Background COVID-19 outbreak lead to nationwide lockdown in Finland on the March 16th, 2020. Previous data regarding to the patient load in the emergency departments during pandemics is scarce. Our aim is to describe the effect of national lockdown and social distancing on the number and reasons for emergency department (ED) visits and inpatient admissions in three large volume hospitals prior to and after the outbreak of the COVID-19 epidemic in Finland. Methods Data for this register-based retrospective cohort study were collected from three large ED’s in Finland, covering 1/6 of the Finnish population. All patients visiting ED’s six weeks before and six weeks after the lockdown were included. Pediatric and gynecological patients were excluded. Numbers and reasons for ED visits and inpatient admissions were collected. Corresponding time period in 2019 was used as reference. Results A total of 40,653 ED visits and 12,226 inpatient admissions were analyzed. The total number of ED visits decreased 16% after the lockdown, whereas the number of inpatient admissions decreased 15% (p < 0.001). This change in inpatient admissions was similar in all participating hospitals. Visits due to back or limb pain decreased 31% and infectious diseases 28%. The visit rate and inpatient admissions due to acute myocardial infarction and strokes remained stable throughout the study period. Interestingly, the rate of inpatient admissions due to psychiatric diagnoses remained unchanged, although the ED visit rate decreased by 19%. The number of ED visits (n = 282) and inpatient admissions (n = 55) due to COVID-19 remained low in the participating hospitals. Conclusions Changes in ED visits and inpatient admissions prior to and during the early phase of the COVID-19 outbreak were unpredictable, and our results may help hospitals and especially ED’s focus their resources better. Surprisingly, there was a major decrease in the rate of ED visits due to back or limb pain and not so surprisingly in infectious diseases. Rates of acute myocardial infarctions and cerebral strokes remained stable. In summary, stabile resources for the treatment of patients with severe diseases will be needed in hospitals and ED’s.

PurposeDespite the comprehensive literature on the anatomical risk factors for patellar dislocation, knowledge on the risk factors for subsequent osteochondral fracture (OCF) remains limited. MethodsMagnetic resonance imaging was used to compare measures of patellofemoral anatomy in patients with OCF after patellar dislocation and propensity score matched patients without OCF. For differing measures, limit values showing a 50% probability for the occurrence of OCF were calculated using predictive logistic regression modelling. Proportions of abnormal measures in the groups were compared using Chi‐square test. The association of anatomical measures with OCF location was examined by comparing subgroup mean values in the different OCF locations. ResultsPropensity score matching provided a total of 111 matched pairs of patients with OCF and patients without OCF. The patients with and without OCF differed in patellotrochlear index (PTI; 0.54 [95% CI 0.52–0.57] vs. 0.47 [95% CI 0.45–0.49]; p < 0.001), tibial tubercle‐posterior cruciate ligament distance (TT‐PCL; 21.6 mm [95% CI 21.0–22.3 mm] vs. 20.5 mm [95% CI 20.0–21.1 mm]; p = 0.013), trochlear depth (2.5 mm [95% CI 2.3–2.7 mm] vs. 3.0 mm [95% CI 2.8–3.2 mm]; p < 0.001) trochlear facet asymmetry ratio (0.54 [95% CI 0.51–0.57] vs. 0.43 [95% CI 0.42–0.45]; p < 0.001) and trochlear condyle asymmetry ratio (1.04 [95% CI 1.03–1.04] vs. 1.05 [95% CI 1.04–1.05]; 0.013. Thresholds for increased OCF risk were > 0.51 for PTI  > 21.1 mm for TT‐PCL < 2.8 mm for trochlear depth > 0.48 for trochlear facet asymmetry ratio and < 1.04 for trochlear condyle asymmetry ratio. ConclusionIn patients with OCF after patellar dislocation, trochlear configuration and patella vertical location were closer to normal anatomy, whereas patella lateralization was more severe when compared to patients without OCF. These anatomical factors contribute to the risk of OCF during patellar dislocation. Level of evidenceIII.

Background A concern has been that health care reorganizations during the first COVID-19 wave have led to delays in elective surgeries, resulting in increased complications and even mortality. This multicenter study examined the changes in waiting times of elective surgeries during the COVID-19 pandemic in Finland. Methods Data on elective surgery were gathered from three Finnish public hospitals for years 2017–2020. Surgery incidence and waiting times were examined and the year 2020 was compared to the reference years 2017–2019. The mean annual, monthly, and weekly waiting times were calculated with 95% confidence intervals (CI). The most common diagnosis groups were examined separately. Findings A total of 88 693 surgeries were included during the study period. The mean waiting time in 2020 was 92.6 (CI 91.5–93.8) days, whereas the mean waiting time in the reference years was 85.8 (CI 85.1–86.5) days, resulting in an average 8% increase in waiting times in 2020. Elective procedure incidence decreased rapidly in the onset of the first COVID-19 wave in March 2020 but recovered in May and June, after which the surgery incidence was 22% higher than in the reference years and remained at this level until the end of the year. In May 2020 and thereafter until November, waiting times were longer with monthly increases varying between 7% and 34%. In gastrointestinal and genitourinary diseases and neoplasms, waiting times were longer in 2020. In cardiovascular and musculoskeletal diseases, waiting times were shorter in 2020. Conclusion The health care reorganizations due to the pandemic have increased elective surgery waiting times by as much as one-third, even though the elective surgery rate increased by one-fifth after the lockdown.

Background Survival analysis and effect of covariates on survival time is a central research interest. Cox proportional hazards regression remains as a gold standard in the survival analysis. The Cox model relies on the assumption of proportional hazards (PH) across different covariates. PH assumptions should be assessed and handled if violated. Our aim was to investigate the reporting of the Cox regression model details and testing of the PH assumption in survival analysis in total joint arthroplasty (TJA) studies. Methods We conducted a review in the PubMed database on 28th August 2019. A total of 1154 studies were identified. The abstracts of these studies were screened for words “cox and “hazard*” and if either was found the abstract was read. The abstract had to fulfill the following criteria to be included in the full-text phase: topic was knee or hip TJA surgery; survival analysis was used, and hazard ratio reported. If all the presented criteria were met, the full-text version of the article was then read. The full-text was included if Cox method was used to analyze TJA survival. After accessing the full-texts 318 articles were included in final analysis. Results The PH assumption was mentioned in 114 of the included studies (36%). KM analysis was used in 281 (88%) studies and the KM curves were presented graphically in 243 of these (87%). In 110 (45%) studies, the KM survival curves crossed in at least one of the presented figures. The most common way to test the PH assumption was to inspect the log-minus-log plots (n = 59). The time-axis division method was the most used corrected model (n = 30) in cox analysis. Of the 318 included studies only 63 (20%) met the following criteria: PH assumption mentioned, PH assumption tested, testing method of the PH assumption named, the result of the testing mentioned, and the Cox regression model corrected, if required. Conclusions Reporting and testing of the PH assumption and dealing with non-proportionality in hip and knee TJA studies was limited. More awareness and education regarding the assumptions behind the used statistical models among researchers, reviewers and editors are needed to improve the quality of TJA research. This could be achieved by better collaboration with methodologists and statisticians and introducing more specific reporting guidelines for TJA studies. Neglecting obvious non-proportionality undermines the overall research efforts since causes of non-proportionality, such as possible underlying pathomechanisms, are not considered and discussed.

Background and purpose — COVID-19 lockdowns have resulted in noteworthy changes in trauma admissions. We report and compare the incidence and characteristics of severe injuries (New Injury Severity Score [NISS] > 15) during the COVID-19 lockdown in Finland with earlier years. Methods — We retrospectively analyzed incidence rate, injury severity scores, injury patterns, and mechanisms of injury of all severely injured patients (NISS >15) in 4 Finnish hospitals (Tampere University Hospital, Kuopio University Hospital, Central Finland Hospital, Mikkeli Central Hospital) during the 11-week lockdown period (March 16–May 31, 2020) with comparison with a matching time period in earlier years (2016–2018). These 4 hospitals have a combined catchment area of 1,150,000 people or roughly one-fifth of the population of Finland. Results — The incidence rate of severe injuries during the lockdown period was 4.9/10 5 inhabitants (95% CI 3.7–6.4). The incidence rate of severe injuries during years 2016–2018 was 5.1/10 5 inhabitants (CI 3.9–6.5). We could not detect a significant incidence difference between the lockdown period and the 3 previous years (incidence rate difference –0.2 (CI –2.0 to 1.7). The proportion of traffic-related accidents was 55% during the lockdown period and 51% during previous years. There were no detectable differences in injury patterns. During the lockdown period, the mean age of patients was higher (53 years vs. 47 years, p = 0.03) and the rate of severely injured elderly patients (aged 70 or more) was higher (30% vs. 16%). Interpretation — Despite heavy social restrictions, the incidence of severe injuries during the lockdown period was similar to previous years. Notably, a decline in road use and traffic volumes did not reduce the number of severe traffic accidents. Although our data is compatible with a decrease of 2.0 to an increase of 1.7 severely injured patients per 10 5 inhabitants, we conclude that severely injured patients do not disappear even during pandemic and stabile hospital resources are needed to treat these patients.

ImportanceUniversal ultrasonographic screening for developmental dysplasia of the hip (DDH) has gained increasing popularity despite the lack of benefit in terms of reducing the rates of late-detected cases (age ≥12 weeks) in randomized clinical trials.ObjectiveTo report the reported incidence of DDH in the English scientific literature and compare rates of late-detected cases in settings with different DDH screening strategies.Data SourcesPubMed, Scopus, and Web of Science databases were searched on November 25 and 27, 2021. No time filters were used in the search.Study SelectionAll observational studies reporting the incidence of early-detected or late-detected (age ≥12 weeks) DDH were included. Non-English reports were excluded if the abstract did not include enough information to be included for analysis.Data Extraction and SynthesisThe number of newborns screened and the detection rates were extracted. Meta-analysis calculated the pooled incidence of DDH per 1000 newborns with 95% CIs using a random- or fixed-effects model. This study is reported according to the PRISMA and MOOSE guidelines.Main Outcomes and MeasuresThe main outcome measures were early detection, early treatment, late detection, and operative treatment incidences.ResultsA total of 1899 studies were identified, 203 full texts were assessed, and 76 studies with 16 901 079 infants were included in final analyses. The early detection rate was 8.4 (95% CI, 4.8-14.8) infants with DDH per 1000 newborns with clinical screening, 4.4 (95% CI, 2.4-8.0) infants with DDH per 1000 newborns with selective ultrasonographic screening, and 23.0 (95% CI, 15.7-33.4) infants with DDH per 1000 newborns with universal ultrasonographic screening. Rates for nonoperative treatment were 5.5 (95% CI, 2.1-14) treatments per 1000 newborns with clinical screening, 3.1 (95% CI, 2.0-4.8) treatments per 1000 newborns with selective ultrasonographic screening, and 9.8 (95% CI, 6.7-14.4) treatments per 1000 newborns with universal ultrasonographic screening. The incidence of late-detected DDH was 0.5 (95% CI, 0.2-1.5) infants with DDH per 1000 newborns with clinical screening, 0.6 (95% CI, 0.3-1.3) infants with DDH per 1000 newborns with selective ultrasonographic screening, and 0.2 (95% CI, 0.0-0.8) infants with DDH per 1000 newborns with universal ultrasonographic screening. The corresponding incidences of operative treatment were 0.2 (95% CI, 0.0-0.9) operations per 1000 newborns with clinical screening, 0.5 (95% CI, 0.4-0.7) operations per 1000 newborns with selective ultrasonographic screening, and 0.4 (95% CI, 0.2-0.7) operations per 1000 newborns with universal ultrasonographic screening.Conclusions and RelevanceThis meta-analysis found that early detection rates and nonoperative treatments were higher with universal screening. The late detection and operative treatment rates with universal screening were similar to those among selectively and clinically screened newborns. Based on these results, universal screening may cause initial overtreatment without reducing the rates of late detection and operative treatment.

Lisfranc injury was originally described as a partial or complete dislocation of the tarsometatarsal (TMT) joints by Quenu and Kuss in 1909. 18 Nunley and Vertullo 16 described that the injury can also be subtle when there is no detectable dislocation in nonweightbearing radiographs. Recently, however, Chiodo and Myerson 2 introduced a new approach to these injuries where they suggested to divide the injuries in medial (TMT 1), central (TMT 2-3), and lateral (TMT 4-5) columns. Lau et al 10 completed the columnar approach with a classification where the prognosis of injury is related to number of affected columns and displacement (less or more than 2 mm) instead of the diastasis between I and II TMT joints. Main and Jowett 13 developed a classification for Chopart injuries, where they stated that these injuries vary from small avulsion fragments to severe subluxation of the whole joint. Diagnostics have become more precise as a result of the more common use of computed tomography (CT). It is unclear whether there is such a type of injury as "purely ligamentous injury," or whether is it detectable from bony avulsion fragments. 7,8,17 The definitions and classifications of these injuries has changed, and still, 100 799741F AIXXX10.

Background: Literature describing the anatomic characteristics of osteochondral fractures (OCFs) in the knee joint after patellar dislocation is scarce. Purpose: To describe the patterns of OCFs in the knee joint after acute or recurrent patellar dislocation in a sample of patients from 2 orthopaedic trauma centers. Study Design: Case series; Level of evidence, 4. Methods: In this multicenter study, all patients who had International Classification of Diseases, 10th Revision, diagnostic codes S83.0 and M22.0 between 2012 and 2018 were screened. Of the 2181 patients with clinically diagnosed patellar dislocation, 1189 had undergone magnetic resonance imaging (MRI). Patients with diagnosed patellar dislocation and osteochondral fragment verified on MRI scans were included. Demographic and clinical data were collected from electronic patient records. OCF location and size were assessed from MRI scans. Results were further compared in subgroups by sex, skeletal maturity, and primary versus recurrent patellar dislocation. Results: An OCF was detected in 134 patients with injured knees, all of whom were included in the final analysis. It occurred in the patella in 63% of patients, in the lateral femoral condyle in 34%, and in both locations in 3%. The median OCF size was 146 mm2 (interquartile range, 105-262 mm2). There was no statistically significant difference in OCF size between patellar and lateral femoral condyle fractures. Patellar OCFs were more frequent in female than male patients ( P = .009) and were larger after primary than recurrent dislocation ( P = .040). Conclusion: OCFs were mainly located in the medial facet of the patella and in the lateral femoral condyle, with these locations accounting for approximately two-thirds and one-third of all OCFs, respectively. Proportion of patellar OCF was higher in female than in male. Patellar OCFs may be larger after primary than recurrent dislocation.