European Journal of Trauma and Emergency Surgery https://doi.org/10.1007/s00068-021-01767-0 ORIGINAL ARTICLE Neurosurgical emergency management during the lockdown period in health care regions in Spain with different COVID‑19 impact: lessons learned to improve outcomes on the future waves Maria L. Gandía‑González1 · Jose M. Viñuela‑Prieto1 · Laura Barrios2 · Carlos Alarcón3 · Fuat Arikan4 · Cinta Arráez5 · Carlos J. Domínguez6 · Jose F. Alén7 · Raquel Gutiérrez‑González8,9 · Angel Horcajadas10 · Fernando Muñoz Hernández11 · Alejandra Narváez12 · Igor Paredes13 · Rebeca Pérez‑Alfayate14 · Angel Rodríguez de Lope15 · Fernando Ruiz‑Juretschke16 · Freddy J. Salge Arrieta17 · Sonia Tejada18 · Martin Tamarit19 · Thomaz Topczewski20 · Jesus Lafuente12 Received: 5 April 2021 / Accepted: 18 July 2021 © Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract Background COVID-19 has overloaded health care systems, testing the capacity and response in every European region. Concerns were raised regarding the impact of resources’ reorganization on certain emergency pathology management. The aim of the present study was to assess the impact of the outbreak (in terms of reduction of neurosurgical emergencies) during lockdown in different regions of Spain. Methods We analyzed the impact of the outbreak in four different affected regions by descriptive statistics and univariate comparison with same period of two previous years. These regions differed in their incidence level (high/low) and in the time of excess mortality with respect to lockdown declaration. That allowed us to analyze their influence on the characteristics of neurosurgical emergencies registered for every region. Results 1185 patients from 18 neurosurgical centers were included. Neurosurgical emergencies that underwent surgery dropped 24.41% and 28.15% in 2020 when compared with 2019 and 2018, respectively. A higher reduction was reported for the most affected regions by COVID-19. Non-traumatic spine experienced the most significant decrease in number of cases. Life-threatening conditions did not suffer a reduction in any health care region. Conclusions COVID-19 affected dramatically the neurosurgical emergency management. The most significant reduction in neurosurgical emergencies occurred on those regions that were hit unexpectedly by the pandemic, as resources were focused on fighting the virus. As a consequence, life-threating and non-life-threatening conditions’ mortality raised. Results in regions who had time to prepare for the hit were congruent with an organized and sensible neurosurgical decision-making. Keywords Emergency · COVID-19 · Lockdown · Neurosurgery · Pandemic · Collateral damages Introduction Attention has been inevitably directed towards COVID-19 patients and pandemic control efforts; therefore, healthcare The disruptive Severe Acute Respiratory Syndrome Coro- reorganization at all levels (central state, autonomous com- navirus 2 (SARS-CoV2) pandemic tested our health care munities and hospital centers) was indispensable to protect system resilience and preparedness, which was initially patients and staff and to increase the number of necessary collapsed by a flood of COVID-19 patients being affected resources to treat the high percentage of SARS-CoV2 despite the measures that have been quickly implemented infected patients [3, 4]. [1, 2]. In our country, 3.733.600 COVID-19 cases have been confirmed to date 11th June 2021, and 80.501 deaths have been registered according to official registry by the Min- * Maria L. Gandía‑González istry of Health [5]. There were big differences in the inci- marisagg4@hotmail.com dence and time lapse between outbreak starting and plan- Extended author information available on the last page of the article ning, being Madrid, Castilla la Mancha, and Catalonia the 13 Vol.:(0123456789) M. L. Gandía‑González et al. most affected healthcare regions during the first outbreak, Variables in this order [6]. Madrid started on March 8th, Castilla la Mancha, March 15th, and Catalonia on March 20th, consid- To explore the different regions across the country that ering the date of outbreak starting when excess mortality suffered the strike of the pandemic at a different time we was registered by National Epidemiological Surveillance defined four categories. Briefly, the main epidemiological Network–Carlos III Institute [7]. differences between them were incidence, time of outbreak The high incidence of COVID-19 patients in Spain has declaration and whether the lockdown period had been allowed us to build an important registry with information declared or not when the outbreak started. from hospitals in autonomous communities that experienced The groups were defined as follows: completely different scenarios. Due the decentralized man- agement of the Spanish Public Health Care System, different -Group A (Madrid): high incidence, first region to achieve approaches in terms of planification, organization, and strat- excess of mortality and this happened before lockdown egy were applied in each autonomous community [4]. Some (March 8th). healthcare administrative regions were caught unprepared -Group B (Castilla la Mancha): high incidence, excess like Madrid that was severely hit without notice. Others, like of mortality achieved 1 week later (March 15th), under Catalonia and Andalucía, where the outbreak was delayed by lockdown. some days (12 and 13, respectively), were better organized -Group C (Catalonia): high incidence, excess of mortality and prepared for the pandemic. achieved 12 days later (March 20th), under lockdown. Additionally, the message of generalized hospital collapse -Group D (Andalucía): low incidence, excess of mortal- and the fear spread by mass media, dissuaded many patients ity achieved 13 days later (March 21st), under lockdown. to attend to the hospitals when feeling sick [8, 9]. This situ- ation led to a significant decrease in the number of emergen- Neurosurgical pathologies treated as emergency surgeries cies related to pathologies different than COVID-19 [10, 11]. were classified into non-traumatic spine, trauma including The aim of the present study was to assess the impact of traumatic brain injury (TBI) and traumatic spine, vascular, the outbreak (in terms of reduction of neurosurgical emer- oncology, cerebrospinal fluid (CSF) related surgeries, and gencies) during lockdown in different regions of Spain by others (wound infection, functional, and miscellanea). Addi- comparing it with the same period of the 2 previous years. tionally, they were classified into life-threatening (trauma, We undertook the analysis of the available data hoping that vascular, oncology and CSF) and non-life-threatening lessons learned might be useful to prevent excess of mortal- pathologies (non-traumatic spine and others). Life-threaten- ity and morbidity in patients for future waves of the SARS- ing conditions were considered those patients that required CoV-2 pandemic and be an example for other countries in a surgical intervention to survive. need of health care reorganization. Statistical analysis Methods Descriptive statistics were expressed as mean ± SD (stand- ard deviation) for continuous variables, median (IQR; Design, setting, and population interquartile range) for ordinal variables and as n (%) for categorical variables. Comparison of proportions for cat- We retrospectively reviewed the database of the Neurosur- egorical variables was performed by either Fisher’s exact gery Departments from 18 hospitals across Spain during the test or chi-squared test. For each value of the categorical first outbreak. This study was approved by the coordinating variable, the rest of categories acted as reference. center’s Ethics Committee of Clinical Research and carried To compare continuous variables among the three peri- out following their recommendations. ods included in the study we used the ANOVA test with Data from all neurosurgical emergencies registered post hoc Bonferroni corrections for multiple comparisons. between 14th March and 14th May 2020—lockdown period To compare ordinal variables and medians we employed and peak of the wave—were retrospectively collected, the Kruskal–Wallis’ H test. A Dunn–Bonferroni’s non- including only patients ≥ 18 years old who actually under- parametric pairwise comparison for post hoc testing after went surgery. In addition, neurosurgical emergencies that a statistically significant Kruskal–Wallis test was also per- underwent surgery from the same period of time of the 2 formed. The level of significance was defined as P < 0.05. previous years were also collected. All statistical analyses were performed using ­S PSS® Version 20 ­(IBM®, Chicago, USA). 13 Neurosurgical emergency management during the lockdown period in health care regions in Spain… Results 2020. Trauma emergencies were significantly lower in 2020 in comparison with the previous years for the whole study Population and descriptive data sample. No statistically significant differences were detected among specific groups. We collected a total of 1185 patients from 18 centers who The proportion of vascular emergencies was not sig- underwent an emergency neurosurgical procedure between nificantly different in 2020 with respect to previous years. March 14th and May 14th. Worth noting, a 24.41% and a Oncological emergency procedures experienced a significant 28.15% reduction in the number of patients were observed decrease in group D in 2020 (P < 0.001), while in group C in 2020 when compared with 2019 and 2018, respectively. the tendency was the opposite (P = 0.027). CSF-related sur- Results regarding distribution among different regions are geries’ frequency was significantly higher among the whole summarized in Table 1. Patient and pathologies’ character- sample and particularly in group A (P < 0.001 and P = 0.001, istics are summarized in Table 2. respectively). Regarding the COVID-19’s PCR results obtained from Main results patients attended in 2020, an overall 7.5% positive rate was observed. Among groups, the highest positive rate was A chi-squared test was used to compare the number of sur- observed in group B and the lowest in group D. The amount geries between groups. All groups suffered a reduction in of indeterminate results ranged from 0% in group B to as the volume of patients underwent surgery in 2020 in com- high as a 29% in group C. Importantly, the rate of negative- parison with 2019 that ranged from a 39% (group A) and to-positive change during stay was not negligible for certain 6% (group D) (Fig. 1). However, only groups A, B, and D groups, such as A and B, where it was above 5% (Table 3). reported a decrease in number of patients when comparing Regarding the median GCS at their arrival at the ER, only with 2018. Only group C showed a significant change in a significant reduction was observed when comparing 2020 distribution (P = 0.012), with the lowest volume of patients to the previous years in groups A and D. When comparing in 2018 (Table 1). GCS at arrival between life-threatening and non-life-threat- No major redistribution of patients between hospitals ening pathologies, no statistically significant differences within the same group was observed. Overall, all hospitals in were observed among the 3 years studied. When this com- group A and B experienced a wide decrease of neurosurgical parison was further explored for each group no significant emergencies. In group C, all hospitals registered a reduced differences were observed whatsoever (Table 4). number of neurosurgical emergencies when compared with The proportion of emergency neurosurgical patients 2019. Group D showed a minimum reduction of cases. admitted in ICU beds increased significantly in 2020 when Regarding patient characteristics, no significant differ- compared with previous years for all groups. Groups A, B ences were observed in age, gender, admission after the and C reported a higher increase than group D from 2019 surgery, mean stay at ICU in days and mortality. Group C to 2020, without statistical significance though. In terms of showed a statistically significant reduction on ward and ICU ICU stay, the mean stay was reduced, although not signifi- median stay. cantly, in groups A, B, and C, but not in group D. Interest- We also evaluated the pandemic influence on the dis- ingly, when considering the median ICU stay, the reduction tribution of pathologies requiring an emergency operation of the median ICU stay was significant (P = 0.015) when during the study period (Figs. 2, 3). Non-traumatic spine comparing 2019 with 2020 (P = 0.019) in group C. The same operations were significantly reduced considering the whole tendency among groups was observed regarding the mean sample and in group A, achieving statistical significance in and the median global stay, being reduced in all groups but achieving statistical significance only in group C (P = 0.025 and P < 0.001, respectively). Mortality analysis showed a worrying, yet not significant, Table 1  Yearly and regionally distribution of neurosurgical emergen- increase of mortality for our emergency neurosurgical opera- cies tions in all groups when comparing 2020 with either 2019 or Group 2018 2019 2020 P value 2018. In fact, group A alone experienced a 6–7% increased mortality when compared with previous years (Table 5). Group A 195 (43.9) 169 (40) 118 (37) 0.150 Mortality rates for non-life-threatening pathologies were Group B 44 (9.9) 33 (7.8) 28 (8.8) 0.556 significantly higher in 2020 whereas mortality rates for life- Group C 118 (26.6) 150 (35.5) 107 (33.5) 0.012 threatening pathologies were not. Further analysis regarding Group D 87 (19.6) 70 (16.6) 66 (20.7) 0.320 the pathologies registering higher rates of mortality during Total 444 (100) 422 (100) 319 (100) 0.083 2020 revealed that functional, infection-related, and other Results are expressed as n (%) 13 13 Table 2  Patient and pathologies’ characteristics Variable Group A Group B Group C Group D Total 2018 2019 2020 P 2018 2019 2020 P 2018 2019 2020 P 2018 2019 2020 P value 2018 2019 2020 P value value value value Age Mean ± SD 60.9 ± 17.8 62.0 ± 16.8 58.5 ± 18.7 0.258 61.1 ± 19.1 65.5 ± 16.7 63.9 ± 15.6 0.544 59.4 ± 18.6 60.8 ± 17.1 58.6 ± 16.2 0.595 61.4 ± 16.1 59.2 ± 17.6 58.0 ± 16.9 0.437 60.6 ± 17.8 61.4 ± 17.1 58.9 ± 17.3 0.151 Sex Female 81 (41.5) 60 (35.5) 49 (41.5) 14 (31.8) 14 (42.4) 13 (46.4) 65 (55.1) 66 (44) 60 (56.1) 32 (36.8) 31 (44.3) 28 (43.1) 192 (43.2) 171 (40.5) 150 (47.2) Male 114 (58.5) 109 (64.5) 69 (58.5) 0.434 30 (68.2) 19 (57.6) 15 (53.6) 0.414 53 (44.9) 84 (56) 47 (43.9) 0.089 55 (63.2) 39 (55.7) 37 (56.9) 0.586 252 (56.8) 251 (59.5) 168 (52.8) 0.195 Pathol- Spine 28 (14.4) 9 (5.3) 7 (5.9) 0.004 5 (11.4) 3 (9.1) 3 (10.7) 0.948 11 (9.3) 19 (12.7) 5 (4.7) 0.095 8 (9.2) 5 (7.1) 5 (7.6) 0.882 52 (11.7) 36 (8.5) 20 (6.3) 0.032 ogy Trauma 64 (32.8) 74 (43.8) 40 (33.9) 0.071 18 (40.9) 16 (48.5) 9 (32.1) 0.433 45 (38.1) 60 (40) 33 (30.8) 0.304 26 (29.9) 33 (47.1) 24 (36.4) 0.083 153 (34.5) 183 (43.4) 106 (33.2) 0.005 Vascular 30 (15.4) 33 (19.5) 20 (16.9) 0.578 13 (29.5) 8 (24.2) 10 (35.7) 0.619 26 (22) 37 (24.7) 21 (19.6) 0.629 14 (16.1) 10 (14.3) 14 (21.2) 0.537 83 (18.7) 88 (20.9) 65 (20.4) 0.708 Oncology 3 (1.5) 4 (2.4) 4 (3.4) 0.566 0 (0) 0 (0) 2 (7.1) 0.061 2 (1.7) 3 (2) 8 (7.5) 0.027 13 (14.9) 0 (0) 1 (1.5) < 0.001 18 (4.1) 7 (1.7) 15 (4.7) 0.046 CSF 45 (23.1) 19 (11.2) 33 (28) 0.001 3 (6.8) 1 (3) 1 (3.6) 0.699 19 (16.1) 15 (10) 20 (18.7) 0.121 16 (18.4) 12 (17.1) 14 (21.2) 0.824 83 (18.7) 47 (11.1) 68 (21.3) < 0.001 Others 25 (12.8) 30 (17.8) 14 (11.9) 0.278 5 (11.4) 5 (15.2) 3 (10.7) 0.841 15 (12.7) 16 (10.7) 20 (18.7) 0.170 10 (11.5) 10 (14.3) 8 (12.1) 0.864 55 (12.4) 61 (14.5) 45 (14.1) 0.641 (infection, functional) GCS Median–IQR 15 (11–15) 14 (10–15) 13 0.022 14 (11–15) 14 (9–15) 13 (7–15) 0.312 14 (10.3– 15 (10–15) 15 (12–15) 0.630 15 (12–15) 15 (12.5– 14 (8–15) 0.036 15 (11–15) 15 (10–15) 14 (9–15) 0.061 (8.5–15) 15) 15) Admis- N (%) 195 (100) 168 (99.4) 113 (100) 0.401 44 (100) 33 (100) 28 (100) NA 84 (100) 129 (100) 76 (100) NA 87 (100) 68 (100) 64 (98.5) 0.302 410 (100) 398 (99.7) 281 (99.6) 0.521 sion Days 22.9 ± 28.0 21.8 ± 20.5 18.3 ± 22.2 0.276 19.5 ± 23.4 19.3 ± 18.1 15.1 ± 8.9 0.584 22.1 ± 26.9 25.6 ± 38.8 13.0 ± 23.4 0.025 25.1 ± 26.8 38.1 ± 55.8 25.1 ± 30.5 0.076 22.8 ± 27 25.6 ± 35.3 18.1 ± 24.1 0.006 (mean ± SD) ICU N (%) 93 (47.7) 95 (56.2) 70 (59.3) 0.093 29 (65.9) 24 (72.7) 25 (89.3) 0.084 61 (51.7) 86 (57.3) 66 (61.7) .315 29 (33.3) 33 (47.1) 31 (47) 0.128 212 (47.7) 238 (56.4) 192 (60.2) 0.002 Days 16 ± 21.4 12.8 ± 14.4 12.3 ± 13.8 0.296 12.8 ± 12.4 11.4 ± 16.9 8.5 ± 7.1 0.455 10.9 ± 12.6 16.8 ± 38.4 7.8 ± 10.6 0.101 10.2 ± 8.9 9.4 ± 9.1 11.8 ± 9.6 0.553 13.3 ± 16.8 13.6 ± 25.7 10.2 ± 11.5 0.143 (mean ± SD) Mortal- 21 (10.8) 20 (11.8) 21 (17.8) 0.175 7 (15.9) 8 (24.2) 7 (25) 0.558 15 (12.7) 12 (8) 14 (13.1) 0.330 8 (9.2) 9 (12.9) 9 (13.6) 0.650 51 (11.5) 49 (11.6) 51 (16) 0.126 ity CSF cerebrospinal fluid, GCS Glasgow coma scale, ICU intensive care unit, SD standard deviation, IQR interquartile range, NA not applicable M. L. Gandía‑González et al. Neurosurgical emergency management during the lockdown period in health care regions in Spain… Fig. 1  Neurosurgical emergen- cies’ evolution during study time. Arrows represent percen- tual variation with respect to previous years pathologies were the only ones experiencing a significant Unit (ICU) beds were highly reduced in many European increase during 2020. countries [12], but many of staff neurosurgeons were also relocated to Emergency and Internal Medicine Depart- ments [13] while elective surgeries were put on hold in Discussion the most hit countries for a long period of time [14, 15]. On these grounds, we analyzed the different impact of COVID-19 pandemic has changed our paradigm of surgi- COVID-19 pandemic on neurosurgical emergency proce- cal care, testing our capacity to prioritize one patient over dures based on the preparation and response capacity. To do another and to develop decision-making processes that so, we compared the volume and characteristics with those ensure an adequate management to our patients. Concern from emergencies attended during the same period of the about neurosurgical emergencies and potential “collateral two previous years, 2018 and 2019. Other similar studies damages” has been raised among neurosurgeons through- conducted in other countries have included variable time out the world [5]. Reallocation of resources and medical frames as controls, often considering only the year before staff to the COVID-19 patient’s has hugely affected neu- [16–18]. Due to the intrinsic variability of neurosurgi- rosurgical patient care delivery, particularly in severely cal emergencies along time, we considered that including affected countries such as Spain [1, 4]. Not only the num- a longer period of time for comparison would add further ber of available neurosurgical ward and Intensive Care validity to our conclusions. 13 M. L. Gandía‑González et al. assessing the repercussion of COVID-19 on neurosurgical activity [17, 18, 20–24]. Conversely, other authors have reported an increase in the neurosurgical hospitalization and treatment of their respective centers [16]. Those particular cases were usually observed in the context of emergency network reorganization, where hub hospitals were focused on the management of non-COVID-19 pathologies, a clear example of a better organization. The percentual distribution of cases among the four groups did not significantly varied along time, with the exception of group C that raised from a 26.6% of cases in 2018 to a 35.5% in 2019 and a 33.5% in 2020. That excep- tion could be explained due to the relatively maintained number of surgeries in that group that had enough time to prepare for the outbreak noting a smaller reduction in number of emergencies in the context of a marked reduc- tion of patients in groups A and B. We classified every neurosurgical emergency into one out of six different categories. In that sense, we share many Fig. 2  Emergency surgeries for every pathology evolution during classification criteria with other similar studies published study time. CSF cerebrospinal fluid-related pathologies to date [18, 23]. Nonetheless, in our work, we distinguished between degenerative and traumatic spinal injuries, including each Furthermore, resembling the impact of an earthquake, of them in a separated category (spine and trauma, respec- we considered 4 different regions along the Spanish geog- tively). We considered that, despite sharing the anatomical raphy (Fig. 4). Other single-country studies have tried to location, both types of pathologies are sufficiently different longitudinally analyze the impact of the pandemic by setting by means of acuity of onset, patient profile, global sever- a timeline along the 2020’s March–May period [19]. Despite ity of the associated lesions, medical and extra-hospital the restricted national framework of the present study, we management to get classified in different categories. Addi- consider that this subdivision based on the pandemic timing tionally, we considered traumatic spine caseload had prob- widens its international applicability. ably dropped due to lockdown, but there was no reason Inside our borders a broad spectrum of situations regard- to record a reduction of the rate of non-traumatic spine ing incidence, health care saturation and excess of mortality emergencies. were seen depending on the region considered, as our health Regarding the type of pathology attended during the 2020 care management and organization is transferred to regional lockdown period, it is worth noting that at the epicenter of political powers. the pandemic, namely group A, the number of non-traumatic Trias-Llimós et al [4]. Previously expressed their con- spine on-call surgeries significantly dropped. These obser- cerns about poor coordination among central and regional vations have also been reported by other authors [17, 20]. authorities and slow decision-making processes in some Probably, the deterrent effect of the pandemic on the ER cases, showing the weakness of a fragile decentralized sys- frequentation, the patients’ fear and the cancellation of con- tem. They urged to analyze the situation in different regions sultations may have accounted for this finding. In this regard, to identify health care needs that might be improved for the we consider that this type of pathology should be monitored, following waves. either by remote consultation or telemedicine, in the yet-to- In our study, we analyzed four different time windows come waves of the pandemic to avoid complications derived based on the excess of mortality instead of the first posi- from more advanced cases. tive cases, since that was the actual parameter that preceded For every period of time considered in the present study, health care overrun and precluded the most drastic confine- traumatic injuries were the most frequent causes to perform ment measures. Other similar studies have only considered emergency surgery. This finding is shared by other authors a single time frame based on the identification of the first [18, 24]. Nevertheless, trauma emergencies were signifi- COVID-19 cases [18]. cantly lower in 2020 in comparison with 2019 for the whole Globally, the data showed a marked decrease in the total sample. Those results could be explained by both the reduc- number of procedures performed during the same period tion of road mobility and the closure of work centers associ- this year 2020. This is consistent with the majority of studies ated to the lockdown state. 13 Neurosurgical emergency management during the lockdown period in health care regions in Spain… Fig. 3  Non-life-threatening and life-threatening emergency surgeries during study time (expressed as a percentage of total emergency surgeries). Mortality percentage evolution during study time for non-life- threatening and threatening pathologies Conversely to the generalized reduction observed in other differences were not significant for both groups. Other stud- types of neurosurgical emergencies, oncological and CSF- ies have also identified this reduction in GCS during the related surgeries experienced a proportional increase. Other pandemic in vascular emergencies, hydrocephalus and trau- similar studies have also identified this tendency, attributing matic brain injury [18]. it to prioritization policies during the pandemic [17, 18, 21], The proportion of patients needing an ICU bed after the as due to cancelled elective-surgery and consultations, emer- surgery suffered an increase in all groups. That shows a good gent surgeries drifted to either more severe, impossible-to- and responsible decision-making for patients, operating postpone and were operated by the emergency team. How- only those that have life-threatening conditions. However, ever, the fact that the absolute numbers remain relatively in exchange, the non-life-threatening conditions may have similar to previous years may indicate that the proportional been left behind and, consequently, would have suffered an increase is due to the reduction of the rest of pathologies. increase in mortality, particularly in group A. In our study, the mean and the median GCS obtained If we consider these data, we could conclude that group at Emergency Room (ER) arrival did not significantly var- C had enough time to prepare the resources and optimizing ied, with the exception of the most and the least pandemic- the turnover of the ICU beds. Also, these centers applied affected groups. Nevertheless, when differentiating between less ICU-time-consuming procedures that could be managed life-threatening and non-life-threatening pathologies those 13 M. L. Gandía‑González et al. Fig. 4  Geographical categoriza- tion into four different groups depending on percentage and date of excess mortality, resembling the impact of an earthquake Table 3  COVID-19’s PCR results Table 5  Yearly distribution of mortality regarding severity of the pathology 2020 (N = 319) Mortality Indeterminate Negative Positive Positivized during stay 2018 2019 2020 P value Group A 3 (2.5) 95 (80.5) 14 (11.9) 6 (5.1) Non-life-threatening 6 (5.6) 4 (4.1) 10 (15.4) 0.018 Group B 0 (0) 19 (67.9) 6 (21.4) 3 (10.7) Life-threatening 45 (13.4) 45 (13.8) 41 (16.1) 0.605 Group C 31 (29) 71 (66.4) 4 (3.7) 1 (0.9) Results are expressed as n (%) Group D 8 (12.1) 56 (84.8) 0 (0) 2 (3) Total 42 (13.2) 241 (75.5) 24 (7.5) 12 (3.8) Results are expressed as n (%) Mortality did not seem to significantly differ in groups C and D with respect to previous years. This supports that the fact that C and D did have more time to anticipate to the out- Table 4  Yearly distribution of GCS depending on the severity of the pathology break hospital crisis has an influence on patients’ outcomes. Nevertheless, in group A, a 6–7% increase in mortality GCS was observed in comparison with 2018 and 2019, respec- 2018 2019 2020 P value tively. Regardless of statistical significance, we believe that Non-life-threatening 15 (15–15) 15 (15–15) 15 (13–15) 0.137 those numbers could not be unapprised. Life-threatening 14 (9–15) 14 (9–15) 13 (8–15) 0.397 All the patients included in our sample were tested for SARS-CoV2 infection preoperatively by means of PCR Results are expressed as median (IQR) test. Globally, a 7.5% positive rate was detected. Neverthe- less, positive rates widely varied among regions (from 0% to 21.4%), being higher in the most affected ones. The fact with a short ICU stay to be performed during the peak of that mortality was not significantly higher in 2020 when the wave. compared to previous years suggests that, at least in our In our study, mortality did not significantly increased dur- sample, SARS-CoV2 infection did not add further risk to ing the 2020 lockdown with respect to the previous years. neurosurgical procedures. This finding is in line with other similar studies evaluating The interpretation of the present study has some limi- the impact of COVID-19 on neurosurgical practice [17]. tations. First, groups A and C represented big population 13 Neurosurgical emergency management during the lockdown period in health care regions in Spain… groups with 482 and 375 patients included, respectively. siona​les/​salud​Publi​ca/​ccayes/​alert​asAct​ual/​nCov/​docum​entos/​Actua​ However, group B only included 105 patients which makes lizac​ion_​395_​COVID-​19.​pdf. Accessed 14 June 2021. 6. 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Early report on the impact of Authors and Affiliations Maria L. Gandía‑González1 · Jose M. Viñuela‑Prieto1 · Laura Barrios2 · Carlos Alarcón3 · Fuat Arikan4 · Cinta Arráez5 · Carlos J. Domínguez6 · Jose F. Alén7 · Raquel Gutiérrez‑González8,9 · Angel Horcajadas10 · Fernando Muñoz Hernández11 · Alejandra Narváez12 · Igor Paredes13 · Rebeca Pérez‑Alfayate14 · Angel Rodríguez de Lope15 · Fernando Ruiz‑Juretschke16 · Freddy J. Salge Arrieta17 · Sonia Tejada18 · Martin Tamarit19 · Thomaz Topczewski20 · Jesus Lafuente12 1 11 Department of Neurosurgery, La Paz University Hospital, Neurosurgery, Hospital de la Santa Creu i Sant Pau, Idipaz, Paseo de La Castellana, 261, 28046 Madrid, Spain Autonomous University of Barcelona, Barcelona, Spain 2 12 Department of Statistics CSIC, Madrid, Spain Department of Neurosurgery, Parc de Salut Mar, Barcelona, 3 Spain Department of Neurosurgery, Hospital de Terrassa, Terrassa, 13 Spain Neurosurgery Department, Hospital 12 de Octubre, Madrid, 4 Spain Department of Neurosurgery, Neurotraumatology 14 and Neurosurgery Research Unit (UNINN), Vall d’Hebron Department of Neurological Surgery, Hospital Clínico San University Hospital and Vall d’Hebron Research Institute, Carlos, Madrid, Spain Barcelona, Spain 15 Department of Neurosurgery, Virgen de la Salud Hospital, 5 Department of Neurosurgery, Carlos Haya University Toledo, Spain Hospital, Málaga, Spain 16 Department of Neurosurgery, Hospital General Universitario 6 Department of Neurological Surgery, Germans Trias i Pujol Gregorio Marañón, Madrid, Spain University Hospital, Badalona, Spain 17 Department of Neurosurgery, Ramón y Cajal University 7 Department of Neurosurgery, La Princesa University Hospital, Madrid, Spain Hospital, Madrid, Spain 18 Department of Neurosurgery, Fundación Jiménez Díaz 8 Department of Neurosurgery, Puerta de Hierro University (IIS-FJD), Madrid, Spain Hospital, Madrid, Spain 19 Department of Neurosurgery, Hospital Universitario de 9 Department of Surgery, Faculty of Medicine, Autonomous Getafe, Getafe, Spain University of Madrid, Madrid, Spain 20 Department of Neurological Surgery, Hospital Clinic, 10 Neurosurgery Department, Virgen de las Nieves University Barcelona, Spain Hospital, Granada, Spain 13