in facilities that can provide appropriate levels of care. This review addresses the multiple variables and resources that should be considered when selecting patients for anesthesia in ambulatory centers and offices.

Total Hip Arthroplasty Revision Surgery: Impact of Morbidity on Perioperative Outcomes

BACKGROUND

Primary and revision total hip arthroplasty (THA) is increasingly performed in patients with high comorbidity burden. Its predominantly negative effects on outcomes are well understood in primary THA; however, the effects of morbidity on revision THA are unknown. Since revision procedures account for about 10% of the total surgical volume, we set out to investigate the effects of physical health status on perioperative outcomes in this setting.

METHODS

We queried our prospectively collected institutional database for patients who underwent revision THA at our institution (Orthopedic University Hospital Friedrichsheim, Frankfurt) between 2007 and 2011. Patients were classified according to American Society of Anesthesiologists (ASA) category and number of comorbidities. Subsequently, their impact on perioperative parameters was analyzed.

RESULTS

Our database revealed 294 cases of revision THA during the study period. Patients preoperatively classified as ASA 3 and 4 showed significantly higher rates of intraoperative and postoperative complications, transfusions, prolonged intensive care unit (ICU) stay, and total length of stay (LOS) compared to patients classified as ASA 1 and 2. Similarly, patients with >3 comorbidities presented with significantly elevated postoperative complications, ICU stay, and LOS. Particularly, preoperative cardiac diseases were associated with increased blood loss, transfusions, duration of surgery, postoperative complications, ICU stay, LOS, and re-revisions.

CONCLUSION

Poor physical health condition is associated with negative perioperative outcomes in revision THA. Especially cardiac comorbidities are linked to unfavorable outcomes, which have important implications for assessment of perioperative risk.

Preoperative medications is one of the factor affecting patient-reported outcomes after total hip arthroplasty

Although the reported clinical outcomes of total hip arthroplasty (THA) for hip osteoarthritis are satisfactory, not all patients are completely satisfied. Thus, there is interest in predicting postoperative satisfaction before surgery. The influence of comorbidities and preoperative medications on the incidence of complications and duration of hospitalization following THA has become apparent. However, studies about the associations of preoperative medication with clinical outcomes of THA are limited. Therefore, this study aimed to clarify the relationship between preoperative medications and postoperative patient-reported outcomes. This retrospective cross-sectional multicenter study enrolled post-THA patients (79 patients, 90 hips) who were examined from February to March 2019 in eight general hospitals. Outcome measures included patient-reported outcome as Japanese Orthopaedic Association Hip Disease Evaluation Questionnaire (JHEQ) score. Preoperative medications were investigated from medical records. Medications were categorized, and analgesics were categorized into non-steroidal anti-inflammatory drugs (NSAIDs), acetaminophen, pregabalin, duloxetine, neurotropin (an extract from inflammatory rabbit skin inoculated by vaccinia virus), and opioid. To identify the factors associated with JHEQ score, the patients were divided into lower (<55 score) and higher (≥55) JHEQ score groups. Spearman rank correlation coefficient (r) showed significant difference between the total number of preoperative medications and postoperative JHEQ movement subscale (r = -0.37, p < 0.01), mental subscale (r = -0.29, p < 0.01), and JHEQ (r = -0.30, p < 0.01) scores. In the multiple logistic regression analysis, only the total number of preoperative medications was identified as a risk factor for lower JHEQ score (p < 0.01). This study clarified an inverse correlation between the total preoperative medication count and postoperative outcomes and found that larger total count of preoperative medications is a risk factor of poor postoperative patient-reported outcomes of THA.

Polypharmacy at admission prolongs length of hospitalization in gastrointestinal surgery patients

Aim

Polypharmacy in elderly people is a social issue and has been reported to cause not only drug adverse events, but also falls, dysfunction and cognitive decline. Those events may trigger prolonged length of hospitalization. Therefore, the aim of this study was to investigate whether polypharmacy has a prolonging effect on hospitalization.

Methods

The study subjects were 584 patients in a university hospital in Japan who had been admitted for hepatectomy, pancreaticoduodenectomy, gastrectomy or colectomy, and to whom clinical pathways had been applied. In this study, polypharmacy was defined as taking five or more regular oral medications, and prolonged hospitalization was defined as hospitalization longer than that determined by the clinical pathway. Multiple logistic regression analysis was performed to investigate whether polypharmacy affects the length of hospitalization.

Results

The subjects were 348 males and 236 females, mean ± SD age of 65.8 ± 12.9 years. Among all subjects, 228 (39.0%) were receiving polypharmacy at admission, and the number of patients with prolonged hospitalization was 262 (44.9%). Multiple logistic regression analysis revealed that the following variables were significantly associated with prolonged hospitalization; polypharmacy (odds ratio = 1.532; 95% confidence interval = 1.010–2.327), age 50–59; 2.971 (1.216–7.7758), age 60–69; 2.405 (1.059–5.909), organ pancreas; 0.298 (0.122–0.708), operation time ≥386 min; 2.050 (1.233–3.432), intraoperative bleeding volume ≥401 mL; 2.440 (1.489–4.038), postoperative delirium; 2.395 (1.240–4.734), postoperative infection; 10.715 (4.270–33.059).

Conclusion

The current study revealed that polypharmacy at admission was an independent factor for prolonged hospitalization. In future, measures against polypharmacy are required, collaborating with outpatient clinics, family doctors and dispensing pharmacies. Geriatr Gerontol Int 2020; 20: 1085–1090..

Four questions to identify patients with ASA III or higher

BACKGROUND

Increased age, obesity, and American Society of Anesthesiologists (ASA) Physical Status class III and IV have been reported as predictors for mortality and perioperative complications. High-volume institutions rely on central referral services as first contact point for patients. The current study reports on a simple four-step questionnaire to identify patients with ASA-physical status class III and IV to improve referral processes and optimize perioperative work ups.

MATERIALS AND METHODS

Seven hundred and seventy-five patients who called the physician referral service (PRS) at the author's institution and subsequently underwent surgery were enrolled in this study. The answers to the initial PRS questionnaire were analyzed. The study cohort consisted of 414 women (53.4%) and 361 men (46.6%) with an average age of 61.4 years (range 44-90 years) at the time of surgery.

RESULTS

Binary logistic regression revealed hypertension, diabetes mellitus (using medication), using blood thinner (other than Aspirin) and a number of 4-9 prescribed medication, respectively, as predictors for ASA III and IV. Receiver-operating characteristic (ROC) curve analysis identified a sensitivity of 82.4%, a specificity of 82.9%, and an accuracy of 82.8%, when two of these four questions are answered "yes". The area under the curve for this analysis was 0.876 [95% confidence interval (CI) 0.845-0.908]. Positive and negative likelihood ratios were 4.8 (95% CI 4.0-5.8) and 0.2 (95% CI 0.1-0.3), respectively.

CONCLUSIONS

This study revealed a simple four-step questionnaire to identify patients with ASA III or IV before a medical appointment. This helps to balance referrals between multiple providers in high-volume medical groups.

How Do Preoperative Medications Influence Outcomes After Total Joint Arthroplasty?

BACKGROUND

Recent health care policy changes require hospitals and physicians to demonstrate improved quality. In 2012, a prospective database was formed with the Blue Cross and Blue Shield of Michigan to improve quality of care. The purpose of this study was to analyze patient preoperative medication as predictors of outcomes after total joint arthroplasty.

METHODS

Data were collected on patient's preoperative medications from 2012 to 2015 using a total joint arthroplasty database. Medications were categorized as antiplatelet, antimicrobial, anticoagulant, narcotic, steroid, insulin, or oral diabetes medication. Outcomes included hospital length of stay (LOS), discharge disposition/destination, and 90-day readmission. Univariate and multivariate regression analyses were performed.

RESULTS

A total of 3959 patients were studied. Eighty percent (3163 patients) were discharged home. The remainder (795) went to an extended-care facility (ECF). Patients discharged to an ECF were taking more medications (1.13 vs 0.80 in total knee arthroplasty; 1.18 vs 0.83 in total hip arthroplasty; P <.001). Patients who were readmitted took more medications (1.0 vs 0.85; P <.01). There were more discharges to an ECF in narcotic, steroid, and diabetes medication users. Patients taking anticoagulants, narcotics, insulin, and antiplatelets had greater readmission rates. There was a significant correlation between the number of medications and an increased LOS.

CONCLUSION

Patients taking more medications were more frequently discharged to an ECF and had increased LOS and readmission rates. Narcotics and diabetic medications had the greatest influence. Category and quantity of preoperative medications can be used as predictors of outcomes after arthroplasty surgery.

Medication Use is a Better Predictor of Length of Hospital Stay in Total Hip Arthroplasty Than the American Society of Anesthetists (ASA) Score

BACKGROUND

Length of hospital stay (LOS) greatly influences costs of total hip arthroplasty (THA). LOS is, among others, dependent on patient comorbidity. American Society of Anesthetists (ASA) scores are traditionally used as comorbidity measure, but simple medication-based measures may suffice. Therefore, the objective of the study is to determine if medication-based measures (count of medication and the medication-based index Chronic Disease Score [CDS]) have a surplus value compared to a diagnosis-based measure for comorbidity (ASA score) to predict LOS in THA.

METHODS

A retrospective cohort study. THA patients from 3 hospitals were included for 2009-2013, and demographic data, comorbidity (ASA score), and medication use (count of medication and CDS) were collected. A binomial regression model was used to compare the predictive ability of the medication-based and diagnosis-based measures.

RESULTS

A total of 2,282 THA patients were included. Number of medications proved a statistical significant predictor of LOS. LOS increased 6% (incidence rate ratios: 10.06 [confidence interval: 1.03-1.09]) with each medication. Neither the CDS nor the ASA score had a statistically significant relation to LOS.

CONCLUSION

The medication-based measure count of medication is a better predictor for LOS in THA than the CDS and ASA score. This simple measure also appears to have more clinical relevance, as it has a higher range in scores than diagnosis-based indexes and is easily applicable.