Total knee arthroplasty (TKA) is a highly effective procedure for advanced osteoarthritis of the knee. Thirty-day hospital readmission is an adverse outcome related to complications, which can be mitigated by identifying associated risk factors.
Total knee arthroplasty (TKA) is a highly effective treatment for advanced osteoarthritis of the knee[1][2]. The number of procedures being performed each year continues to grow[3]. However, despite its widespread success and increasing utilisation rates, a range of complications can arise following TKA surgery[4], some of which necessitate hospital readmission. Hospital readmission following TKA is often a marker of surgical complications[5][6]. Post-operative hospital readmissions are recognised as a significant cause for concern because such events disrupt the patient’s postoperative recovery, incur significant costs to the healthcare system¸ and controversially have been used as a marker of quality of care[7][8][9]. In the USA, unplanned hospital readmissions for all patient populations overall are estimated to cost over USD 17 billion[10] In 2004, Germany became the first country to implement financial incentives to reduce readmissions[11]. Five years later, in 2009, the United States’ Centers for Medicare & Medicaid Services introduced the Hospital Readmissions Reduction Program[9] and expanded this program in 2014 to include TKA[12][13], where hospital penalties are applied for readmission signalling government authorities to view readmission as an issue requiring attention.
By improving our ability to accurately predict individual patients’ risk of readmission following TKA, we may reduce the rate of avoidable readmissions through optimising shared decision-making and consent processes; better preparing patients for surgery and developing personalised management and discharge planning for higher risk patients. Furthermore, some readmissions are potentially avoidable and can be targeted through the development of personalised management and discharge planning for higher risk patients. Patients whose risk of readmission is difficult to mitigate, such as those patients with non-modifiable risk factors, can still benefit from risk prediction because they will be more informed as they work with the surgeon to weigh the potential benefits and risks of the procedure, and patients who have more realistic expectations regarding their likely postoperative course are more likely to achieve a satisfactory outcome following TKA [14].
Our previous narrative literature review has explored patient-related risk factors for 30-day readmissions in TKA[15]. Comorbidities such as diabetes, chronic kidney disease, and bleeding disorders were consistently shown to increase risk, but demographic factors such as age, sex, and body mass index (BMI) demonstrated a more complex and less consistent influence on 30-day readmission. Using age as an example, some researchers dichotomise at a particular number, while others create multiple categories at different cut-points with different interval durations, such as five years or 10 years. The inconsistent way different researchers categorise predictor variables when modelling risk, and the increasing age, BMI, and physical activity demands of the TKA patient population over time[16][17][18], may contribute and confound this further. Thus, the purpose of this systematic review was to apply rigorous systematic review methodology to synthesise the evidence pertaining to patient risk factors for 30-day readmission following TKA. Contrasting the more subjective style of the narrative review, which identified broad themes in the literature, the current work synthesises the evidence in the most objective manner possible, including: critical appraisal of all included articles, quantitative synthesis when appropriate, narrative synthesis when quantitative synthesis was not possible, and summary of findings in accordance with a version of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach modified for systematic reviews of prognostic factors [19].
The objectives of this review were to (1) identify patient-related characteristics that are associated with increased risk of unplanned 30-day readmission following TKA and (2) determine the effect size of the association between the identified risk factors and unplanned 30-day readmission[20]. This systematic review and meta-analysis synthesises existing knowledge, determines the effect size of identified factors, and aims to resolve uncertainty when discrepancies arise between reports.
The protocol for this systematic review has been published [
] and registered with the International Prospective Register of Systematic Reviews (PROSPERO-CRD42019118154). Protocol deviations, and justifications for them, are outlined in
. Deviations were minor and did not alter the objectives, nor the direction of this systematic review. This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement[21].
We used the adapted Patient, Intervention, Comparator, Outcome (PICO) framework[22] to answer the following questions: which patient-related factors confer increased risk of unplanned 30-day readmission following TKA, and to what extent do these factors influence the risk? Eligible studies involved TKA recipients (primary and revision) compared for 30-day readmission to any institution, due to any cause, on the basis of patient risk factors (presence vs absence of each risk factor). Case series were excluded, but all other types of quantitative study design were eligible for inclusion, including retrospective and observational studies.
No restrictions were placed on the date of publication for this review.
MEDLINE and EMBASE were searched from inception to 5 February 2020, using search terms related to total knee arthroplasty and patient-related risk factors for 30-day readmission. An experienced research librarian was consulted to assist with development of the search strategy, and no restriction was placed on grey literature. The full search strategy for both databases is available in
. The search was repeated immediately prior to final analysis (8th September 2020) to obtain studies that had been published since initially searching the database. Reference lists of articles included after full text screening were also screened.
The search strategy was carried out in line with the protocol. In brief, two reviewers (DG and OJ) pilot-tested the eligibility criteria on a 10% sample of titles and abstracts of articles obtained from the database search. A third reviewer (MD) arbitrated discussions between DG and OJ to resolve any major difference in opinion arising from this process. The eligibility criteria were then applied to titles and abstracts and, subsequently, to the full text of articles that were deemed eligible for inclusion following initial screening.
Authors of articles potentially eligible for inclusion were contacted to provide the requisite data for inclusion.
Two reviewers (DG and JT) independently extracted data using a standardised data extraction form. The process was pilot-tested on 10 articles from the final set of included articles following full-text screening. Any points of clarification were resolved by discussion between DG and JT. DG identified additional information required in order to complete the critical appraisal assessment and this was verified by JT as well as the reviewer who completed the critical appraisal assessment with DG (WK).
Data items extracted were those listed in the protocol, as well as several additional items necessary for critical appraisal (
).
As outlined in the protocol amendments (
), adjusted odds ratios (ORs) were preferentially collected over risk ratios (RRs), as this reflects how data were reported in the vast majority of included studies, which were retrospective in nature. As the estimated 30-day readmission rate for TKA ranges from 3%[5] to 4.6% [23][
] and this is well below the 10% threshold whereby the OR provides a reasonable approximation of the RR [20][24], it is unlikely that this would have altered the key findings.
The Joanna Briggs Institute (JBI) critical appraisal tool [25] was used for all studies. A semi-quantitative method was used, based on that used by Goplen et al. [26] in a systematic review on outcomes in total joint arthroplasty (TJA) patients. However, since there is no valid cut-off value to determine “high” or “low” methodological quality, we assessed quality in relative terms by splitting the studies according to risk of bias quartiles. The item: “Were the groups/participants free of the outcome at the start of the study (or at the moment of exposure)?” was omitted from the checklist as it is not possible for a patient to be readmitted prior to their TKA procedure. The remaining 10 items were given equal weighting with a higher score indicating greater risk of bias. Each “no” was given a score of 2, each ‘unclear a score of 1, and each “yes” a score of 0. Arbitrarily selecting a cut-point above which a study is considered to be at high risk of bias is problematic because there are no clear guidelines pertaining to the choice of such a cut-point. Instead, quartiles of risk of bias were calculated to distinguish between higher quality studies (lower risk of bias quartiles) and lower quality studies (higher risk of bias quartiles). This use of quartiles is similar to that used by Detweiler et al., 2016 [27] in their exploration of methodological quality of systematic reviews, and we believe it provides readers with an easily interpretable way of judging the relative methodological quality of included studies without generating an overwhelming number of categories.
Selective reporting was also assessed for each study. This was included in the summary table for critical appraisal but because it was not a JBI checklist item, it did not contribute to the calculation of risk of bias score.
depicts a generic example of the way in which the outcome of critical appraisal is presented in this review for an imaginary study, for the sake of illustration.
Example of critical appraisal table.
Meta-analysis | ||||||||
Prognostic factor | OR (95% CI) | Overall quality | ||||||
Hispanic race | 0.92 (0.68–1.25) | 5 (+++) | ||||||
Narrative Synthesis | ||||||||
Prognostic factor | Univariate | Multivariate | Overall quality | |||||
+ | 0 | - | + | 0 | - | |||
Age (continuous variable) | ||||||||
Age | 3 | 1 | - | 4 | 3 | - | 5 (+++) | |
Sex | ||||||||
Female sex | - | 1 | - | - | 1 | 4 | 5 (+++) | |
Male sex | 2 | 2 | - | 8 | - | - | 6 (++++) | |
Race | ||||||||
Black (reference = white or non-Black) | 1 | 1 | - | 4 | 3 | - | 4 (+++) | |
Hispanic (reference = white or non-Hispanic) | - | 1 | - | - | - | - | 1 (+) | |
Asian (reference = white) | - | 2 | - | - | 1 | 2 | 4 (+++) | |
Native Hawaiian (reference = white) | - | 1 | - | - | - | - | 3 (++) | |
American Indian (reference = white) | - | 2 | - | - | 1 | - | 4 (+++) | |
White | - | 1 | 1 | - | 1 | - | 2 (+) | |
Indian (reference = Chinese) | - | - | - | - | 1 | - | 2 (+) | |
Malay (reference = Chinese) | - | - | - | - | 1 | - | 2 (+) | |
Biracial (Workman) or mixed race (Ali) | 1 | - | - | 1 | - | - | 5 (+++) | |
Minority ethnicity | - | - | - | 1 | - | - | 2 (+) | |
Other (Tang = Chinese; otherwise = white) | - | 1 | - | 1 | 4 | 2 | 3 (++) | |
Missing | - | 1 | - | 1 | - | 3 | 3 (++) | |
Race (combined analysis – i.e., racial difference exists between readmitted and non-readmitted cohorts) | 2 | - | - | 1 | - | - | 4 (+++) | |
Socioeconomic | ||||||||
Decreasing incoming | - | - | - | 3 | 1 | - | 5 (+++) | |
Low socioeconomic status | 1 | - | - | 1 | - | - | 4 (+++) | |
Insurance status | ||||||||
Medicare (reference category = private insurance or non-Medicare) | - | - | - | 4 | - | - | 4 (+++) | |
Medicaid (reference category = private insurance) | - | - | - | 3 | - | - | 3 (++) | |
Self-pay, no charge, workers’ compensation, or other (reference category = private insurance) | - | - | - | - | 2 | 3 | 2 (+) | |
Disability entitlement | - | - | - | 1 | - | - | 3 (++) | |
Functional status, living situation, and frailty | ||||||||
Dependent functional status | - | - | - | 1 | - | - | 4 (+++) | |
Use of walking aids | 1 | - | - | - | 1 | - | 4 (+++) | |
Living alone | - | 1 | - | - | 2 | - | 5 (+++) | |
Living in an institution or nursing home | - | 1 | - | 1 | - | - | 3 (++) | |
Homeless | - | - | - | 1 | - | - | 2 (+) | |
Frailty (Modified Frailty Index) | - | - | - | 1 | - | - | 5 (+++) | |
Smoking | ||||||||
1.25 (0.82–1.91) | ||||||||
5 (+++) | ||||||||
Rheumatologic disorder | ||||||||
1.11 (1.04–1.18) | ||||||||
3 (++) | ||||||||
Narrative Synthesis | ||||||||
Prognostic factor | ||||||||
Univariate | ||||||||
Multivariate | ||||||||
Overall quality | ||||||||
+ | ||||||||
0 | - | + | 0 | - | ||||
Composite comorbidity indices | ||||||||
Charlson Comorbidity Index (CCI) 1-2 (reference category = 0) | - | - | - | 2 | - | - | 6 (++++) | |
CCI 1 (reference category = 0) | - | - | - | 2 | 1 | - | 6 (++++) | |
CCI 2 (reference category = 0) | - | - | - | 1 | - | - | 5 (++++) | |
CCI ≥2 (reference category = 0) | - | - | - | 1 | 1 | - | 6 (++++) | |
CCI 3-4 (reference category = 0) | - | - | - | 1 | - | - | 5 (+++) | |
CCI ≥3 (reference category = 0) | - | - | - | 1 | - | - | 4 (+++) | |
CCI 5+ (reference category = 0) | - | - | - | 1 | - | - | 5 (+++) | |
Increasing CCI | - | - | - | - | 1 | - | 3 (++) | |
Presence of any comorbidity | 1 | - | - | 2 | - | - | 4 (+++) | |
Increasing American Society of Anaesthesiologists (ASA) classification (reference category = 2) | - | - | - | 1 | - | - | 4 (+++) | |
Increasing ASA classification (reference category = 1) | - | - | - | - | 1 | - | 2 (+) | |
ASA classification (other) | - | 1 | - | - | 1 | - | 2 (+) | |
Increasing Elixhauser Index | - | - | - | 1 | - | - | 5 (+++) | |
Increasing DRG (Diagnosis-related group) | - | - | - | 1 | - | - | 3 (++) | |
Cardiovascular | ||||||||
Hypertension | 2 | 2 | - | 6 | 1 | - | 5 (+++) | |
Hyperlipidaemia | 1 | 1 | - | - | - | - | 4 (+++) | |
Cardiac disease | - | - | - | 1 | ||||
- | ||||||||
- | ||||||||
1 | ||||||||
- | ||||||||
4 (+++) | ||||||||
Endocrine | ||||||||
Diabetes (general category and Peskun type two diabetes mellitus (T2DM)) | ||||||||
- | ||||||||
1 | - | 5 | 4 | - | 3 (++) | |||
Diabetes (with complications) | 1 | - | - | 1 | - | - | 5 (+++) | |
Diabetes (without complications) | 1 | - | - | 1 | - | - | 5 (+++) | |
Insulin-dependent diabetes mellitus (IDDM) | 1 | - | - | 1 | - | - | 5 (+++) | |
NIDDM | 1 | - | - | - | 1 | - | 4 (+++) | |
Hypothyroidism | - | 1 | - | - | 1 | - | 5 (+++) | |
Gastrointestinal | ||||||||
Liver disease | 1 | - | - | - | 1 | - | 2 (+) | |
Haematological | ||||||||
Anaemia | - | - | - | 1 | 1 | 1 | 4 (+++) | |
Anaemia (blood loss) | 1 | - | - | - | 1 | - | 4 (+++) | |
Anaemia (deficiency) | 1 | - | - | - | 2 | - | 3 (++) | |
Bleeding disorders | 1 | - | - | 1 | - | - | 3 (++) | |
Coagulopathy | 1 | - | - | - | - | - | 3 (++) | |
Anticoagulant therapy | - | - | - | - | 1 | - | 2 (+) | |
Increasing INR | 1 | - | - | 1 | - | - | 4 (+++) | |
Fluid and electrolyte disorder | 1 | - | - | 1 | - | - | 3 (++) | |
Elevated serum blood urea nitrogen (BUN) | 1 | - | - | 1 | - | - | 4 (+++) | |
Hyponatraemia | - | 1 | - | - | 1 | - | 4 (+++) | |
Low albumin | - | - | - | 1 | - | - | 4 (+++) | |
Elevated creatinine | 1 | - | - | - | - | - | 3 (++) | |
Elevated WBC count | 1 | - | - | - | - | - | 3 (++) | |
Reduced haematocrit | 1 | - | - | - | - | - | 3 (++) | |
Low platelets | 1 | - | - | - | - | - | 3 (++) | |
Respiratory | ||||||||
Chronic obstructive pulmonary disease (COPD) and chronic airways disease (combined) | - | - | - | 4 | - | - | 3 (++) | |
Pulmonary disease | 1 | - | - | 1 | 1 | - | 4 (+++) | |
Smoking | 1 | 2 | - | 1 | - | - | 3 (++) | |
Pulmonary circulation disorder | - | - | - | 1 | 1 | - | 2 (+) | |
Asthma | - | 1 | - | - | - | - | 1 (+) | |
Dyspnoea | 1 | - | - | - | 1 | - | 3 (++) | |
Previous pneumonia | - | - | - | - | 1 | - | 3 (++) | |
Obstructive sleep apnoea | - | 1 | - | - | - | - | 1 (+) | |
Cardiopulmonary disease | 1 | - | - | - | - | - | 0 (+) | |
Psychiatric | ||||||||
Depression | 1 | 2 | - | 3 | 1 | - | 5 (+++) | |
‘Other’ mental health condition (other than depression) | - | - | - | 1 | - | - | 3 (++) | |
Bipolar disorder | - | 1 | - | - | - | - |
Critical Appraisal | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Study ID | * JBI 1. | JBI 2. | JBI 3. | JBI 4. | JBI 5. | JBI 7. | JBI 8. | JBI 9. | JBI 10. | JBI 11. | Overall Risk of Bias Score (Quartile; Arranged in Descending Order) | Evidence of Selective Reporting |
Example study | Y | Y | Y | Y | Y | Y | Y | N | U | Y | 3/20 therefore 15% (1st quartile) | No |
The colour scheme mimics that of a traffic light system indicating whether each critical appraisal criterion was fulfilled in the given study: Green = yes (Y), Yellow = unclear (U), Red = No (N); * Joanna Briggs Institute critical appraisal checklist for cohort studies – components: Joanna Briggs Institute (JBI) 1. Were the groups similar and recruited from the same population? JBI 2. Were the exposures measured similarly to assign people to both exposed and unexposed groups? JBI 3. Was the exposure measured in a valid and reliable way? JBI 4. Were confounding factors identified? JBI 5. Were strategies to deal with confounding factors stated? JBI 6. (Omitted because it is not relevant) Were the groups/participants free of the outcome at the start of the study (or at the moment of exposure)? JBI 7. Were strategies to deal with confounding factors stated? JBI 8. Was the follow up time reported and sufficient to be long enough for outcomes to occur? JBI 9. Was follow up complete, and if not, were the reasons for loss to follow up described and explored? JBI 10. Were strategies to address incomplete follow up utilized? JBI 11. Was appropriate statistical analysis used?
3. Results
Meta-analysis | ||||||||
---|---|---|---|---|---|---|---|---|
Prognostic factor | OR (95% CI) | Overall quality | ||||||
Alcohol abuse | 1.08 (0.96–1.20) | 6 (++++) | ||||||
BMI < 18.5 vs. normal | 1.15 (0.45–2.98) | 4 (+++) | ||||||
BMI 25–30 vs. normal | 0.91 (0.80–1.03) | 6 (++++) | ||||||
BMI 30–35 vs. normal | 0.90 (0.80–1.02) | 6 (++++) | ||||||
BMI 35–40 vs. normal | 0.84 (0.69–1.02) | 6 (++++) | ||||||
BMI > 40 vs. normal | 1.05 (0.84–1.31) | 6 (++++) | ||||||
Obesity | 1.06 (1.02–1.09) | 4 (+++) | ||||||
Weight loss | 0.95 (0.71–1.27) | 3 (++) | ||||||
Arrhythmias and AF combined | 1.14 (1.09–1.19) | 4 (+++) | ||||||
Ischaemic heart disease (IHD) + coronary artery disease (CAD) + cardiac disease | 1.29 (0.79–2.09) | 3 (++) | ||||||
Peripheral vascular disease | 1.17 (1.10–1.24) | 5 (+++) | ||||||
Previous myocardial infarction, or coronary artery disease | 1.18 (0.29–4.88) | 3 (++) | ||||||
Non-insulin-dependent diabetes mellitus (NIDDM) | 1.08 (0.80–1.45) | 4 (+++) | ||||||
Liver disease | 1.29 (1.20–1.39) | 4 (+++) | ||||||
Peptic ulcer disease | 0.94 (0.84–1.07) | 4 (+++) | ||||||
Anaemia | 1.19 (1.15–1.24) | 6 (++++) | ||||||
Deficiency anaemias | 1.06 (1.01–1.11) | 4 (+++) | ||||||
Coagulopathy | 1.25 (1.15–1.36) | 4 (+++) | ||||||
Fluid and electrolyte disorder | 1.05 (1.00–1.12) | 4 (+++) | ||||||
Chronic pulmonary disease | 1.28 (1.22–1.34) | 3 (++) | ||||||
Paralysis | 1.13 (0.97–1.31) | 4 (+++) | ||||||
Psychiatric disorder | 1.43 (1.12–1.70) | 3 (++) | ||||||
- | ||||||||
- | ||||||||
3 (++) | ||||||||
Cardiovascular disease (CVD) | ||||||||
- | ||||||||
1 | ||||||||
- | ||||||||
- | ||||||||
- | ||||||||
- | ||||||||
3 (++) | ||||||||
Congestive Cardiac/Heart Failure (CCF/CHF) | 3 | - | - | 5 | 2 | - | 5 (+++) | |
Valvular disease | 1 | - | - | 2 | 1 | - | 3 (++) | |
Peripheral vascular disease | 1 | 1 | - | - | 1 | - | 3 (++) | |
History of percutaneous coronary intervention or cardiac surgery | 1 | - | - | - | - | - | 2 (+) | |
BMI, obesity, and weight loss | ||||||||
BMI (continuous) | - | 1 | - | 1 | 1 | - | 4 (+++) | |
BMI underweight (reference category = overweight (25–30)) | - | - | - | - | 1 | - | 4 (+++) | |
BMI normal weight (reference category = overweight (25–30)) | - | - | - | - | 1 | - | 4 (+++) | |
BMI obese (reference category = overweight (25–30)) | - | - | - | - | 1 | - | 4 (+++) | |
BMI very obese (reference category = overweight (25–30)) | - | - | - | - | 1 | - | 4 (+++) | |
BMI morbidly obese (reference category = overweight (25–30)) | - | - | - | 1 | - | - | 4 (+++) | |
BMI > 30 (reference category = normal weight) | - | - | - | 1 | - | - | 2 (+) | |
Increasing BMI (reference category = <25) | - | 1 | - | - | - | - | 1 (+) | |
Obesity | 1 | 1 | - | 2 | 1 | - | 2 (+) | |
Morbid obesity | - | 1 | - | - | - | - | 2 (+) | |
Weight loss | - | 1 | ||||||
1 (+) | ||||||||
Post-traumatic stress disorder (PTSD) | ||||||||
- | ||||||||
1 | ||||||||
- | ||||||||
- | ||||||||
- | ||||||||
- | ||||||||
1 (+) | ||||||||
Anxiety disorder | ||||||||
- | ||||||||
2 | ||||||||
- | ||||||||
- | ||||||||
- | ||||||||
- | ||||||||
2 (+) | ||||||||
Alcohol abuse | ||||||||
1 | ||||||||
2 | - | - | - | - | 3 (++) | |||
Drug abuse (including general substance abuse designation, and drug/alcohol abuse (combined category in Kurtz)) | 1 | 1 | - | 2 | - | - | 4 (+++) | |
Psychoses | 1 | - | - | - | - | - | 2 (+) | |
Neoplastic | ||||||||
History of cancer | 1 | - | - | 2 | 1 | - | 4 (+++) | |
Disseminated cancer | 1 | - | - | 1 | 2 | - | 3 (++) | |
Lymphoma | - | - | - | 2 | - | - | 4 (+++) | |
Neurological | ||||||||
Previous stroke | - | 1 | - | 1 | - | 1 | 4 (+++) | |
Dementia | - | - | - | 1 | - | - | 4 (+++) | |
Other neurological disorder | 1 | - | - | 2 | 1 | - | 3 (++) | |
In-hospital complications | ||||||||
Deep vein thrombosis | - | - | - | 1 | - | - | 5 (+++) | |
Pulmonary embolism | - | - | - | 1 | - | - | 5 (+++) | |
Any complication | 1 | - | - | 1 | - | - | 6 (++++) | |
Any medical complication | 1 | - | - | 1 | - | - | 4 (+++) | |
Any surgical complication | 1 | - | - | 1 | - | - | 4 (+++) | |
Urinary tract infection | - | - | - | 1 | - | - | 5 (+++) | |
Surgical site infection | - | - | - | 1 | - | - | 5 (+++) | |
Sepsis | 1 | - | - | - | 1 | - | 4 (+++) | |
Cardiac (including cardiac arrest and myocardial infarction) | - | - | - | 1 | - | - | 4 (+++) | |
Pneumonia | - | - | - | 1 | - | - | 5 (+++) | |
Acute renal failure | - | - | - | 1 | - | - | 5 (+++) | |
Cerebrovascular accident (CVA) or transient ischaemic attach (TIA) | 1 | - | - | - | - | - | 3 (++) | |
Renal | ||||||||
Chronic kidney disease (CKD) | 1 | - | - | 2 | 1 | - | 5 (+++) | |
Dialysis dependence | - | - | - | 1 | - | - | 4 (++) | |
Renal failure–acute, preoperative | - | - | - | - | 1 | - | 4 (++) | |
Renal failure/disease–chronicity unspecified | 1 | - | - | 5 | - | - | 6 (++++) | |
Rheumatological and autoimmune | ||||||||
Rheumatoid arthritis/collagen vascular diseases | 1 | - | - | - | - | - | 3 (++) | |
Steroid or other immunosuppressant use for chronic condition | - | - | - | 1 | - | - | 3 (++) | |
Other | ||||||||
Preoperative opioid use | - | - | - | 2 | 1 | - | 3 (++) | |
Post-discharge opioid use | - | - | - | 1 | - | - | 1 (+) | |
Preoperative medication use (general) | - | - | - | 1 | - | - | 3 (++) | |
Preoperative medication use (analgesics) | - | - | - | 1 | - | 1 (+) | ||
Preoperative medication use (anticonvulsants) | - | - | - | 1 | - | - | 2 (+) | |
Preoperative medication use (Serotonin–norepinephrine reuptake inhibitor (SNRIs)) | - | - | - | - | 1 | - | 2 (+) | |
Preoperative medication use (Tricyclic antidepressants (TCAs)) | - | - | - | - | 1 | - | 2 (+) | |
Preoperative medication use (sedatives) | - | - | - | - | 1 | - | 2 (+) | |
Wound class | 1 | - | - | - | 2 | - | 4 (+++) |
3.4. Synthesis of Evidence
,
and
, and
, present the findings for every risk factor identified in the included studies, including high, moderate, low, and very low-quality evidence. A summary of the high and moderate quality evidence for risk factors that correlated with readmission are presented. Forest plots for all meta-analyses are available (
).
3.4.5. Different Types of Readmission
The focus of this review is on 30-day readmission due to any cause, so the main summary of findings tables comprise studies that analysed all-cause readmission. Three of these studies additionally analysed readmission due to specific causes: D’Apuzzo et al. 2017 [
], Ali et al. 2019 [
], and Rudasil et al. 2019 [
]. An in-depth discussion of the differences between risk factor profiles for each of these outcomes is given in the full text articles. One other study, Anthony et al. 2018 [
], did not analyse all-cause readmission, instead focusing on readmission due to surgical site infection only. On multivariate logistic regression analysis (OR (95% confidence interval)), risk factors found to be associated with risk of readmission were: age 18–30 (reference category <18: 0.114 (0.02–0.63)), female sex (0.559 (0.53–0.59)), private insurance and Medicaid (reference category Medicare: 0.679 (0.63–0.73) and 1.489 (1.32–1.68), respectively), hypertension (1.189 (1.11–1.27)), obesity (1.182 (1.11–1.26)), and diabetes (1.122 (1.05–1.2)). The results for each of these studies are available in
.